Ali_sensynehealthchallenge_code.html

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  content: "\e252";
}
.glyphicon-triangle-top:before {
  content: "\e253";
}
.glyphicon-console:before {
  content: "\e254";
}
.glyphicon-superscript:before {
  content: "\e255";
}
.glyphicon-subscript:before {
  content: "\e256";
}
.glyphicon-menu-left:before {
  content: "\e257";
}
.glyphicon-menu-right:before {
  content: "\e258";
}
.glyphicon-menu-down:before {
  content: "\e259";
}
.glyphicon-menu-up:before {
  content: "\e260";
}
* {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
*:before,
*:after {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
html {
  font-size: 10px;
  -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
}
body {
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-size: 13px;
  line-height: 1.42857143;
  color: #000;
  background-color: #fff;
}
input,
button,
select,
textarea {
  font-family: inherit;
  font-size: inherit;
  line-height: inherit;
}
a {
  color: #337ab7;
  text-decoration: none;
}
a:hover,
a:focus {
  color: #23527c;
  text-decoration: underline;
}
a:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
figure {
  margin: 0;
}
img {
  vertical-align: middle;
}
.img-responsive,
.thumbnail > img,
.thumbnail a > img,
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  display: block;
  max-width: 100%;
  height: auto;
}
.img-rounded {
  border-radius: 3px;
}
.img-thumbnail {
  padding: 4px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: all 0.2s ease-in-out;
  -o-transition: all 0.2s ease-in-out;
  transition: all 0.2s ease-in-out;
  display: inline-block;
  max-width: 100%;
  height: auto;
}
.img-circle {
  border-radius: 50%;
}
hr {
  margin-top: 18px;
  margin-bottom: 18px;
  border: 0;
  border-top: 1px solid #eeeeee;
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  margin: -1px;
  padding: 0;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
[role="button"] {
  cursor: pointer;
}
h1,
h2,
h3,
h4,
h5,
h6,
.h1,
.h2,
.h3,
.h4,
.h5,
.h6 {
  font-family: inherit;
  font-weight: 500;
  line-height: 1.1;
  color: inherit;
}
h1 small,
h2 small,
h3 small,
h4 small,
h5 small,
h6 small,
.h1 small,
.h2 small,
.h3 small,
.h4 small,
.h5 small,
.h6 small,
h1 .small,
h2 .small,
h3 .small,
h4 .small,
h5 .small,
h6 .small,
.h1 .small,
.h2 .small,
.h3 .small,
.h4 .small,
.h5 .small,
.h6 .small {
  font-weight: normal;
  line-height: 1;
  color: #777777;
}
h1,
.h1,
h2,
.h2,
h3,
.h3 {
  margin-top: 18px;
  margin-bottom: 9px;
}
h1 small,
.h1 small,
h2 small,
.h2 small,
h3 small,
.h3 small,
h1 .small,
.h1 .small,
h2 .small,
.h2 .small,
h3 .small,
.h3 .small {
  font-size: 65%;
}
h4,
.h4,
h5,
.h5,
h6,
.h6 {
  margin-top: 9px;
  margin-bottom: 9px;
}
h4 small,
.h4 small,
h5 small,
.h5 small,
h6 small,
.h6 small,
h4 .small,
.h4 .small,
h5 .small,
.h5 .small,
h6 .small,
.h6 .small {
  font-size: 75%;
}
h1,
.h1 {
  font-size: 33px;
}
h2,
.h2 {
  font-size: 27px;
}
h3,
.h3 {
  font-size: 23px;
}
h4,
.h4 {
  font-size: 17px;
}
h5,
.h5 {
  font-size: 13px;
}
h6,
.h6 {
  font-size: 12px;
}
p {
  margin: 0 0 9px;
}
.lead {
  margin-bottom: 18px;
  font-size: 14px;
  font-weight: 300;
  line-height: 1.4;
}
@media (min-width: 768px) {
  .lead {
    font-size: 19.5px;
  }
}
small,
.small {
  font-size: 92%;
}
mark,
.mark {
  background-color: #fcf8e3;
  padding: .2em;
}
.text-left {
  text-align: left;
}
.text-right {
  text-align: right;
}
.text-center {
  text-align: center;
}
.text-justify {
  text-align: justify;
}
.text-nowrap {
  white-space: nowrap;
}
.text-lowercase {
  text-transform: lowercase;
}
.text-uppercase {
  text-transform: uppercase;
}
.text-capitalize {
  text-transform: capitalize;
}
.text-muted {
  color: #777777;
}
.text-primary {
  color: #337ab7;
}
a.text-primary:hover,
a.text-primary:focus {
  color: #286090;
}
.text-success {
  color: #3c763d;
}
a.text-success:hover,
a.text-success:focus {
  color: #2b542c;
}
.text-info {
  color: #31708f;
}
a.text-info:hover,
a.text-info:focus {
  color: #245269;
}
.text-warning {
  color: #8a6d3b;
}
a.text-warning:hover,
a.text-warning:focus {
  color: #66512c;
}
.text-danger {
  color: #a94442;
}
a.text-danger:hover,
a.text-danger:focus {
  color: #843534;
}
.bg-primary {
  color: #fff;
  background-color: #337ab7;
}
a.bg-primary:hover,
a.bg-primary:focus {
  background-color: #286090;
}
.bg-success {
  background-color: #dff0d8;
}
a.bg-success:hover,
a.bg-success:focus {
  background-color: #c1e2b3;
}
.bg-info {
  background-color: #d9edf7;
}
a.bg-info:hover,
a.bg-info:focus {
  background-color: #afd9ee;
}
.bg-warning {
  background-color: #fcf8e3;
}
a.bg-warning:hover,
a.bg-warning:focus {
  background-color: #f7ecb5;
}
.bg-danger {
  background-color: #f2dede;
}
a.bg-danger:hover,
a.bg-danger:focus {
  background-color: #e4b9b9;
}
.page-header {
  padding-bottom: 8px;
  margin: 36px 0 18px;
  border-bottom: 1px solid #eeeeee;
}
ul,
ol {
  margin-top: 0;
  margin-bottom: 9px;
}
ul ul,
ol ul,
ul ol,
ol ol {
  margin-bottom: 0;
}
.list-unstyled {
  padding-left: 0;
  list-style: none;
}
.list-inline {
  padding-left: 0;
  list-style: none;
  margin-left: -5px;
}
.list-inline > li {
  display: inline-block;
  padding-left: 5px;
  padding-right: 5px;
}
dl {
  margin-top: 0;
  margin-bottom: 18px;
}
dt,
dd {
  line-height: 1.42857143;
}
dt {
  font-weight: bold;
}
dd {
  margin-left: 0;
}
@media (min-width: 541px) {
  .dl-horizontal dt {
    float: left;
    width: 160px;
    clear: left;
    text-align: right;
    overflow: hidden;
    text-overflow: ellipsis;
    white-space: nowrap;
  }
  .dl-horizontal dd {
    margin-left: 180px;
  }
}
abbr[title],
abbr[data-original-title] {
  cursor: help;
  border-bottom: 1px dotted #777777;
}
.initialism {
  font-size: 90%;
  text-transform: uppercase;
}
blockquote {
  padding: 9px 18px;
  margin: 0 0 18px;
  font-size: inherit;
  border-left: 5px solid #eeeeee;
}
blockquote p:last-child,
blockquote ul:last-child,
blockquote ol:last-child {
  margin-bottom: 0;
}
blockquote footer,
blockquote small,
blockquote .small {
  display: block;
  font-size: 80%;
  line-height: 1.42857143;
  color: #777777;
}
blockquote footer:before,
blockquote small:before,
blockquote .small:before {
  content: '\2014 \00A0';
}
.blockquote-reverse,
blockquote.pull-right {
  padding-right: 15px;
  padding-left: 0;
  border-right: 5px solid #eeeeee;
  border-left: 0;
  text-align: right;
}
.blockquote-reverse footer:before,
blockquote.pull-right footer:before,
.blockquote-reverse small:before,
blockquote.pull-right small:before,
.blockquote-reverse .small:before,
blockquote.pull-right .small:before {
  content: '';
}
.blockquote-reverse footer:after,
blockquote.pull-right footer:after,
.blockquote-reverse small:after,
blockquote.pull-right small:after,
.blockquote-reverse .small:after,
blockquote.pull-right .small:after {
  content: '\00A0 \2014';
}
address {
  margin-bottom: 18px;
  font-style: normal;
  line-height: 1.42857143;
}
code,
kbd,
pre,
samp {
  font-family: monospace;
}
code {
  padding: 2px 4px;
  font-size: 90%;
  color: #c7254e;
  background-color: #f9f2f4;
  border-radius: 2px;
}
kbd {
  padding: 2px 4px;
  font-size: 90%;
  color: #888;
  background-color: transparent;
  border-radius: 1px;
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
}
kbd kbd {
  padding: 0;
  font-size: 100%;
  font-weight: bold;
  box-shadow: none;
}
pre {
  display: block;
  padding: 8.5px;
  margin: 0 0 9px;
  font-size: 12px;
  line-height: 1.42857143;
  word-break: break-all;
  word-wrap: break-word;
  color: #333333;
  background-color: #f5f5f5;
  border: 1px solid #ccc;
  border-radius: 2px;
}
pre code {
  padding: 0;
  font-size: inherit;
  color: inherit;
  white-space: pre-wrap;
  background-color: transparent;
  border-radius: 0;
}
.pre-scrollable {
  max-height: 340px;
  overflow-y: scroll;
}
.container {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
@media (min-width: 768px) {
  .container {
    width: 768px;
  }
}
@media (min-width: 992px) {
  .container {
    width: 940px;
  }
}
@media (min-width: 1200px) {
  .container {
    width: 1140px;
  }
}
.container-fluid {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
.row {
  margin-left: 0px;
  margin-right: 0px;
}
.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
  position: relative;
  min-height: 1px;
  padding-left: 0px;
  padding-right: 0px;
}
.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
  float: left;
}
.col-xs-12 {
  width: 100%;
}
.col-xs-11 {
  width: 91.66666667%;
}
.col-xs-10 {
  width: 83.33333333%;
}
.col-xs-9 {
  width: 75%;
}
.col-xs-8 {
  width: 66.66666667%;
}
.col-xs-7 {
  width: 58.33333333%;
}
.col-xs-6 {
  width: 50%;
}
.col-xs-5 {
  width: 41.66666667%;
}
.col-xs-4 {
  width: 33.33333333%;
}
.col-xs-3 {
  width: 25%;
}
.col-xs-2 {
  width: 16.66666667%;
}
.col-xs-1 {
  width: 8.33333333%;
}
.col-xs-pull-12 {
  right: 100%;
}
.col-xs-pull-11 {
  right: 91.66666667%;
}
.col-xs-pull-10 {
  right: 83.33333333%;
}
.col-xs-pull-9 {
  right: 75%;
}
.col-xs-pull-8 {
  right: 66.66666667%;
}
.col-xs-pull-7 {
  right: 58.33333333%;
}
.col-xs-pull-6 {
  right: 50%;
}
.col-xs-pull-5 {
  right: 41.66666667%;
}
.col-xs-pull-4 {
  right: 33.33333333%;
}
.col-xs-pull-3 {
  right: 25%;
}
.col-xs-pull-2 {
  right: 16.66666667%;
}
.col-xs-pull-1 {
  right: 8.33333333%;
}
.col-xs-pull-0 {
  right: auto;
}
.col-xs-push-12 {
  left: 100%;
}
.col-xs-push-11 {
  left: 91.66666667%;
}
.col-xs-push-10 {
  left: 83.33333333%;
}
.col-xs-push-9 {
  left: 75%;
}
.col-xs-push-8 {
  left: 66.66666667%;
}
.col-xs-push-7 {
  left: 58.33333333%;
}
.col-xs-push-6 {
  left: 50%;
}
.col-xs-push-5 {
  left: 41.66666667%;
}
.col-xs-push-4 {
  left: 33.33333333%;
}
.col-xs-push-3 {
  left: 25%;
}
.col-xs-push-2 {
  left: 16.66666667%;
}
.col-xs-push-1 {
  left: 8.33333333%;
}
.col-xs-push-0 {
  left: auto;
}
.col-xs-offset-12 {
  margin-left: 100%;
}
.col-xs-offset-11 {
  margin-left: 91.66666667%;
}
.col-xs-offset-10 {
  margin-left: 83.33333333%;
}
.col-xs-offset-9 {
  margin-left: 75%;
}
.col-xs-offset-8 {
  margin-left: 66.66666667%;
}
.col-xs-offset-7 {
  margin-left: 58.33333333%;
}
.col-xs-offset-6 {
  margin-left: 50%;
}
.col-xs-offset-5 {
  margin-left: 41.66666667%;
}
.col-xs-offset-4 {
  margin-left: 33.33333333%;
}
.col-xs-offset-3 {
  margin-left: 25%;
}
.col-xs-offset-2 {
  margin-left: 16.66666667%;
}
.col-xs-offset-1 {
  margin-left: 8.33333333%;
}
.col-xs-offset-0 {
  margin-left: 0%;
}
@media (min-width: 768px) {
  .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
    float: left;
  }
  .col-sm-12 {
    width: 100%;
  }
  .col-sm-11 {
    width: 91.66666667%;
  }
  .col-sm-10 {
    width: 83.33333333%;
  }
  .col-sm-9 {
    width: 75%;
  }
  .col-sm-8 {
    width: 66.66666667%;
  }
  .col-sm-7 {
    width: 58.33333333%;
  }
  .col-sm-6 {
    width: 50%;
  }
  .col-sm-5 {
    width: 41.66666667%;
  }
  .col-sm-4 {
    width: 33.33333333%;
  }
  .col-sm-3 {
    width: 25%;
  }
  .col-sm-2 {
    width: 16.66666667%;
  }
  .col-sm-1 {
    width: 8.33333333%;
  }
  .col-sm-pull-12 {
    right: 100%;
  }
  .col-sm-pull-11 {
    right: 91.66666667%;
  }
  .col-sm-pull-10 {
    right: 83.33333333%;
  }
  .col-sm-pull-9 {
    right: 75%;
  }
  .col-sm-pull-8 {
    right: 66.66666667%;
  }
  .col-sm-pull-7 {
    right: 58.33333333%;
  }
  .col-sm-pull-6 {
    right: 50%;
  }
  .col-sm-pull-5 {
    right: 41.66666667%;
  }
  .col-sm-pull-4 {
    right: 33.33333333%;
  }
  .col-sm-pull-3 {
    right: 25%;
  }
  .col-sm-pull-2 {
    right: 16.66666667%;
  }
  .col-sm-pull-1 {
    right: 8.33333333%;
  }
  .col-sm-pull-0 {
    right: auto;
  }
  .col-sm-push-12 {
    left: 100%;
  }
  .col-sm-push-11 {
    left: 91.66666667%;
  }
  .col-sm-push-10 {
    left: 83.33333333%;
  }
  .col-sm-push-9 {
    left: 75%;
  }
  .col-sm-push-8 {
    left: 66.66666667%;
  }
  .col-sm-push-7 {
    left: 58.33333333%;
  }
  .col-sm-push-6 {
    left: 50%;
  }
  .col-sm-push-5 {
    left: 41.66666667%;
  }
  .col-sm-push-4 {
    left: 33.33333333%;
  }
  .col-sm-push-3 {
    left: 25%;
  }
  .col-sm-push-2 {
    left: 16.66666667%;
  }
  .col-sm-push-1 {
    left: 8.33333333%;
  }
  .col-sm-push-0 {
    left: auto;
  }
  .col-sm-offset-12 {
    margin-left: 100%;
  }
  .col-sm-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-sm-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-sm-offset-9 {
    margin-left: 75%;
  }
  .col-sm-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-sm-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-sm-offset-6 {
    margin-left: 50%;
  }
  .col-sm-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-sm-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-sm-offset-3 {
    margin-left: 25%;
  }
  .col-sm-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-sm-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-sm-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 992px) {
  .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
    float: left;
  }
  .col-md-12 {
    width: 100%;
  }
  .col-md-11 {
    width: 91.66666667%;
  }
  .col-md-10 {
    width: 83.33333333%;
  }
  .col-md-9 {
    width: 75%;
  }
  .col-md-8 {
    width: 66.66666667%;
  }
  .col-md-7 {
    width: 58.33333333%;
  }
  .col-md-6 {
    width: 50%;
  }
  .col-md-5 {
    width: 41.66666667%;
  }
  .col-md-4 {
    width: 33.33333333%;
  }
  .col-md-3 {
    width: 25%;
  }
  .col-md-2 {
    width: 16.66666667%;
  }
  .col-md-1 {
    width: 8.33333333%;
  }
  .col-md-pull-12 {
    right: 100%;
  }
  .col-md-pull-11 {
    right: 91.66666667%;
  }
  .col-md-pull-10 {
    right: 83.33333333%;
  }
  .col-md-pull-9 {
    right: 75%;
  }
  .col-md-pull-8 {
    right: 66.66666667%;
  }
  .col-md-pull-7 {
    right: 58.33333333%;
  }
  .col-md-pull-6 {
    right: 50%;
  }
  .col-md-pull-5 {
    right: 41.66666667%;
  }
  .col-md-pull-4 {
    right: 33.33333333%;
  }
  .col-md-pull-3 {
    right: 25%;
  }
  .col-md-pull-2 {
    right: 16.66666667%;
  }
  .col-md-pull-1 {
    right: 8.33333333%;
  }
  .col-md-pull-0 {
    right: auto;
  }
  .col-md-push-12 {
    left: 100%;
  }
  .col-md-push-11 {
    left: 91.66666667%;
  }
  .col-md-push-10 {
    left: 83.33333333%;
  }
  .col-md-push-9 {
    left: 75%;
  }
  .col-md-push-8 {
    left: 66.66666667%;
  }
  .col-md-push-7 {
    left: 58.33333333%;
  }
  .col-md-push-6 {
    left: 50%;
  }
  .col-md-push-5 {
    left: 41.66666667%;
  }
  .col-md-push-4 {
    left: 33.33333333%;
  }
  .col-md-push-3 {
    left: 25%;
  }
  .col-md-push-2 {
    left: 16.66666667%;
  }
  .col-md-push-1 {
    left: 8.33333333%;
  }
  .col-md-push-0 {
    left: auto;
  }
  .col-md-offset-12 {
    margin-left: 100%;
  }
  .col-md-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-md-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-md-offset-9 {
    margin-left: 75%;
  }
  .col-md-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-md-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-md-offset-6 {
    margin-left: 50%;
  }
  .col-md-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-md-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-md-offset-3 {
    margin-left: 25%;
  }
  .col-md-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-md-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-md-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 1200px) {
  .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
    float: left;
  }
  .col-lg-12 {
    width: 100%;
  }
  .col-lg-11 {
    width: 91.66666667%;
  }
  .col-lg-10 {
    width: 83.33333333%;
  }
  .col-lg-9 {
    width: 75%;
  }
  .col-lg-8 {
    width: 66.66666667%;
  }
  .col-lg-7 {
    width: 58.33333333%;
  }
  .col-lg-6 {
    width: 50%;
  }
  .col-lg-5 {
    width: 41.66666667%;
  }
  .col-lg-4 {
    width: 33.33333333%;
  }
  .col-lg-3 {
    width: 25%;
  }
  .col-lg-2 {
    width: 16.66666667%;
  }
  .col-lg-1 {
    width: 8.33333333%;
  }
  .col-lg-pull-12 {
    right: 100%;
  }
  .col-lg-pull-11 {
    right: 91.66666667%;
  }
  .col-lg-pull-10 {
    right: 83.33333333%;
  }
  .col-lg-pull-9 {
    right: 75%;
  }
  .col-lg-pull-8 {
    right: 66.66666667%;
  }
  .col-lg-pull-7 {
    right: 58.33333333%;
  }
  .col-lg-pull-6 {
    right: 50%;
  }
  .col-lg-pull-5 {
    right: 41.66666667%;
  }
  .col-lg-pull-4 {
    right: 33.33333333%;
  }
  .col-lg-pull-3 {
    right: 25%;
  }
  .col-lg-pull-2 {
    right: 16.66666667%;
  }
  .col-lg-pull-1 {
    right: 8.33333333%;
  }
  .col-lg-pull-0 {
    right: auto;
  }
  .col-lg-push-12 {
    left: 100%;
  }
  .col-lg-push-11 {
    left: 91.66666667%;
  }
  .col-lg-push-10 {
    left: 83.33333333%;
  }
  .col-lg-push-9 {
    left: 75%;
  }
  .col-lg-push-8 {
    left: 66.66666667%;
  }
  .col-lg-push-7 {
    left: 58.33333333%;
  }
  .col-lg-push-6 {
    left: 50%;
  }
  .col-lg-push-5 {
    left: 41.66666667%;
  }
  .col-lg-push-4 {
    left: 33.33333333%;
  }
  .col-lg-push-3 {
    left: 25%;
  }
  .col-lg-push-2 {
    left: 16.66666667%;
  }
  .col-lg-push-1 {
    left: 8.33333333%;
  }
  .col-lg-push-0 {
    left: auto;
  }
  .col-lg-offset-12 {
    margin-left: 100%;
  }
  .col-lg-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-lg-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-lg-offset-9 {
    margin-left: 75%;
  }
  .col-lg-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-lg-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-lg-offset-6 {
    margin-left: 50%;
  }
  .col-lg-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-lg-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-lg-offset-3 {
    margin-left: 25%;
  }
  .col-lg-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-lg-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-lg-offset-0 {
    margin-left: 0%;
  }
}
table {
  background-color: transparent;
}
caption {
  padding-top: 8px;
  padding-bottom: 8px;
  color: #777777;
  text-align: left;
}
th {
  text-align: left;
}
.table {
  width: 100%;
  max-width: 100%;
  margin-bottom: 18px;
}
.table > thead > tr > th,
.table > tbody > tr > th,
.table > tfoot > tr > th,
.table > thead > tr > td,
.table > tbody > tr > td,
.table > tfoot > tr > td {
  padding: 8px;
  line-height: 1.42857143;
  vertical-align: top;
  border-top: 1px solid #ddd;
}
.table > thead > tr > th {
  vertical-align: bottom;
  border-bottom: 2px solid #ddd;
}
.table > caption + thead > tr:first-child > th,
.table > colgroup + thead > tr:first-child > th,
.table > thead:first-child > tr:first-child > th,
.table > caption + thead > tr:first-child > td,
.table > colgroup + thead > tr:first-child > td,
.table > thead:first-child > tr:first-child > td {
  border-top: 0;
}
.table > tbody + tbody {
  border-top: 2px solid #ddd;
}
.table .table {
  background-color: #fff;
}
.table-condensed > thead > tr > th,
.table-condensed > tbody > tr > th,
.table-condensed > tfoot > tr > th,
.table-condensed > thead > tr > td,
.table-condensed > tbody > tr > td,
.table-condensed > tfoot > tr > td {
  padding: 5px;
}
.table-bordered {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > tbody > tr > th,
.table-bordered > tfoot > tr > th,
.table-bordered > thead > tr > td,
.table-bordered > tbody > tr > td,
.table-bordered > tfoot > tr > td {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > thead > tr > td {
  border-bottom-width: 2px;
}
.table-striped > tbody > tr:nth-of-type(odd) {
  background-color: #f9f9f9;
}
.table-hover > tbody > tr:hover {
  background-color: #f5f5f5;
}
table col[class*="col-"] {
  position: static;
  float: none;
  display: table-column;
}
table td[class*="col-"],
table th[class*="col-"] {
  position: static;
  float: none;
  display: table-cell;
}
.table > thead > tr > td.active,
.table > tbody > tr > td.active,
.table > tfoot > tr > td.active,
.table > thead > tr > th.active,
.table > tbody > tr > th.active,
.table > tfoot > tr > th.active,
.table > thead > tr.active > td,
.table > tbody > tr.active > td,
.table > tfoot > tr.active > td,
.table > thead > tr.active > th,
.table > tbody > tr.active > th,
.table > tfoot > tr.active > th {
  background-color: #f5f5f5;
}
.table-hover > tbody > tr > td.active:hover,
.table-hover > tbody > tr > th.active:hover,
.table-hover > tbody > tr.active:hover > td,
.table-hover > tbody > tr:hover > .active,
.table-hover > tbody > tr.active:hover > th {
  background-color: #e8e8e8;
}
.table > thead > tr > td.success,
.table > tbody > tr > td.success,
.table > tfoot > tr > td.success,
.table > thead > tr > th.success,
.table > tbody > tr > th.success,
.table > tfoot > tr > th.success,
.table > thead > tr.success > td,
.table > tbody > tr.success > td,
.table > tfoot > tr.success > td,
.table > thead > tr.success > th,
.table > tbody > tr.success > th,
.table > tfoot > tr.success > th {
  background-color: #dff0d8;
}
.table-hover > tbody > tr > td.success:hover,
.table-hover > tbody > tr > th.success:hover,
.table-hover > tbody > tr.success:hover > td,
.table-hover > tbody > tr:hover > .success,
.table-hover > tbody > tr.success:hover > th {
  background-color: #d0e9c6;
}
.table > thead > tr > td.info,
.table > tbody > tr > td.info,
.table > tfoot > tr > td.info,
.table > thead > tr > th.info,
.table > tbody > tr > th.info,
.table > tfoot > tr > th.info,
.table > thead > tr.info > td,
.table > tbody > tr.info > td,
.table > tfoot > tr.info > td,
.table > thead > tr.info > th,
.table > tbody > tr.info > th,
.table > tfoot > tr.info > th {
  background-color: #d9edf7;
}
.table-hover > tbody > tr > td.info:hover,
.table-hover > tbody > tr > th.info:hover,
.table-hover > tbody > tr.info:hover > td,
.table-hover > tbody > tr:hover > .info,
.table-hover > tbody > tr.info:hover > th {
  background-color: #c4e3f3;
}
.table > thead > tr > td.warning,
.table > tbody > tr > td.warning,
.table > tfoot > tr > td.warning,
.table > thead > tr > th.warning,
.table > tbody > tr > th.warning,
.table > tfoot > tr > th.warning,
.table > thead > tr.warning > td,
.table > tbody > tr.warning > td,
.table > tfoot > tr.warning > td,
.table > thead > tr.warning > th,
.table > tbody > tr.warning > th,
.table > tfoot > tr.warning > th {
  background-color: #fcf8e3;
}
.table-hover > tbody > tr > td.warning:hover,
.table-hover > tbody > tr > th.warning:hover,
.table-hover > tbody > tr.warning:hover > td,
.table-hover > tbody > tr:hover > .warning,
.table-hover > tbody > tr.warning:hover > th {
  background-color: #faf2cc;
}
.table > thead > tr > td.danger,
.table > tbody > tr > td.danger,
.table > tfoot > tr > td.danger,
.table > thead > tr > th.danger,
.table > tbody > tr > th.danger,
.table > tfoot > tr > th.danger,
.table > thead > tr.danger > td,
.table > tbody > tr.danger > td,
.table > tfoot > tr.danger > td,
.table > thead > tr.danger > th,
.table > tbody > tr.danger > th,
.table > tfoot > tr.danger > th {
  background-color: #f2dede;
}
.table-hover > tbody > tr > td.danger:hover,
.table-hover > tbody > tr > th.danger:hover,
.table-hover > tbody > tr.danger:hover > td,
.table-hover > tbody > tr:hover > .danger,
.table-hover > tbody > tr.danger:hover > th {
  background-color: #ebcccc;
}
.table-responsive {
  overflow-x: auto;
  min-height: 0.01%;
}
@media screen and (max-width: 767px) {
  .table-responsive {
    width: 100%;
    margin-bottom: 13.5px;
    overflow-y: hidden;
    -ms-overflow-style: -ms-autohiding-scrollbar;
    border: 1px solid #ddd;
  }
  .table-responsive > .table {
    margin-bottom: 0;
  }
  .table-responsive > .table > thead > tr > th,
  .table-responsive > .table > tbody > tr > th,
  .table-responsive > .table > tfoot > tr > th,
  .table-responsive > .table > thead > tr > td,
  .table-responsive > .table > tbody > tr > td,
  .table-responsive > .table > tfoot > tr > td {
    white-space: nowrap;
  }
  .table-responsive > .table-bordered {
    border: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:first-child,
  .table-responsive > .table-bordered > tbody > tr > th:first-child,
  .table-responsive > .table-bordered > tfoot > tr > th:first-child,
  .table-responsive > .table-bordered > thead > tr > td:first-child,
  .table-responsive > .table-bordered > tbody > tr > td:first-child,
  .table-responsive > .table-bordered > tfoot > tr > td:first-child {
    border-left: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:last-child,
  .table-responsive > .table-bordered > tbody > tr > th:last-child,
  .table-responsive > .table-bordered > tfoot > tr > th:last-child,
  .table-responsive > .table-bordered > thead > tr > td:last-child,
  .table-responsive > .table-bordered > tbody > tr > td:last-child,
  .table-responsive > .table-bordered > tfoot > tr > td:last-child {
    border-right: 0;
  }
  .table-responsive > .table-bordered > tbody > tr:last-child > th,
  .table-responsive > .table-bordered > tfoot > tr:last-child > th,
  .table-responsive > .table-bordered > tbody > tr:last-child > td,
  .table-responsive > .table-bordered > tfoot > tr:last-child > td {
    border-bottom: 0;
  }
}
fieldset {
  padding: 0;
  margin: 0;
  border: 0;
  min-width: 0;
}
legend {
  display: block;
  width: 100%;
  padding: 0;
  margin-bottom: 18px;
  font-size: 19.5px;
  line-height: inherit;
  color: #333333;
  border: 0;
  border-bottom: 1px solid #e5e5e5;
}
label {
  display: inline-block;
  max-width: 100%;
  margin-bottom: 5px;
  font-weight: bold;
}
input[type="search"] {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
input[type="radio"],
input[type="checkbox"] {
  margin: 4px 0 0;
  margin-top: 1px \9;
  line-height: normal;
}
input[type="file"] {
  display: block;
}
input[type="range"] {
  display: block;
  width: 100%;
}
select[multiple],
select[size] {
  height: auto;
}
input[type="file"]:focus,
input[type="radio"]:focus,
input[type="checkbox"]:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
output {
  display: block;
  padding-top: 7px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
}
.form-control {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
}
.form-control:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.form-control::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.form-control:-ms-input-placeholder {
  color: #999;
}
.form-control::-webkit-input-placeholder {
  color: #999;
}
.form-control::-ms-expand {
  border: 0;
  background-color: transparent;
}
.form-control[disabled],
.form-control[readonly],
fieldset[disabled] .form-control {
  background-color: #eeeeee;
  opacity: 1;
}
.form-control[disabled],
fieldset[disabled] .form-control {
  cursor: not-allowed;
}
textarea.form-control {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: none;
}
@media screen and (-webkit-min-device-pixel-ratio: 0) {
  input[type="date"].form-control,
  input[type="time"].form-control,
  input[type="datetime-local"].form-control,
  input[type="month"].form-control {
    line-height: 32px;
  }
  input[type="date"].input-sm,
  input[type="time"].input-sm,
  input[type="datetime-local"].input-sm,
  input[type="month"].input-sm,
  .input-group-sm input[type="date"],
  .input-group-sm input[type="time"],
  .input-group-sm input[type="datetime-local"],
  .input-group-sm input[type="month"] {
    line-height: 30px;
  }
  input[type="date"].input-lg,
  input[type="time"].input-lg,
  input[type="datetime-local"].input-lg,
  input[type="month"].input-lg,
  .input-group-lg input[type="date"],
  .input-group-lg input[type="time"],
  .input-group-lg input[type="datetime-local"],
  .input-group-lg input[type="month"] {
    line-height: 45px;
  }
}
.form-group {
  margin-bottom: 15px;
}
.radio,
.checkbox {
  position: relative;
  display: block;
  margin-top: 10px;
  margin-bottom: 10px;
}
.radio label,
.checkbox label {
  min-height: 18px;
  padding-left: 20px;
  margin-bottom: 0;
  font-weight: normal;
  cursor: pointer;
}
.radio input[type="radio"],
.radio-inline input[type="radio"],
.checkbox input[type="checkbox"],
.checkbox-inline input[type="checkbox"] {
  position: absolute;
  margin-left: -20px;
  margin-top: 4px \9;
}
.radio + .radio,
.checkbox + .checkbox {
  margin-top: -5px;
}
.radio-inline,
.checkbox-inline {
  position: relative;
  display: inline-block;
  padding-left: 20px;
  margin-bottom: 0;
  vertical-align: middle;
  font-weight: normal;
  cursor: pointer;
}
.radio-inline + .radio-inline,
.checkbox-inline + .checkbox-inline {
  margin-top: 0;
  margin-left: 10px;
}
input[type="radio"][disabled],
input[type="checkbox"][disabled],
input[type="radio"].disabled,
input[type="checkbox"].disabled,
fieldset[disabled] input[type="radio"],
fieldset[disabled] input[type="checkbox"] {
  cursor: not-allowed;
}
.radio-inline.disabled,
.checkbox-inline.disabled,
fieldset[disabled] .radio-inline,
fieldset[disabled] .checkbox-inline {
  cursor: not-allowed;
}
.radio.disabled label,
.checkbox.disabled label,
fieldset[disabled] .radio label,
fieldset[disabled] .checkbox label {
  cursor: not-allowed;
}
.form-control-static {
  padding-top: 7px;
  padding-bottom: 7px;
  margin-bottom: 0;
  min-height: 31px;
}
.form-control-static.input-lg,
.form-control-static.input-sm {
  padding-left: 0;
  padding-right: 0;
}
.input-sm {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-sm {
  height: 30px;
  line-height: 30px;
}
textarea.input-sm,
select[multiple].input-sm {
  height: auto;
}
.form-group-sm .form-control {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.form-group-sm select.form-control {
  height: 30px;
  line-height: 30px;
}
.form-group-sm textarea.form-control,
.form-group-sm select[multiple].form-control {
  height: auto;
}
.form-group-sm .form-control-static {
  height: 30px;
  min-height: 30px;
  padding: 6px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.input-lg {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-lg {
  height: 45px;
  line-height: 45px;
}
textarea.input-lg,
select[multiple].input-lg {
  height: auto;
}
.form-group-lg .form-control {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.form-group-lg select.form-control {
  height: 45px;
  line-height: 45px;
}
.form-group-lg textarea.form-control,
.form-group-lg select[multiple].form-control {
  height: auto;
}
.form-group-lg .form-control-static {
  height: 45px;
  min-height: 35px;
  padding: 11px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.has-feedback {
  position: relative;
}
.has-feedback .form-control {
  padding-right: 40px;
}
.form-control-feedback {
  position: absolute;
  top: 0;
  right: 0;
  z-index: 2;
  display: block;
  width: 32px;
  height: 32px;
  line-height: 32px;
  text-align: center;
  pointer-events: none;
}
.input-lg + .form-control-feedback,
.input-group-lg + .form-control-feedback,
.form-group-lg .form-control + .form-control-feedback {
  width: 45px;
  height: 45px;
  line-height: 45px;
}
.input-sm + .form-control-feedback,
.input-group-sm + .form-control-feedback,
.form-group-sm .form-control + .form-control-feedback {
  width: 30px;
  height: 30px;
  line-height: 30px;
}
.has-success .help-block,
.has-success .control-label,
.has-success .radio,
.has-success .checkbox,
.has-success .radio-inline,
.has-success .checkbox-inline,
.has-success.radio label,
.has-success.checkbox label,
.has-success.radio-inline label,
.has-success.checkbox-inline label {
  color: #3c763d;
}
.has-success .form-control {
  border-color: #3c763d;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-success .form-control:focus {
  border-color: #2b542c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
}
.has-success .input-group-addon {
  color: #3c763d;
  border-color: #3c763d;
  background-color: #dff0d8;
}
.has-success .form-control-feedback {
  color: #3c763d;
}
.has-warning .help-block,
.has-warning .control-label,
.has-warning .radio,
.has-warning .checkbox,
.has-warning .radio-inline,
.has-warning .checkbox-inline,
.has-warning.radio label,
.has-warning.checkbox label,
.has-warning.radio-inline label,
.has-warning.checkbox-inline label {
  color: #8a6d3b;
}
.has-warning .form-control {
  border-color: #8a6d3b;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-warning .form-control:focus {
  border-color: #66512c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
}
.has-warning .input-group-addon {
  color: #8a6d3b;
  border-color: #8a6d3b;
  background-color: #fcf8e3;
}
.has-warning .form-control-feedback {
  color: #8a6d3b;
}
.has-error .help-block,
.has-error .control-label,
.has-error .radio,
.has-error .checkbox,
.has-error .radio-inline,
.has-error .checkbox-inline,
.has-error.radio label,
.has-error.checkbox label,
.has-error.radio-inline label,
.has-error.checkbox-inline label {
  color: #a94442;
}
.has-error .form-control {
  border-color: #a94442;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-error .form-control:focus {
  border-color: #843534;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
}
.has-error .input-group-addon {
  color: #a94442;
  border-color: #a94442;
  background-color: #f2dede;
}
.has-error .form-control-feedback {
  color: #a94442;
}
.has-feedback label ~ .form-control-feedback {
  top: 23px;
}
.has-feedback label.sr-only ~ .form-control-feedback {
  top: 0;
}
.help-block {
  display: block;
  margin-top: 5px;
  margin-bottom: 10px;
  color: #404040;
}
@media (min-width: 768px) {
  .form-inline .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .form-inline .form-control-static {
    display: inline-block;
  }
  .form-inline .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .form-inline .input-group .input-group-addon,
  .form-inline .input-group .input-group-btn,
  .form-inline .input-group .form-control {
    width: auto;
  }
  .form-inline .input-group > .form-control {
    width: 100%;
  }
  .form-inline .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio,
  .form-inline .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio label,
  .form-inline .checkbox label {
    padding-left: 0;
  }
  .form-inline .radio input[type="radio"],
  .form-inline .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .form-inline .has-feedback .form-control-feedback {
    top: 0;
  }
}
.form-horizontal .radio,
.form-horizontal .checkbox,
.form-horizontal .radio-inline,
.form-horizontal .checkbox-inline {
  margin-top: 0;
  margin-bottom: 0;
  padding-top: 7px;
}
.form-horizontal .radio,
.form-horizontal .checkbox {
  min-height: 25px;
}
.form-horizontal .form-group {
  margin-left: 0px;
  margin-right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .control-label {
    text-align: right;
    margin-bottom: 0;
    padding-top: 7px;
  }
}
.form-horizontal .has-feedback .form-control-feedback {
  right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .form-group-lg .control-label {
    padding-top: 11px;
    font-size: 17px;
  }
}
@media (min-width: 768px) {
  .form-horizontal .form-group-sm .control-label {
    padding-top: 6px;
    font-size: 12px;
  }
}
.btn {
  display: inline-block;
  margin-bottom: 0;
  font-weight: normal;
  text-align: center;
  vertical-align: middle;
  touch-action: manipulation;
  cursor: pointer;
  background-image: none;
  border: 1px solid transparent;
  white-space: nowrap;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  border-radius: 2px;
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}
.btn:focus,
.btn:active:focus,
.btn.active:focus,
.btn.focus,
.btn:active.focus,
.btn.active.focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
.btn:hover,
.btn:focus,
.btn.focus {
  color: #333;
  text-decoration: none;
}
.btn:active,
.btn.active {
  outline: 0;
  background-image: none;
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn.disabled,
.btn[disabled],
fieldset[disabled] .btn {
  cursor: not-allowed;
  opacity: 0.65;
  filter: alpha(opacity=65);
  -webkit-box-shadow: none;
  box-shadow: none;
}
a.btn.disabled,
fieldset[disabled] a.btn {
  pointer-events: none;
}
.btn-default {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.btn-default:focus,
.btn-default.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.btn-default:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active:hover,
.btn-default.active:hover,
.open > .dropdown-toggle.btn-default:hover,
.btn-default:active:focus,
.btn-default.active:focus,
.open > .dropdown-toggle.btn-default:focus,
.btn-default:active.focus,
.btn-default.active.focus,
.open > .dropdown-toggle.btn-default.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  background-image: none;
}
.btn-default.disabled:hover,
.btn-default[disabled]:hover,
fieldset[disabled] .btn-default:hover,
.btn-default.disabled:focus,
.btn-default[disabled]:focus,
fieldset[disabled] .btn-default:focus,
.btn-default.disabled.focus,
.btn-default[disabled].focus,
fieldset[disabled] .btn-default.focus {
  background-color: #fff;
  border-color: #ccc;
}
.btn-default .badge {
  color: #fff;
  background-color: #333;
}
.btn-primary {
  color: #fff;
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary:focus,
.btn-primary.focus {
  color: #fff;
  background-color: #286090;
  border-color: #122b40;
}
.btn-primary:hover {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active:hover,
.btn-primary.active:hover,
.open > .dropdown-toggle.btn-primary:hover,
.btn-primary:active:focus,
.btn-primary.active:focus,
.open > .dropdown-toggle.btn-primary:focus,
.btn-primary:active.focus,
.btn-primary.active.focus,
.open > .dropdown-toggle.btn-primary.focus {
  color: #fff;
  background-color: #204d74;
  border-color: #122b40;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  background-image: none;
}
.btn-primary.disabled:hover,
.btn-primary[disabled]:hover,
fieldset[disabled] .btn-primary:hover,
.btn-primary.disabled:focus,
.btn-primary[disabled]:focus,
fieldset[disabled] .btn-primary:focus,
.btn-primary.disabled.focus,
.btn-primary[disabled].focus,
fieldset[disabled] .btn-primary.focus {
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary .badge {
  color: #337ab7;
  background-color: #fff;
}
.btn-success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success:focus,
.btn-success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.btn-success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active:hover,
.btn-success.active:hover,
.open > .dropdown-toggle.btn-success:hover,
.btn-success:active:focus,
.btn-success.active:focus,
.open > .dropdown-toggle.btn-success:focus,
.btn-success:active.focus,
.btn-success.active.focus,
.open > .dropdown-toggle.btn-success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  background-image: none;
}
.btn-success.disabled:hover,
.btn-success[disabled]:hover,
fieldset[disabled] .btn-success:hover,
.btn-success.disabled:focus,
.btn-success[disabled]:focus,
fieldset[disabled] .btn-success:focus,
.btn-success.disabled.focus,
.btn-success[disabled].focus,
fieldset[disabled] .btn-success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.btn-info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info:focus,
.btn-info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.btn-info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active:hover,
.btn-info.active:hover,
.open > .dropdown-toggle.btn-info:hover,
.btn-info:active:focus,
.btn-info.active:focus,
.open > .dropdown-toggle.btn-info:focus,
.btn-info:active.focus,
.btn-info.active.focus,
.open > .dropdown-toggle.btn-info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  background-image: none;
}
.btn-info.disabled:hover,
.btn-info[disabled]:hover,
fieldset[disabled] .btn-info:hover,
.btn-info.disabled:focus,
.btn-info[disabled]:focus,
fieldset[disabled] .btn-info:focus,
.btn-info.disabled.focus,
.btn-info[disabled].focus,
fieldset[disabled] .btn-info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.btn-warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning:focus,
.btn-warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.btn-warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active:hover,
.btn-warning.active:hover,
.open > .dropdown-toggle.btn-warning:hover,
.btn-warning:active:focus,
.btn-warning.active:focus,
.open > .dropdown-toggle.btn-warning:focus,
.btn-warning:active.focus,
.btn-warning.active.focus,
.open > .dropdown-toggle.btn-warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  background-image: none;
}
.btn-warning.disabled:hover,
.btn-warning[disabled]:hover,
fieldset[disabled] .btn-warning:hover,
.btn-warning.disabled:focus,
.btn-warning[disabled]:focus,
fieldset[disabled] .btn-warning:focus,
.btn-warning.disabled.focus,
.btn-warning[disabled].focus,
fieldset[disabled] .btn-warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.btn-danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger:focus,
.btn-danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.btn-danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active:hover,
.btn-danger.active:hover,
.open > .dropdown-toggle.btn-danger:hover,
.btn-danger:active:focus,
.btn-danger.active:focus,
.open > .dropdown-toggle.btn-danger:focus,
.btn-danger:active.focus,
.btn-danger.active.focus,
.open > .dropdown-toggle.btn-danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  background-image: none;
}
.btn-danger.disabled:hover,
.btn-danger[disabled]:hover,
fieldset[disabled] .btn-danger:hover,
.btn-danger.disabled:focus,
.btn-danger[disabled]:focus,
fieldset[disabled] .btn-danger:focus,
.btn-danger.disabled.focus,
.btn-danger[disabled].focus,
fieldset[disabled] .btn-danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger .badge {
  color: #d9534f;
  background-color: #fff;
}
.btn-link {
  color: #337ab7;
  font-weight: normal;
  border-radius: 0;
}
.btn-link,
.btn-link:active,
.btn-link.active,
.btn-link[disabled],
fieldset[disabled] .btn-link {
  background-color: transparent;
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn-link,
.btn-link:hover,
.btn-link:focus,
.btn-link:active {
  border-color: transparent;
}
.btn-link:hover,
.btn-link:focus {
  color: #23527c;
  text-decoration: underline;
  background-color: transparent;
}
.btn-link[disabled]:hover,
fieldset[disabled] .btn-link:hover,
.btn-link[disabled]:focus,
fieldset[disabled] .btn-link:focus {
  color: #777777;
  text-decoration: none;
}
.btn-lg,
.btn-group-lg > .btn {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.btn-sm,
.btn-group-sm > .btn {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-xs,
.btn-group-xs > .btn {
  padding: 1px 5px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-block {
  display: block;
  width: 100%;
}
.btn-block + .btn-block {
  margin-top: 5px;
}
input[type="submit"].btn-block,
input[type="reset"].btn-block,
input[type="button"].btn-block {
  width: 100%;
}
.fade {
  opacity: 0;
  -webkit-transition: opacity 0.15s linear;
  -o-transition: opacity 0.15s linear;
  transition: opacity 0.15s linear;
}
.fade.in {
  opacity: 1;
}
.collapse {
  display: none;
}
.collapse.in {
  display: block;
}
tr.collapse.in {
  display: table-row;
}
tbody.collapse.in {
  display: table-row-group;
}
.collapsing {
  position: relative;
  height: 0;
  overflow: hidden;
  -webkit-transition-property: height, visibility;
  transition-property: height, visibility;
  -webkit-transition-duration: 0.35s;
  transition-duration: 0.35s;
  -webkit-transition-timing-function: ease;
  transition-timing-function: ease;
}
.caret {
  display: inline-block;
  width: 0;
  height: 0;
  margin-left: 2px;
  vertical-align: middle;
  border-top: 4px dashed;
  border-top: 4px solid \9;
  border-right: 4px solid transparent;
  border-left: 4px solid transparent;
}
.dropup,
.dropdown {
  position: relative;
}
.dropdown-toggle:focus {
  outline: 0;
}
.dropdown-menu {
  position: absolute;
  top: 100%;
  left: 0;
  z-index: 1000;
  display: none;
  float: left;
  min-width: 160px;
  padding: 5px 0;
  margin: 2px 0 0;
  list-style: none;
  font-size: 13px;
  text-align: left;
  background-color: #fff;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.15);
  border-radius: 2px;
  -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  background-clip: padding-box;
}
.dropdown-menu.pull-right {
  right: 0;
  left: auto;
}
.dropdown-menu .divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.dropdown-menu > li > a {
  display: block;
  padding: 3px 20px;
  clear: both;
  font-weight: normal;
  line-height: 1.42857143;
  color: #333333;
  white-space: nowrap;
}
.dropdown-menu > li > a:hover,
.dropdown-menu > li > a:focus {
  text-decoration: none;
  color: #262626;
  background-color: #f5f5f5;
}
.dropdown-menu > .active > a,
.dropdown-menu > .active > a:hover,
.dropdown-menu > .active > a:focus {
  color: #fff;
  text-decoration: none;
  outline: 0;
  background-color: #337ab7;
}
.dropdown-menu > .disabled > a,
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  color: #777777;
}
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  text-decoration: none;
  background-color: transparent;
  background-image: none;
  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
  cursor: not-allowed;
}
.open > .dropdown-menu {
  display: block;
}
.open > a {
  outline: 0;
}
.dropdown-menu-right {
  left: auto;
  right: 0;
}
.dropdown-menu-left {
  left: 0;
  right: auto;
}
.dropdown-header {
  display: block;
  padding: 3px 20px;
  font-size: 12px;
  line-height: 1.42857143;
  color: #777777;
  white-space: nowrap;
}
.dropdown-backdrop {
  position: fixed;
  left: 0;
  right: 0;
  bottom: 0;
  top: 0;
  z-index: 990;
}
.pull-right > .dropdown-menu {
  right: 0;
  left: auto;
}
.dropup .caret,
.navbar-fixed-bottom .dropdown .caret {
  border-top: 0;
  border-bottom: 4px dashed;
  border-bottom: 4px solid \9;
  content: "";
}
.dropup .dropdown-menu,
.navbar-fixed-bottom .dropdown .dropdown-menu {
  top: auto;
  bottom: 100%;
  margin-bottom: 2px;
}
@media (min-width: 541px) {
  .navbar-right .dropdown-menu {
    left: auto;
    right: 0;
  }
  .navbar-right .dropdown-menu-left {
    left: 0;
    right: auto;
  }
}
.btn-group,
.btn-group-vertical {
  position: relative;
  display: inline-block;
  vertical-align: middle;
}
.btn-group > .btn,
.btn-group-vertical > .btn {
  position: relative;
  float: left;
}
.btn-group > .btn:hover,
.btn-group-vertical > .btn:hover,
.btn-group > .btn:focus,
.btn-group-vertical > .btn:focus,
.btn-group > .btn:active,
.btn-group-vertical > .btn:active,
.btn-group > .btn.active,
.btn-group-vertical > .btn.active {
  z-index: 2;
}
.btn-group .btn + .btn,
.btn-group .btn + .btn-group,
.btn-group .btn-group + .btn,
.btn-group .btn-group + .btn-group {
  margin-left: -1px;
}
.btn-toolbar {
  margin-left: -5px;
}
.btn-toolbar .btn,
.btn-toolbar .btn-group,
.btn-toolbar .input-group {
  float: left;
}
.btn-toolbar > .btn,
.btn-toolbar > .btn-group,
.btn-toolbar > .input-group {
  margin-left: 5px;
}
.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
  border-radius: 0;
}
.btn-group > .btn:first-child {
  margin-left: 0;
}
.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn:last-child:not(:first-child),
.btn-group > .dropdown-toggle:not(:first-child) {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group > .btn-group {
  float: left;
}
.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group .dropdown-toggle:active,
.btn-group.open .dropdown-toggle {
  outline: 0;
}
.btn-group > .btn + .dropdown-toggle {
  padding-left: 8px;
  padding-right: 8px;
}
.btn-group > .btn-lg + .dropdown-toggle {
  padding-left: 12px;
  padding-right: 12px;
}
.btn-group.open .dropdown-toggle {
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn-group.open .dropdown-toggle.btn-link {
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn .caret {
  margin-left: 0;
}
.btn-lg .caret {
  border-width: 5px 5px 0;
  border-bottom-width: 0;
}
.dropup .btn-lg .caret {
  border-width: 0 5px 5px;
}
.btn-group-vertical > .btn,
.btn-group-vertical > .btn-group,
.btn-group-vertical > .btn-group > .btn {
  display: block;
  float: none;
  width: 100%;
  max-width: 100%;
}
.btn-group-vertical > .btn-group > .btn {
  float: none;
}
.btn-group-vertical > .btn + .btn,
.btn-group-vertical > .btn + .btn-group,
.btn-group-vertical > .btn-group + .btn,
.btn-group-vertical > .btn-group + .btn-group {
  margin-top: -1px;
  margin-left: 0;
}
.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.btn-group-vertical > .btn:first-child:not(:last-child) {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn:last-child:not(:first-child) {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.btn-group-justified {
  display: table;
  width: 100%;
  table-layout: fixed;
  border-collapse: separate;
}
.btn-group-justified > .btn,
.btn-group-justified > .btn-group {
  float: none;
  display: table-cell;
  width: 1%;
}
.btn-group-justified > .btn-group .btn {
  width: 100%;
}
.btn-group-justified > .btn-group .dropdown-menu {
  left: auto;
}
[data-toggle="buttons"] > .btn input[type="radio"],
[data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
[data-toggle="buttons"] > .btn input[type="checkbox"],
[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
  position: absolute;
  clip: rect(0, 0, 0, 0);
  pointer-events: none;
}
.input-group {
  position: relative;
  display: table;
  border-collapse: separate;
}
.input-group[class*="col-"] {
  float: none;
  padding-left: 0;
  padding-right: 0;
}
.input-group .form-control {
  position: relative;
  z-index: 2;
  float: left;
  width: 100%;
  margin-bottom: 0;
}
.input-group .form-control:focus {
  z-index: 3;
}
.input-group-lg > .form-control,
.input-group-lg > .input-group-addon,
.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-group-lg > .form-control,
select.input-group-lg > .input-group-addon,
select.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  line-height: 45px;
}
textarea.input-group-lg > .form-control,
textarea.input-group-lg > .input-group-addon,
textarea.input-group-lg > .input-group-btn > .btn,
select[multiple].input-group-lg > .form-control,
select[multiple].input-group-lg > .input-group-addon,
select[multiple].input-group-lg > .input-group-btn > .btn {
  height: auto;
}
.input-group-sm > .form-control,
.input-group-sm > .input-group-addon,
.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-group-sm > .form-control,
select.input-group-sm > .input-group-addon,
select.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  line-height: 30px;
}
textarea.input-group-sm > .form-control,
textarea.input-group-sm > .input-group-addon,
textarea.input-group-sm > .input-group-btn > .btn,
select[multiple].input-group-sm > .form-control,
select[multiple].input-group-sm > .input-group-addon,
select[multiple].input-group-sm > .input-group-btn > .btn {
  height: auto;
}
.input-group-addon,
.input-group-btn,
.input-group .form-control {
  display: table-cell;
}
.input-group-addon:not(:first-child):not(:last-child),
.input-group-btn:not(:first-child):not(:last-child),
.input-group .form-control:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.input-group-addon,
.input-group-btn {
  width: 1%;
  white-space: nowrap;
  vertical-align: middle;
}
.input-group-addon {
  padding: 6px 12px;
  font-size: 13px;
  font-weight: normal;
  line-height: 1;
  color: #555555;
  text-align: center;
  background-color: #eeeeee;
  border: 1px solid #ccc;
  border-radius: 2px;
}
.input-group-addon.input-sm {
  padding: 5px 10px;
  font-size: 12px;
  border-radius: 1px;
}
.input-group-addon.input-lg {
  padding: 10px 16px;
  font-size: 17px;
  border-radius: 3px;
}
.input-group-addon input[type="radio"],
.input-group-addon input[type="checkbox"] {
  margin-top: 0;
}
.input-group .form-control:first-child,
.input-group-addon:first-child,
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group > .btn,
.input-group-btn:first-child > .dropdown-toggle,
.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
.input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.input-group-addon:first-child {
  border-right: 0;
}
.input-group .form-control:last-child,
.input-group-addon:last-child,
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group > .btn,
.input-group-btn:last-child > .dropdown-toggle,
.input-group-btn:first-child > .btn:not(:first-child),
.input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.input-group-addon:last-child {
  border-left: 0;
}
.input-group-btn {
  position: relative;
  font-size: 0;
  white-space: nowrap;
}
.input-group-btn > .btn {
  position: relative;
}
.input-group-btn > .btn + .btn {
  margin-left: -1px;
}
.input-group-btn > .btn:hover,
.input-group-btn > .btn:focus,
.input-group-btn > .btn:active {
  z-index: 2;
}
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group {
  margin-right: -1px;
}
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group {
  z-index: 2;
  margin-left: -1px;
}
.nav {
  margin-bottom: 0;
  padding-left: 0;
  list-style: none;
}
.nav > li {
  position: relative;
  display: block;
}
.nav > li > a {
  position: relative;
  display: block;
  padding: 10px 15px;
}
.nav > li > a:hover,
.nav > li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.nav > li.disabled > a {
  color: #777777;
}
.nav > li.disabled > a:hover,
.nav > li.disabled > a:focus {
  color: #777777;
  text-decoration: none;
  background-color: transparent;
  cursor: not-allowed;
}
.nav .open > a,
.nav .open > a:hover,
.nav .open > a:focus {
  background-color: #eeeeee;
  border-color: #337ab7;
}
.nav .nav-divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.nav > li > a > img {
  max-width: none;
}
.nav-tabs {
  border-bottom: 1px solid #ddd;
}
.nav-tabs > li {
  float: left;
  margin-bottom: -1px;
}
.nav-tabs > li > a {
  margin-right: 2px;
  line-height: 1.42857143;
  border: 1px solid transparent;
  border-radius: 2px 2px 0 0;
}
.nav-tabs > li > a:hover {
  border-color: #eeeeee #eeeeee #ddd;
}
.nav-tabs > li.active > a,
.nav-tabs > li.active > a:hover,
.nav-tabs > li.active > a:focus {
  color: #555555;
  background-color: #fff;
  border: 1px solid #ddd;
  border-bottom-color: transparent;
  cursor: default;
}
.nav-tabs.nav-justified {
  width: 100%;
  border-bottom: 0;
}
.nav-tabs.nav-justified > li {
  float: none;
}
.nav-tabs.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-tabs.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-tabs.nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs.nav-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs.nav-justified > .active > a,
.nav-tabs.nav-justified > .active > a:hover,
.nav-tabs.nav-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs.nav-justified > .active > a,
  .nav-tabs.nav-justified > .active > a:hover,
  .nav-tabs.nav-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.nav-pills > li {
  float: left;
}
.nav-pills > li > a {
  border-radius: 2px;
}
.nav-pills > li + li {
  margin-left: 2px;
}
.nav-pills > li.active > a,
.nav-pills > li.active > a:hover,
.nav-pills > li.active > a:focus {
  color: #fff;
  background-color: #337ab7;
}
.nav-stacked > li {
  float: none;
}
.nav-stacked > li + li {
  margin-top: 2px;
  margin-left: 0;
}
.nav-justified {
  width: 100%;
}
.nav-justified > li {
  float: none;
}
.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs-justified {
  border-bottom: 0;
}
.nav-tabs-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs-justified > .active > a,
.nav-tabs-justified > .active > a:hover,
.nav-tabs-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs-justified > .active > a,
  .nav-tabs-justified > .active > a:hover,
  .nav-tabs-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.tab-content > .tab-pane {
  display: none;
}
.tab-content > .active {
  display: block;
}
.nav-tabs .dropdown-menu {
  margin-top: -1px;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar {
  position: relative;
  min-height: 30px;
  margin-bottom: 18px;
  border: 1px solid transparent;
}
@media (min-width: 541px) {
  .navbar {
    border-radius: 2px;
  }
}
@media (min-width: 541px) {
  .navbar-header {
    float: left;
  }
}
.navbar-collapse {
  overflow-x: visible;
  padding-right: 0px;
  padding-left: 0px;
  border-top: 1px solid transparent;
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
  -webkit-overflow-scrolling: touch;
}
.navbar-collapse.in {
  overflow-y: auto;
}
@media (min-width: 541px) {
  .navbar-collapse {
    width: auto;
    border-top: 0;
    box-shadow: none;
  }
  .navbar-collapse.collapse {
    display: block !important;
    height: auto !important;
    padding-bottom: 0;
    overflow: visible !important;
  }
  .navbar-collapse.in {
    overflow-y: visible;
  }
  .navbar-fixed-top .navbar-collapse,
  .navbar-static-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    padding-left: 0;
    padding-right: 0;
  }
}
.navbar-fixed-top .navbar-collapse,
.navbar-fixed-bottom .navbar-collapse {
  max-height: 340px;
}
@media (max-device-width: 540px) and (orientation: landscape) {
  .navbar-fixed-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    max-height: 200px;
  }
}
.container > .navbar-header,
.container-fluid > .navbar-header,
.container > .navbar-collapse,
.container-fluid > .navbar-collapse {
  margin-right: 0px;
  margin-left: 0px;
}
@media (min-width: 541px) {
  .container > .navbar-header,
  .container-fluid > .navbar-header,
  .container > .navbar-collapse,
  .container-fluid > .navbar-collapse {
    margin-right: 0;
    margin-left: 0;
  }
}
.navbar-static-top {
  z-index: 1000;
  border-width: 0 0 1px;
}
@media (min-width: 541px) {
  .navbar-static-top {
    border-radius: 0;
  }
}
.navbar-fixed-top,
.navbar-fixed-bottom {
  position: fixed;
  right: 0;
  left: 0;
  z-index: 1030;
}
@media (min-width: 541px) {
  .navbar-fixed-top,
  .navbar-fixed-bottom {
    border-radius: 0;
  }
}
.navbar-fixed-top {
  top: 0;
  border-width: 0 0 1px;
}
.navbar-fixed-bottom {
  bottom: 0;
  margin-bottom: 0;
  border-width: 1px 0 0;
}
.navbar-brand {
  float: left;
  padding: 6px 0px;
  font-size: 17px;
  line-height: 18px;
  height: 30px;
}
.navbar-brand:hover,
.navbar-brand:focus {
  text-decoration: none;
}
.navbar-brand > img {
  display: block;
}
@media (min-width: 541px) {
  .navbar > .container .navbar-brand,
  .navbar > .container-fluid .navbar-brand {
    margin-left: 0px;
  }
}
.navbar-toggle {
  position: relative;
  float: right;
  margin-right: 0px;
  padding: 9px 10px;
  margin-top: -2px;
  margin-bottom: -2px;
  background-color: transparent;
  background-image: none;
  border: 1px solid transparent;
  border-radius: 2px;
}
.navbar-toggle:focus {
  outline: 0;
}
.navbar-toggle .icon-bar {
  display: block;
  width: 22px;
  height: 2px;
  border-radius: 1px;
}
.navbar-toggle .icon-bar + .icon-bar {
  margin-top: 4px;
}
@media (min-width: 541px) {
  .navbar-toggle {
    display: none;
  }
}
.navbar-nav {
  margin: 3px 0px;
}
.navbar-nav > li > a {
  padding-top: 10px;
  padding-bottom: 10px;
  line-height: 18px;
}
@media (max-width: 540px) {
  .navbar-nav .open .dropdown-menu {
    position: static;
    float: none;
    width: auto;
    margin-top: 0;
    background-color: transparent;
    border: 0;
    box-shadow: none;
  }
  .navbar-nav .open .dropdown-menu > li > a,
  .navbar-nav .open .dropdown-menu .dropdown-header {
    padding: 5px 15px 5px 25px;
  }
  .navbar-nav .open .dropdown-menu > li > a {
    line-height: 18px;
  }
  .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-nav .open .dropdown-menu > li > a:focus {
    background-image: none;
  }
}
@media (min-width: 541px) {
  .navbar-nav {
    float: left;
    margin: 0;
  }
  .navbar-nav > li {
    float: left;
  }
  .navbar-nav > li > a {
    padding-top: 6px;
    padding-bottom: 6px;
  }
}
.navbar-form {
  margin-left: 0px;
  margin-right: 0px;
  padding: 10px 0px;
  border-top: 1px solid transparent;
  border-bottom: 1px solid transparent;
  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  margin-top: -1px;
  margin-bottom: -1px;
}
@media (min-width: 768px) {
  .navbar-form .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .navbar-form .form-control-static {
    display: inline-block;
  }
  .navbar-form .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .navbar-form .input-group .input-group-addon,
  .navbar-form .input-group .input-group-btn,
  .navbar-form .input-group .form-control {
    width: auto;
  }
  .navbar-form .input-group > .form-control {
    width: 100%;
  }
  .navbar-form .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio,
  .navbar-form .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio label,
  .navbar-form .checkbox label {
    padding-left: 0;
  }
  .navbar-form .radio input[type="radio"],
  .navbar-form .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .navbar-form .has-feedback .form-control-feedback {
    top: 0;
  }
}
@media (max-width: 540px) {
  .navbar-form .form-group {
    margin-bottom: 5px;
  }
  .navbar-form .form-group:last-child {
    margin-bottom: 0;
  }
}
@media (min-width: 541px) {
  .navbar-form {
    width: auto;
    border: 0;
    margin-left: 0;
    margin-right: 0;
    padding-top: 0;
    padding-bottom: 0;
    -webkit-box-shadow: none;
    box-shadow: none;
  }
}
.navbar-nav > li > .dropdown-menu {
  margin-top: 0;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
  margin-bottom: 0;
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.navbar-btn {
  margin-top: -1px;
  margin-bottom: -1px;
}
.navbar-btn.btn-sm {
  margin-top: 0px;
  margin-bottom: 0px;
}
.navbar-btn.btn-xs {
  margin-top: 4px;
  margin-bottom: 4px;
}
.navbar-text {
  margin-top: 6px;
  margin-bottom: 6px;
}
@media (min-width: 541px) {
  .navbar-text {
    float: left;
    margin-left: 0px;
    margin-right: 0px;
  }
}
@media (min-width: 541px) {
  .navbar-left {
    float: left !important;
    float: left;
  }
  .navbar-right {
    float: right !important;
    float: right;
    margin-right: 0px;
  }
  .navbar-right ~ .navbar-right {
    margin-right: 0;
  }
}
.navbar-default {
  background-color: #f8f8f8;
  border-color: #e7e7e7;
}
.navbar-default .navbar-brand {
  color: #777;
}
.navbar-default .navbar-brand:hover,
.navbar-default .navbar-brand:focus {
  color: #5e5e5e;
  background-color: transparent;
}
.navbar-default .navbar-text {
  color: #777;
}
.navbar-default .navbar-nav > li > a {
  color: #777;
}
.navbar-default .navbar-nav > li > a:hover,
.navbar-default .navbar-nav > li > a:focus {
  color: #333;
  background-color: transparent;
}
.navbar-default .navbar-nav > .active > a,
.navbar-default .navbar-nav > .active > a:hover,
.navbar-default .navbar-nav > .active > a:focus {
  color: #555;
  background-color: #e7e7e7;
}
.navbar-default .navbar-nav > .disabled > a,
.navbar-default .navbar-nav > .disabled > a:hover,
.navbar-default .navbar-nav > .disabled > a:focus {
  color: #ccc;
  background-color: transparent;
}
.navbar-default .navbar-toggle {
  border-color: #ddd;
}
.navbar-default .navbar-toggle:hover,
.navbar-default .navbar-toggle:focus {
  background-color: #ddd;
}
.navbar-default .navbar-toggle .icon-bar {
  background-color: #888;
}
.navbar-default .navbar-collapse,
.navbar-default .navbar-form {
  border-color: #e7e7e7;
}
.navbar-default .navbar-nav > .open > a,
.navbar-default .navbar-nav > .open > a:hover,
.navbar-default .navbar-nav > .open > a:focus {
  background-color: #e7e7e7;
  color: #555;
}
@media (max-width: 540px) {
  .navbar-default .navbar-nav .open .dropdown-menu > li > a {
    color: #777;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #333;
    background-color: transparent;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #555;
    background-color: #e7e7e7;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #ccc;
    background-color: transparent;
  }
}
.navbar-default .navbar-link {
  color: #777;
}
.navbar-default .navbar-link:hover {
  color: #333;
}
.navbar-default .btn-link {
  color: #777;
}
.navbar-default .btn-link:hover,
.navbar-default .btn-link:focus {
  color: #333;
}
.navbar-default .btn-link[disabled]:hover,
fieldset[disabled] .navbar-default .btn-link:hover,
.navbar-default .btn-link[disabled]:focus,
fieldset[disabled] .navbar-default .btn-link:focus {
  color: #ccc;
}
.navbar-inverse {
  background-color: #222;
  border-color: #080808;
}
.navbar-inverse .navbar-brand {
  color: #9d9d9d;
}
.navbar-inverse .navbar-brand:hover,
.navbar-inverse .navbar-brand:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-text {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a:hover,
.navbar-inverse .navbar-nav > li > a:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-nav > .active > a,
.navbar-inverse .navbar-nav > .active > a:hover,
.navbar-inverse .navbar-nav > .active > a:focus {
  color: #fff;
  background-color: #080808;
}
.navbar-inverse .navbar-nav > .disabled > a,
.navbar-inverse .navbar-nav > .disabled > a:hover,
.navbar-inverse .navbar-nav > .disabled > a:focus {
  color: #444;
  background-color: transparent;
}
.navbar-inverse .navbar-toggle {
  border-color: #333;
}
.navbar-inverse .navbar-toggle:hover,
.navbar-inverse .navbar-toggle:focus {
  background-color: #333;
}
.navbar-inverse .navbar-toggle .icon-bar {
  background-color: #fff;
}
.navbar-inverse .navbar-collapse,
.navbar-inverse .navbar-form {
  border-color: #101010;
}
.navbar-inverse .navbar-nav > .open > a,
.navbar-inverse .navbar-nav > .open > a:hover,
.navbar-inverse .navbar-nav > .open > a:focus {
  background-color: #080808;
  color: #fff;
}
@media (max-width: 540px) {
  .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
    border-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
    color: #9d9d9d;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #fff;
    background-color: transparent;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #fff;
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #444;
    background-color: transparent;
  }
}
.navbar-inverse .navbar-link {
  color: #9d9d9d;
}
.navbar-inverse .navbar-link:hover {
  color: #fff;
}
.navbar-inverse .btn-link {
  color: #9d9d9d;
}
.navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link:focus {
  color: #fff;
}
.navbar-inverse .btn-link[disabled]:hover,
fieldset[disabled] .navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link[disabled]:focus,
fieldset[disabled] .navbar-inverse .btn-link:focus {
  color: #444;
}
.breadcrumb {
  padding: 8px 15px;
  margin-bottom: 18px;
  list-style: none;
  background-color: #f5f5f5;
  border-radius: 2px;
}
.breadcrumb > li {
  display: inline-block;
}
.breadcrumb > li + li:before {
  content: "/\00a0";
  padding: 0 5px;
  color: #5e5e5e;
}
.breadcrumb > .active {
  color: #777777;
}
.pagination {
  display: inline-block;
  padding-left: 0;
  margin: 18px 0;
  border-radius: 2px;
}
.pagination > li {
  display: inline;
}
.pagination > li > a,
.pagination > li > span {
  position: relative;
  float: left;
  padding: 6px 12px;
  line-height: 1.42857143;
  text-decoration: none;
  color: #337ab7;
  background-color: #fff;
  border: 1px solid #ddd;
  margin-left: -1px;
}
.pagination > li:first-child > a,
.pagination > li:first-child > span {
  margin-left: 0;
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.pagination > li:last-child > a,
.pagination > li:last-child > span {
  border-bottom-right-radius: 2px;
  border-top-right-radius: 2px;
}
.pagination > li > a:hover,
.pagination > li > span:hover,
.pagination > li > a:focus,
.pagination > li > span:focus {
  z-index: 2;
  color: #23527c;
  background-color: #eeeeee;
  border-color: #ddd;
}
.pagination > .active > a,
.pagination > .active > span,
.pagination > .active > a:hover,
.pagination > .active > span:hover,
.pagination > .active > a:focus,
.pagination > .active > span:focus {
  z-index: 3;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
  cursor: default;
}
.pagination > .disabled > span,
.pagination > .disabled > span:hover,
.pagination > .disabled > span:focus,
.pagination > .disabled > a,
.pagination > .disabled > a:hover,
.pagination > .disabled > a:focus {
  color: #777777;
  background-color: #fff;
  border-color: #ddd;
  cursor: not-allowed;
}
.pagination-lg > li > a,
.pagination-lg > li > span {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.pagination-lg > li:first-child > a,
.pagination-lg > li:first-child > span {
  border-bottom-left-radius: 3px;
  border-top-left-radius: 3px;
}
.pagination-lg > li:last-child > a,
.pagination-lg > li:last-child > span {
  border-bottom-right-radius: 3px;
  border-top-right-radius: 3px;
}
.pagination-sm > li > a,
.pagination-sm > li > span {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.pagination-sm > li:first-child > a,
.pagination-sm > li:first-child > span {
  border-bottom-left-radius: 1px;
  border-top-left-radius: 1px;
}
.pagination-sm > li:last-child > a,
.pagination-sm > li:last-child > span {
  border-bottom-right-radius: 1px;
  border-top-right-radius: 1px;
}
.pager {
  padding-left: 0;
  margin: 18px 0;
  list-style: none;
  text-align: center;
}
.pager li {
  display: inline;
}
.pager li > a,
.pager li > span {
  display: inline-block;
  padding: 5px 14px;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 15px;
}
.pager li > a:hover,
.pager li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.pager .next > a,
.pager .next > span {
  float: right;
}
.pager .previous > a,
.pager .previous > span {
  float: left;
}
.pager .disabled > a,
.pager .disabled > a:hover,
.pager .disabled > a:focus,
.pager .disabled > span {
  color: #777777;
  background-color: #fff;
  cursor: not-allowed;
}
.label {
  display: inline;
  padding: .2em .6em .3em;
  font-size: 75%;
  font-weight: bold;
  line-height: 1;
  color: #fff;
  text-align: center;
  white-space: nowrap;
  vertical-align: baseline;
  border-radius: .25em;
}
a.label:hover,
a.label:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.label:empty {
  display: none;
}
.btn .label {
  position: relative;
  top: -1px;
}
.label-default {
  background-color: #777777;
}
.label-default[href]:hover,
.label-default[href]:focus {
  background-color: #5e5e5e;
}
.label-primary {
  background-color: #337ab7;
}
.label-primary[href]:hover,
.label-primary[href]:focus {
  background-color: #286090;
}
.label-success {
  background-color: #5cb85c;
}
.label-success[href]:hover,
.label-success[href]:focus {
  background-color: #449d44;
}
.label-info {
  background-color: #5bc0de;
}
.label-info[href]:hover,
.label-info[href]:focus {
  background-color: #31b0d5;
}
.label-warning {
  background-color: #f0ad4e;
}
.label-warning[href]:hover,
.label-warning[href]:focus {
  background-color: #ec971f;
}
.label-danger {
  background-color: #d9534f;
}
.label-danger[href]:hover,
.label-danger[href]:focus {
  background-color: #c9302c;
}
.badge {
  display: inline-block;
  min-width: 10px;
  padding: 3px 7px;
  font-size: 12px;
  font-weight: bold;
  color: #fff;
  line-height: 1;
  vertical-align: middle;
  white-space: nowrap;
  text-align: center;
  background-color: #777777;
  border-radius: 10px;
}
.badge:empty {
  display: none;
}
.btn .badge {
  position: relative;
  top: -1px;
}
.btn-xs .badge,
.btn-group-xs > .btn .badge {
  top: 0;
  padding: 1px 5px;
}
a.badge:hover,
a.badge:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.list-group-item.active > .badge,
.nav-pills > .active > a > .badge {
  color: #337ab7;
  background-color: #fff;
}
.list-group-item > .badge {
  float: right;
}
.list-group-item > .badge + .badge {
  margin-right: 5px;
}
.nav-pills > li > a > .badge {
  margin-left: 3px;
}
.jumbotron {
  padding-top: 30px;
  padding-bottom: 30px;
  margin-bottom: 30px;
  color: inherit;
  background-color: #eeeeee;
}
.jumbotron h1,
.jumbotron .h1 {
  color: inherit;
}
.jumbotron p {
  margin-bottom: 15px;
  font-size: 20px;
  font-weight: 200;
}
.jumbotron > hr {
  border-top-color: #d5d5d5;
}
.container .jumbotron,
.container-fluid .jumbotron {
  border-radius: 3px;
  padding-left: 0px;
  padding-right: 0px;
}
.jumbotron .container {
  max-width: 100%;
}
@media screen and (min-width: 768px) {
  .jumbotron {
    padding-top: 48px;
    padding-bottom: 48px;
  }
  .container .jumbotron,
  .container-fluid .jumbotron {
    padding-left: 60px;
    padding-right: 60px;
  }
  .jumbotron h1,
  .jumbotron .h1 {
    font-size: 59px;
  }
}
.thumbnail {
  display: block;
  padding: 4px;
  margin-bottom: 18px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: border 0.2s ease-in-out;
  -o-transition: border 0.2s ease-in-out;
  transition: border 0.2s ease-in-out;
}
.thumbnail > img,
.thumbnail a > img {
  margin-left: auto;
  margin-right: auto;
}
a.thumbnail:hover,
a.thumbnail:focus,
a.thumbnail.active {
  border-color: #337ab7;
}
.thumbnail .caption {
  padding: 9px;
  color: #000;
}
.alert {
  padding: 15px;
  margin-bottom: 18px;
  border: 1px solid transparent;
  border-radius: 2px;
}
.alert h4 {
  margin-top: 0;
  color: inherit;
}
.alert .alert-link {
  font-weight: bold;
}
.alert > p,
.alert > ul {
  margin-bottom: 0;
}
.alert > p + p {
  margin-top: 5px;
}
.alert-dismissable,
.alert-dismissible {
  padding-right: 35px;
}
.alert-dismissable .close,
.alert-dismissible .close {
  position: relative;
  top: -2px;
  right: -21px;
  color: inherit;
}
.alert-success {
  background-color: #dff0d8;
  border-color: #d6e9c6;
  color: #3c763d;
}
.alert-success hr {
  border-top-color: #c9e2b3;
}
.alert-success .alert-link {
  color: #2b542c;
}
.alert-info {
  background-color: #d9edf7;
  border-color: #bce8f1;
  color: #31708f;
}
.alert-info hr {
  border-top-color: #a6e1ec;
}
.alert-info .alert-link {
  color: #245269;
}
.alert-warning {
  background-color: #fcf8e3;
  border-color: #faebcc;
  color: #8a6d3b;
}
.alert-warning hr {
  border-top-color: #f7e1b5;
}
.alert-warning .alert-link {
  color: #66512c;
}
.alert-danger {
  background-color: #f2dede;
  border-color: #ebccd1;
  color: #a94442;
}
.alert-danger hr {
  border-top-color: #e4b9c0;
}
.alert-danger .alert-link {
  color: #843534;
}
@-webkit-keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
@keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
.progress {
  overflow: hidden;
  height: 18px;
  margin-bottom: 18px;
  background-color: #f5f5f5;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
  box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
}
.progress-bar {
  float: left;
  width: 0%;
  height: 100%;
  font-size: 12px;
  line-height: 18px;
  color: #fff;
  text-align: center;
  background-color: #337ab7;
  -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  -webkit-transition: width 0.6s ease;
  -o-transition: width 0.6s ease;
  transition: width 0.6s ease;
}
.progress-striped .progress-bar,
.progress-bar-striped {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-size: 40px 40px;
}
.progress.active .progress-bar,
.progress-bar.active {
  -webkit-animation: progress-bar-stripes 2s linear infinite;
  -o-animation: progress-bar-stripes 2s linear infinite;
  animation: progress-bar-stripes 2s linear infinite;
}
.progress-bar-success {
  background-color: #5cb85c;
}
.progress-striped .progress-bar-success {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-info {
  background-color: #5bc0de;
}
.progress-striped .progress-bar-info {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-warning {
  background-color: #f0ad4e;
}
.progress-striped .progress-bar-warning {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-danger {
  background-color: #d9534f;
}
.progress-striped .progress-bar-danger {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.media {
  margin-top: 15px;
}
.media:first-child {
  margin-top: 0;
}
.media,
.media-body {
  zoom: 1;
  overflow: hidden;
}
.media-body {
  width: 10000px;
}
.media-object {
  display: block;
}
.media-object.img-thumbnail {
  max-width: none;
}
.media-right,
.media > .pull-right {
  padding-left: 10px;
}
.media-left,
.media > .pull-left {
  padding-right: 10px;
}
.media-left,
.media-right,
.media-body {
  display: table-cell;
  vertical-align: top;
}
.media-middle {
  vertical-align: middle;
}
.media-bottom {
  vertical-align: bottom;
}
.media-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.media-list {
  padding-left: 0;
  list-style: none;
}
.list-group {
  margin-bottom: 20px;
  padding-left: 0;
}
.list-group-item {
  position: relative;
  display: block;
  padding: 10px 15px;
  margin-bottom: -1px;
  background-color: #fff;
  border: 1px solid #ddd;
}
.list-group-item:first-child {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
}
.list-group-item:last-child {
  margin-bottom: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
a.list-group-item,
button.list-group-item {
  color: #555;
}
a.list-group-item .list-group-item-heading,
button.list-group-item .list-group-item-heading {
  color: #333;
}
a.list-group-item:hover,
button.list-group-item:hover,
a.list-group-item:focus,
button.list-group-item:focus {
  text-decoration: none;
  color: #555;
  background-color: #f5f5f5;
}
button.list-group-item {
  width: 100%;
  text-align: left;
}
.list-group-item.disabled,
.list-group-item.disabled:hover,
.list-group-item.disabled:focus {
  background-color: #eeeeee;
  color: #777777;
  cursor: not-allowed;
}
.list-group-item.disabled .list-group-item-heading,
.list-group-item.disabled:hover .list-group-item-heading,
.list-group-item.disabled:focus .list-group-item-heading {
  color: inherit;
}
.list-group-item.disabled .list-group-item-text,
.list-group-item.disabled:hover .list-group-item-text,
.list-group-item.disabled:focus .list-group-item-text {
  color: #777777;
}
.list-group-item.active,
.list-group-item.active:hover,
.list-group-item.active:focus {
  z-index: 2;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.list-group-item.active .list-group-item-heading,
.list-group-item.active:hover .list-group-item-heading,
.list-group-item.active:focus .list-group-item-heading,
.list-group-item.active .list-group-item-heading > small,
.list-group-item.active:hover .list-group-item-heading > small,
.list-group-item.active:focus .list-group-item-heading > small,
.list-group-item.active .list-group-item-heading > .small,
.list-group-item.active:hover .list-group-item-heading > .small,
.list-group-item.active:focus .list-group-item-heading > .small {
  color: inherit;
}
.list-group-item.active .list-group-item-text,
.list-group-item.active:hover .list-group-item-text,
.list-group-item.active:focus .list-group-item-text {
  color: #c7ddef;
}
.list-group-item-success {
  color: #3c763d;
  background-color: #dff0d8;
}
a.list-group-item-success,
button.list-group-item-success {
  color: #3c763d;
}
a.list-group-item-success .list-group-item-heading,
button.list-group-item-success .list-group-item-heading {
  color: inherit;
}
a.list-group-item-success:hover,
button.list-group-item-success:hover,
a.list-group-item-success:focus,
button.list-group-item-success:focus {
  color: #3c763d;
  background-color: #d0e9c6;
}
a.list-group-item-success.active,
button.list-group-item-success.active,
a.list-group-item-success.active:hover,
button.list-group-item-success.active:hover,
a.list-group-item-success.active:focus,
button.list-group-item-success.active:focus {
  color: #fff;
  background-color: #3c763d;
  border-color: #3c763d;
}
.list-group-item-info {
  color: #31708f;
  background-color: #d9edf7;
}
a.list-group-item-info,
button.list-group-item-info {
  color: #31708f;
}
a.list-group-item-info .list-group-item-heading,
button.list-group-item-info .list-group-item-heading {
  color: inherit;
}
a.list-group-item-info:hover,
button.list-group-item-info:hover,
a.list-group-item-info:focus,
button.list-group-item-info:focus {
  color: #31708f;
  background-color: #c4e3f3;
}
a.list-group-item-info.active,
button.list-group-item-info.active,
a.list-group-item-info.active:hover,
button.list-group-item-info.active:hover,
a.list-group-item-info.active:focus,
button.list-group-item-info.active:focus {
  color: #fff;
  background-color: #31708f;
  border-color: #31708f;
}
.list-group-item-warning {
  color: #8a6d3b;
  background-color: #fcf8e3;
}
a.list-group-item-warning,
button.list-group-item-warning {
  color: #8a6d3b;
}
a.list-group-item-warning .list-group-item-heading,
button.list-group-item-warning .list-group-item-heading {
  color: inherit;
}
a.list-group-item-warning:hover,
button.list-group-item-warning:hover,
a.list-group-item-warning:focus,
button.list-group-item-warning:focus {
  color: #8a6d3b;
  background-color: #faf2cc;
}
a.list-group-item-warning.active,
button.list-group-item-warning.active,
a.list-group-item-warning.active:hover,
button.list-group-item-warning.active:hover,
a.list-group-item-warning.active:focus,
button.list-group-item-warning.active:focus {
  color: #fff;
  background-color: #8a6d3b;
  border-color: #8a6d3b;
}
.list-group-item-danger {
  color: #a94442;
  background-color: #f2dede;
}
a.list-group-item-danger,
button.list-group-item-danger {
  color: #a94442;
}
a.list-group-item-danger .list-group-item-heading,
button.list-group-item-danger .list-group-item-heading {
  color: inherit;
}
a.list-group-item-danger:hover,
button.list-group-item-danger:hover,
a.list-group-item-danger:focus,
button.list-group-item-danger:focus {
  color: #a94442;
  background-color: #ebcccc;
}
a.list-group-item-danger.active,
button.list-group-item-danger.active,
a.list-group-item-danger.active:hover,
button.list-group-item-danger.active:hover,
a.list-group-item-danger.active:focus,
button.list-group-item-danger.active:focus {
  color: #fff;
  background-color: #a94442;
  border-color: #a94442;
}
.list-group-item-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.list-group-item-text {
  margin-bottom: 0;
  line-height: 1.3;
}
.panel {
  margin-bottom: 18px;
  background-color: #fff;
  border: 1px solid transparent;
  border-radius: 2px;
  -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
}
.panel-body {
  padding: 15px;
}
.panel-heading {
  padding: 10px 15px;
  border-bottom: 1px solid transparent;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel-heading > .dropdown .dropdown-toggle {
  color: inherit;
}
.panel-title {
  margin-top: 0;
  margin-bottom: 0;
  font-size: 15px;
  color: inherit;
}
.panel-title > a,
.panel-title > small,
.panel-title > .small,
.panel-title > small > a,
.panel-title > .small > a {
  color: inherit;
}
.panel-footer {
  padding: 10px 15px;
  background-color: #f5f5f5;
  border-top: 1px solid #ddd;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .list-group,
.panel > .panel-collapse > .list-group {
  margin-bottom: 0;
}
.panel > .list-group .list-group-item,
.panel > .panel-collapse > .list-group .list-group-item {
  border-width: 1px 0;
  border-radius: 0;
}
.panel > .list-group:first-child .list-group-item:first-child,
.panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
  border-top: 0;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .list-group:last-child .list-group-item:last-child,
.panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
  border-bottom: 0;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.panel-heading + .list-group .list-group-item:first-child {
  border-top-width: 0;
}
.list-group + .panel-footer {
  border-top-width: 0;
}
.panel > .table,
.panel > .table-responsive > .table,
.panel > .panel-collapse > .table {
  margin-bottom: 0;
}
.panel > .table caption,
.panel > .table-responsive > .table caption,
.panel > .panel-collapse > .table caption {
  padding-left: 15px;
  padding-right: 15px;
}
.panel > .table:first-child,
.panel > .table-responsive:first-child > .table:first-child {
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
  border-top-left-radius: 1px;
  border-top-right-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
  border-top-right-radius: 1px;
}
.panel > .table:last-child,
.panel > .table-responsive:last-child > .table:last-child {
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
  border-bottom-left-radius: 1px;
  border-bottom-right-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
  border-bottom-right-radius: 1px;
}
.panel > .panel-body + .table,
.panel > .panel-body + .table-responsive,
.panel > .table + .panel-body,
.panel > .table-responsive + .panel-body {
  border-top: 1px solid #ddd;
}
.panel > .table > tbody:first-child > tr:first-child th,
.panel > .table > tbody:first-child > tr:first-child td {
  border-top: 0;
}
.panel > .table-bordered,
.panel > .table-responsive > .table-bordered {
  border: 0;
}
.panel > .table-bordered > thead > tr > th:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
.panel > .table-bordered > tbody > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
.panel > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-bordered > thead > tr > td:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
.panel > .table-bordered > tbody > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
.panel > .table-bordered > tfoot > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
  border-left: 0;
}
.panel > .table-bordered > thead > tr > th:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
.panel > .table-bordered > tbody > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
.panel > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-bordered > thead > tr > td:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
.panel > .table-bordered > tbody > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
.panel > .table-bordered > tfoot > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
  border-right: 0;
}
.panel > .table-bordered > thead > tr:first-child > td,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
.panel > .table-bordered > tbody > tr:first-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
.panel > .table-bordered > thead > tr:first-child > th,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
.panel > .table-bordered > tbody > tr:first-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
  border-bottom: 0;
}
.panel > .table-bordered > tbody > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
.panel > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-bordered > tbody > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
.panel > .table-bordered > tfoot > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
  border-bottom: 0;
}
.panel > .table-responsive {
  border: 0;
  margin-bottom: 0;
}
.panel-group {
  margin-bottom: 18px;
}
.panel-group .panel {
  margin-bottom: 0;
  border-radius: 2px;
}
.panel-group .panel + .panel {
  margin-top: 5px;
}
.panel-group .panel-heading {
  border-bottom: 0;
}
.panel-group .panel-heading + .panel-collapse > .panel-body,
.panel-group .panel-heading + .panel-collapse > .list-group {
  border-top: 1px solid #ddd;
}
.panel-group .panel-footer {
  border-top: 0;
}
.panel-group .panel-footer + .panel-collapse .panel-body {
  border-bottom: 1px solid #ddd;
}
.panel-default {
  border-color: #ddd;
}
.panel-default > .panel-heading {
  color: #333333;
  background-color: #f5f5f5;
  border-color: #ddd;
}
.panel-default > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ddd;
}
.panel-default > .panel-heading .badge {
  color: #f5f5f5;
  background-color: #333333;
}
.panel-default > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ddd;
}
.panel-primary {
  border-color: #337ab7;
}
.panel-primary > .panel-heading {
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.panel-primary > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #337ab7;
}
.panel-primary > .panel-heading .badge {
  color: #337ab7;
  background-color: #fff;
}
.panel-primary > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #337ab7;
}
.panel-success {
  border-color: #d6e9c6;
}
.panel-success > .panel-heading {
  color: #3c763d;
  background-color: #dff0d8;
  border-color: #d6e9c6;
}
.panel-success > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #d6e9c6;
}
.panel-success > .panel-heading .badge {
  color: #dff0d8;
  background-color: #3c763d;
}
.panel-success > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #d6e9c6;
}
.panel-info {
  border-color: #bce8f1;
}
.panel-info > .panel-heading {
  color: #31708f;
  background-color: #d9edf7;
  border-color: #bce8f1;
}
.panel-info > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #bce8f1;
}
.panel-info > .panel-heading .badge {
  color: #d9edf7;
  background-color: #31708f;
}
.panel-info > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #bce8f1;
}
.panel-warning {
  border-color: #faebcc;
}
.panel-warning > .panel-heading {
  color: #8a6d3b;
  background-color: #fcf8e3;
  border-color: #faebcc;
}
.panel-warning > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #faebcc;
}
.panel-warning > .panel-heading .badge {
  color: #fcf8e3;
  background-color: #8a6d3b;
}
.panel-warning > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #faebcc;
}
.panel-danger {
  border-color: #ebccd1;
}
.panel-danger > .panel-heading {
  color: #a94442;
  background-color: #f2dede;
  border-color: #ebccd1;
}
.panel-danger > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ebccd1;
}
.panel-danger > .panel-heading .badge {
  color: #f2dede;
  background-color: #a94442;
}
.panel-danger > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ebccd1;
}
.embed-responsive {
  position: relative;
  display: block;
  height: 0;
  padding: 0;
  overflow: hidden;
}
.embed-responsive .embed-responsive-item,
.embed-responsive iframe,
.embed-responsive embed,
.embed-responsive object,
.embed-responsive video {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  height: 100%;
  width: 100%;
  border: 0;
}
.embed-responsive-16by9 {
  padding-bottom: 56.25%;
}
.embed-responsive-4by3 {
  padding-bottom: 75%;
}
.well {
  min-height: 20px;
  padding: 19px;
  margin-bottom: 20px;
  background-color: #f5f5f5;
  border: 1px solid #e3e3e3;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
}
.well blockquote {
  border-color: #ddd;
  border-color: rgba(0, 0, 0, 0.15);
}
.well-lg {
  padding: 24px;
  border-radius: 3px;
}
.well-sm {
  padding: 9px;
  border-radius: 1px;
}
.close {
  float: right;
  font-size: 19.5px;
  font-weight: bold;
  line-height: 1;
  color: #000;
  text-shadow: 0 1px 0 #fff;
  opacity: 0.2;
  filter: alpha(opacity=20);
}
.close:hover,
.close:focus {
  color: #000;
  text-decoration: none;
  cursor: pointer;
  opacity: 0.5;
  filter: alpha(opacity=50);
}
button.close {
  padding: 0;
  cursor: pointer;
  background: transparent;
  border: 0;
  -webkit-appearance: none;
}
.modal-open {
  overflow: hidden;
}
.modal {
  display: none;
  overflow: hidden;
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1050;
  -webkit-overflow-scrolling: touch;
  outline: 0;
}
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, -25%);
  -ms-transform: translate(0, -25%);
  -o-transform: translate(0, -25%);
  transform: translate(0, -25%);
  -webkit-transition: -webkit-transform 0.3s ease-out;
  -moz-transition: -moz-transform 0.3s ease-out;
  -o-transition: -o-transform 0.3s ease-out;
  transition: transform 0.3s ease-out;
}
.modal.in .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
.modal-open .modal {
  overflow-x: hidden;
  overflow-y: auto;
}
.modal-dialog {
  position: relative;
  width: auto;
  margin: 10px;
}
.modal-content {
  position: relative;
  background-color: #fff;
  border: 1px solid #999;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  background-clip: padding-box;
  outline: 0;
}
.modal-backdrop {
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1040;
  background-color: #000;
}
.modal-backdrop.fade {
  opacity: 0;
  filter: alpha(opacity=0);
}
.modal-backdrop.in {
  opacity: 0.5;
  filter: alpha(opacity=50);
}
.modal-header {
  padding: 15px;
  border-bottom: 1px solid #e5e5e5;
}
.modal-header .close {
  margin-top: -2px;
}
.modal-title {
  margin: 0;
  line-height: 1.42857143;
}
.modal-body {
  position: relative;
  padding: 15px;
}
.modal-footer {
  padding: 15px;
  text-align: right;
  border-top: 1px solid #e5e5e5;
}
.modal-footer .btn + .btn {
  margin-left: 5px;
  margin-bottom: 0;
}
.modal-footer .btn-group .btn + .btn {
  margin-left: -1px;
}
.modal-footer .btn-block + .btn-block {
  margin-left: 0;
}
.modal-scrollbar-measure {
  position: absolute;
  top: -9999px;
  width: 50px;
  height: 50px;
  overflow: scroll;
}
@media (min-width: 768px) {
  .modal-dialog {
    width: 600px;
    margin: 30px auto;
  }
  .modal-content {
    -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
  }
  .modal-sm {
    width: 300px;
  }
}
@media (min-width: 992px) {
  .modal-lg {
    width: 900px;
  }
}
.tooltip {
  position: absolute;
  z-index: 1070;
  display: block;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 12px;
  opacity: 0;
  filter: alpha(opacity=0);
}
.tooltip.in {
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.tooltip.top {
  margin-top: -3px;
  padding: 5px 0;
}
.tooltip.right {
  margin-left: 3px;
  padding: 0 5px;
}
.tooltip.bottom {
  margin-top: 3px;
  padding: 5px 0;
}
.tooltip.left {
  margin-left: -3px;
  padding: 0 5px;
}
.tooltip-inner {
  max-width: 200px;
  padding: 3px 8px;
  color: #fff;
  text-align: center;
  background-color: #000;
  border-radius: 2px;
}
.tooltip-arrow {
  position: absolute;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.tooltip.top .tooltip-arrow {
  bottom: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-left .tooltip-arrow {
  bottom: 0;
  right: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-right .tooltip-arrow {
  bottom: 0;
  left: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.right .tooltip-arrow {
  top: 50%;
  left: 0;
  margin-top: -5px;
  border-width: 5px 5px 5px 0;
  border-right-color: #000;
}
.tooltip.left .tooltip-arrow {
  top: 50%;
  right: 0;
  margin-top: -5px;
  border-width: 5px 0 5px 5px;
  border-left-color: #000;
}
.tooltip.bottom .tooltip-arrow {
  top: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-left .tooltip-arrow {
  top: 0;
  right: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-right .tooltip-arrow {
  top: 0;
  left: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.popover {
  position: absolute;
  top: 0;
  left: 0;
  z-index: 1060;
  display: none;
  max-width: 276px;
  padding: 1px;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 13px;
  background-color: #fff;
  background-clip: padding-box;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
  box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
}
.popover.top {
  margin-top: -10px;
}
.popover.right {
  margin-left: 10px;
}
.popover.bottom {
  margin-top: 10px;
}
.popover.left {
  margin-left: -10px;
}
.popover-title {
  margin: 0;
  padding: 8px 14px;
  font-size: 13px;
  background-color: #f7f7f7;
  border-bottom: 1px solid #ebebeb;
  border-radius: 2px 2px 0 0;
}
.popover-content {
  padding: 9px 14px;
}
.popover > .arrow,
.popover > .arrow:after {
  position: absolute;
  display: block;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.popover > .arrow {
  border-width: 11px;
}
.popover > .arrow:after {
  border-width: 10px;
  content: "";
}
.popover.top > .arrow {
  left: 50%;
  margin-left: -11px;
  border-bottom-width: 0;
  border-top-color: #999999;
  border-top-color: rgba(0, 0, 0, 0.25);
  bottom: -11px;
}
.popover.top > .arrow:after {
  content: " ";
  bottom: 1px;
  margin-left: -10px;
  border-bottom-width: 0;
  border-top-color: #fff;
}
.popover.right > .arrow {
  top: 50%;
  left: -11px;
  margin-top: -11px;
  border-left-width: 0;
  border-right-color: #999999;
  border-right-color: rgba(0, 0, 0, 0.25);
}
.popover.right > .arrow:after {
  content: " ";
  left: 1px;
  bottom: -10px;
  border-left-width: 0;
  border-right-color: #fff;
}
.popover.bottom > .arrow {
  left: 50%;
  margin-left: -11px;
  border-top-width: 0;
  border-bottom-color: #999999;
  border-bottom-color: rgba(0, 0, 0, 0.25);
  top: -11px;
}
.popover.bottom > .arrow:after {
  content: " ";
  top: 1px;
  margin-left: -10px;
  border-top-width: 0;
  border-bottom-color: #fff;
}
.popover.left > .arrow {
  top: 50%;
  right: -11px;
  margin-top: -11px;
  border-right-width: 0;
  border-left-color: #999999;
  border-left-color: rgba(0, 0, 0, 0.25);
}
.popover.left > .arrow:after {
  content: " ";
  right: 1px;
  border-right-width: 0;
  border-left-color: #fff;
  bottom: -10px;
}
.carousel {
  position: relative;
}
.carousel-inner {
  position: relative;
  overflow: hidden;
  width: 100%;
}
.carousel-inner > .item {
  display: none;
  position: relative;
  -webkit-transition: 0.6s ease-in-out left;
  -o-transition: 0.6s ease-in-out left;
  transition: 0.6s ease-in-out left;
}
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  line-height: 1;
}
@media all and (transform-3d), (-webkit-transform-3d) {
  .carousel-inner > .item {
    -webkit-transition: -webkit-transform 0.6s ease-in-out;
    -moz-transition: -moz-transform 0.6s ease-in-out;
    -o-transition: -o-transform 0.6s ease-in-out;
    transition: transform 0.6s ease-in-out;
    -webkit-backface-visibility: hidden;
    -moz-backface-visibility: hidden;
    backface-visibility: hidden;
    -webkit-perspective: 1000px;
    -moz-perspective: 1000px;
    perspective: 1000px;
  }
  .carousel-inner > .item.next,
  .carousel-inner > .item.active.right {
    -webkit-transform: translate3d(100%, 0, 0);
    transform: translate3d(100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.prev,
  .carousel-inner > .item.active.left {
    -webkit-transform: translate3d(-100%, 0, 0);
    transform: translate3d(-100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.next.left,
  .carousel-inner > .item.prev.right,
  .carousel-inner > .item.active {
    -webkit-transform: translate3d(0, 0, 0);
    transform: translate3d(0, 0, 0);
    left: 0;
  }
}
.carousel-inner > .active,
.carousel-inner > .next,
.carousel-inner > .prev {
  display: block;
}
.carousel-inner > .active {
  left: 0;
}
.carousel-inner > .next,
.carousel-inner > .prev {
  position: absolute;
  top: 0;
  width: 100%;
}
.carousel-inner > .next {
  left: 100%;
}
.carousel-inner > .prev {
  left: -100%;
}
.carousel-inner > .next.left,
.carousel-inner > .prev.right {
  left: 0;
}
.carousel-inner > .active.left {
  left: -100%;
}
.carousel-inner > .active.right {
  left: 100%;
}
.carousel-control {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  width: 15%;
  opacity: 0.5;
  filter: alpha(opacity=50);
  font-size: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
  background-color: rgba(0, 0, 0, 0);
}
.carousel-control.left {
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
}
.carousel-control.right {
  left: auto;
  right: 0;
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
}
.carousel-control:hover,
.carousel-control:focus {
  outline: 0;
  color: #fff;
  text-decoration: none;
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.carousel-control .icon-prev,
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-left,
.carousel-control .glyphicon-chevron-right {
  position: absolute;
  top: 50%;
  margin-top: -10px;
  z-index: 5;
  display: inline-block;
}
.carousel-control .icon-prev,
.carousel-control .glyphicon-chevron-left {
  left: 50%;
  margin-left: -10px;
}
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-right {
  right: 50%;
  margin-right: -10px;
}
.carousel-control .icon-prev,
.carousel-control .icon-next {
  width: 20px;
  height: 20px;
  line-height: 1;
  font-family: serif;
}
.carousel-control .icon-prev:before {
  content: '\2039';
}
.carousel-control .icon-next:before {
  content: '\203a';
}
.carousel-indicators {
  position: absolute;
  bottom: 10px;
  left: 50%;
  z-index: 15;
  width: 60%;
  margin-left: -30%;
  padding-left: 0;
  list-style: none;
  text-align: center;
}
.carousel-indicators li {
  display: inline-block;
  width: 10px;
  height: 10px;
  margin: 1px;
  text-indent: -999px;
  border: 1px solid #fff;
  border-radius: 10px;
  cursor: pointer;
  background-color: #000 \9;
  background-color: rgba(0, 0, 0, 0);
}
.carousel-indicators .active {
  margin: 0;
  width: 12px;
  height: 12px;
  background-color: #fff;
}
.carousel-caption {
  position: absolute;
  left: 15%;
  right: 15%;
  bottom: 20px;
  z-index: 10;
  padding-top: 20px;
  padding-bottom: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
}
.carousel-caption .btn {
  text-shadow: none;
}
@media screen and (min-width: 768px) {
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-prev,
  .carousel-control .icon-next {
    width: 30px;
    height: 30px;
    margin-top: -10px;
    font-size: 30px;
  }
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .icon-prev {
    margin-left: -10px;
  }
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-next {
    margin-right: -10px;
  }
  .carousel-caption {
    left: 20%;
    right: 20%;
    padding-bottom: 30px;
  }
  .carousel-indicators {
    bottom: 20px;
  }
}
.clearfix:before,
.clearfix:after,
.dl-horizontal dd:before,
.dl-horizontal dd:after,
.container:before,
.container:after,
.container-fluid:before,
.container-fluid:after,
.row:before,
.row:after,
.form-horizontal .form-group:before,
.form-horizontal .form-group:after,
.btn-toolbar:before,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:before,
.btn-group-vertical > .btn-group:after,
.nav:before,
.nav:after,
.navbar:before,
.navbar:after,
.navbar-header:before,
.navbar-header:after,
.navbar-collapse:before,
.navbar-collapse:after,
.pager:before,
.pager:after,
.panel-body:before,
.panel-body:after,
.modal-header:before,
.modal-header:after,
.modal-footer:before,
.modal-footer:after,
.item_buttons:before,
.item_buttons:after {
  content: " ";
  display: table;
}
.clearfix:after,
.dl-horizontal dd:after,
.container:after,
.container-fluid:after,
.row:after,
.form-horizontal .form-group:after,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:after,
.nav:after,
.navbar:after,
.navbar-header:after,
.navbar-collapse:after,
.pager:after,
.panel-body:after,
.modal-header:after,
.modal-footer:after,
.item_buttons:after {
  clear: both;
}
.center-block {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.pull-right {
  float: right !important;
}
.pull-left {
  float: left !important;
}
.hide {
  display: none !important;
}
.show {
  display: block !important;
}
.invisible {
  visibility: hidden;
}
.text-hide {
  font: 0/0 a;
  color: transparent;
  text-shadow: none;
  background-color: transparent;
  border: 0;
}
.hidden {
  display: none !important;
}
.affix {
  position: fixed;
}
@-ms-viewport {
  width: device-width;
}
.visible-xs,
.visible-sm,
.visible-md,
.visible-lg {
  display: none !important;
}
.visible-xs-block,
.visible-xs-inline,
.visible-xs-inline-block,
.visible-sm-block,
.visible-sm-inline,
.visible-sm-inline-block,
.visible-md-block,
.visible-md-inline,
.visible-md-inline-block,
.visible-lg-block,
.visible-lg-inline,
.visible-lg-inline-block {
  display: none !important;
}
@media (max-width: 767px) {
  .visible-xs {
    display: block !important;
  }
  table.visible-xs {
    display: table !important;
  }
  tr.visible-xs {
    display: table-row !important;
  }
  th.visible-xs,
  td.visible-xs {
    display: table-cell !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-block {
    display: block !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline {
    display: inline !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm {
    display: block !important;
  }
  table.visible-sm {
    display: table !important;
  }
  tr.visible-sm {
    display: table-row !important;
  }
  th.visible-sm,
  td.visible-sm {
    display: table-cell !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-block {
    display: block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline {
    display: inline !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md {
    display: block !important;
  }
  table.visible-md {
    display: table !important;
  }
  tr.visible-md {
    display: table-row !important;
  }
  th.visible-md,
  td.visible-md {
    display: table-cell !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-block {
    display: block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline {
    display: inline !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg {
    display: block !important;
  }
  table.visible-lg {
    display: table !important;
  }
  tr.visible-lg {
    display: table-row !important;
  }
  th.visible-lg,
  td.visible-lg {
    display: table-cell !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-block {
    display: block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline {
    display: inline !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline-block {
    display: inline-block !important;
  }
}
@media (max-width: 767px) {
  .hidden-xs {
    display: none !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .hidden-sm {
    display: none !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .hidden-md {
    display: none !important;
  }
}
@media (min-width: 1200px) {
  .hidden-lg {
    display: none !important;
  }
}
.visible-print {
  display: none !important;
}
@media print {
  .visible-print {
    display: block !important;
  }
  table.visible-print {
    display: table !important;
  }
  tr.visible-print {
    display: table-row !important;
  }
  th.visible-print,
  td.visible-print {
    display: table-cell !important;
  }
}
.visible-print-block {
  display: none !important;
}
@media print {
  .visible-print-block {
    display: block !important;
  }
}
.visible-print-inline {
  display: none !important;
}
@media print {
  .visible-print-inline {
    display: inline !important;
  }
}
.visible-print-inline-block {
  display: none !important;
}
@media print {
  .visible-print-inline-block {
    display: inline-block !important;
  }
}
@media print {
  .hidden-print {
    display: none !important;
  }
}
/*!
*
* Font Awesome
*
*/
/*!
 *  Font Awesome 4.7.0 by @davegandy - http://fontawesome.io - @fontawesome
 *  License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
 */
/* FONT PATH
 * -------------------------- */
@font-face {
  font-family: 'FontAwesome';
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.7.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.7.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff2?v=4.7.0') format('woff2'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.7.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.7.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.7.0#fontawesomeregular') format('svg');
  font-weight: normal;
  font-style: normal;
}
.fa {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
/* makes the font 33% larger relative to the icon container */
.fa-lg {
  font-size: 1.33333333em;
  line-height: 0.75em;
  vertical-align: -15%;
}
.fa-2x {
  font-size: 2em;
}
.fa-3x {
  font-size: 3em;
}
.fa-4x {
  font-size: 4em;
}
.fa-5x {
  font-size: 5em;
}
.fa-fw {
  width: 1.28571429em;
  text-align: center;
}
.fa-ul {
  padding-left: 0;
  margin-left: 2.14285714em;
  list-style-type: none;
}
.fa-ul > li {
  position: relative;
}
.fa-li {
  position: absolute;
  left: -2.14285714em;
  width: 2.14285714em;
  top: 0.14285714em;
  text-align: center;
}
.fa-li.fa-lg {
  left: -1.85714286em;
}
.fa-border {
  padding: .2em .25em .15em;
  border: solid 0.08em #eee;
  border-radius: .1em;
}
.fa-pull-left {
  float: left;
}
.fa-pull-right {
  float: right;
}
.fa.fa-pull-left {
  margin-right: .3em;
}
.fa.fa-pull-right {
  margin-left: .3em;
}
/* Deprecated as of 4.4.0 */
.pull-right {
  float: right;
}
.pull-left {
  float: left;
}
.fa.pull-left {
  margin-right: .3em;
}
.fa.pull-right {
  margin-left: .3em;
}
.fa-spin {
  -webkit-animation: fa-spin 2s infinite linear;
  animation: fa-spin 2s infinite linear;
}
.fa-pulse {
  -webkit-animation: fa-spin 1s infinite steps(8);
  animation: fa-spin 1s infinite steps(8);
}
@-webkit-keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
@keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
.fa-rotate-90 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=1)";
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2)";
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=3)";
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1)";
  -webkit-transform: scale(-1, 1);
  -ms-transform: scale(-1, 1);
  transform: scale(-1, 1);
}
.fa-flip-vertical {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1)";
  -webkit-transform: scale(1, -1);
  -ms-transform: scale(1, -1);
  transform: scale(1, -1);
}
:root .fa-rotate-90,
:root .fa-rotate-180,
:root .fa-rotate-270,
:root .fa-flip-horizontal,
:root .fa-flip-vertical {
  filter: none;
}
.fa-stack {
  position: relative;
  display: inline-block;
  width: 2em;
  height: 2em;
  line-height: 2em;
  vertical-align: middle;
}
.fa-stack-1x,
.fa-stack-2x {
  position: absolute;
  left: 0;
  width: 100%;
  text-align: center;
}
.fa-stack-1x {
  line-height: inherit;
}
.fa-stack-2x {
  font-size: 2em;
}
.fa-inverse {
  color: #fff;
}
/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
   readers do not read off random characters that represent icons */
.fa-glass:before {
  content: "\f000";
}
.fa-music:before {
  content: "\f001";
}
.fa-search:before {
  content: "\f002";
}
.fa-envelope-o:before {
  content: "\f003";
}
.fa-heart:before {
  content: "\f004";
}
.fa-star:before {
  content: "\f005";
}
.fa-star-o:before {
  content: "\f006";
}
.fa-user:before {
  content: "\f007";
}
.fa-film:before {
  content: "\f008";
}
.fa-th-large:before {
  content: "\f009";
}
.fa-th:before {
  content: "\f00a";
}
.fa-th-list:before {
  content: "\f00b";
}
.fa-check:before {
  content: "\f00c";
}
.fa-remove:before,
.fa-close:before,
.fa-times:before {
  content: "\f00d";
}
.fa-search-plus:before {
  content: "\f00e";
}
.fa-search-minus:before {
  content: "\f010";
}
.fa-power-off:before {
  content: "\f011";
}
.fa-signal:before {
  content: "\f012";
}
.fa-gear:before,
.fa-cog:before {
  content: "\f013";
}
.fa-trash-o:before {
  content: "\f014";
}
.fa-home:before {
  content: "\f015";
}
.fa-file-o:before {
  content: "\f016";
}
.fa-clock-o:before {
  content: "\f017";
}
.fa-road:before {
  content: "\f018";
}
.fa-download:before {
  content: "\f019";
}
.fa-arrow-circle-o-down:before {
  content: "\f01a";
}
.fa-arrow-circle-o-up:before {
  content: "\f01b";
}
.fa-inbox:before {
  content: "\f01c";
}
.fa-play-circle-o:before {
  content: "\f01d";
}
.fa-rotate-right:before,
.fa-repeat:before {
  content: "\f01e";
}
.fa-refresh:before {
  content: "\f021";
}
.fa-list-alt:before {
  content: "\f022";
}
.fa-lock:before {
  content: "\f023";
}
.fa-flag:before {
  content: "\f024";
}
.fa-headphones:before {
  content: "\f025";
}
.fa-volume-off:before {
  content: "\f026";
}
.fa-volume-down:before {
  content: "\f027";
}
.fa-volume-up:before {
  content: "\f028";
}
.fa-qrcode:before {
  content: "\f029";
}
.fa-barcode:before {
  content: "\f02a";
}
.fa-tag:before {
  content: "\f02b";
}
.fa-tags:before {
  content: "\f02c";
}
.fa-book:before {
  content: "\f02d";
}
.fa-bookmark:before {
  content: "\f02e";
}
.fa-print:before {
  content: "\f02f";
}
.fa-camera:before {
  content: "\f030";
}
.fa-font:before {
  content: "\f031";
}
.fa-bold:before {
  content: "\f032";
}
.fa-italic:before {
  content: "\f033";
}
.fa-text-height:before {
  content: "\f034";
}
.fa-text-width:before {
  content: "\f035";
}
.fa-align-left:before {
  content: "\f036";
}
.fa-align-center:before {
  content: "\f037";
}
.fa-align-right:before {
  content: "\f038";
}
.fa-align-justify:before {
  content: "\f039";
}
.fa-list:before {
  content: "\f03a";
}
.fa-dedent:before,
.fa-outdent:before {
  content: "\f03b";
}
.fa-indent:before {
  content: "\f03c";
}
.fa-video-camera:before {
  content: "\f03d";
}
.fa-photo:before,
.fa-image:before,
.fa-picture-o:before {
  content: "\f03e";
}
.fa-pencil:before {
  content: "\f040";
}
.fa-map-marker:before {
  content: "\f041";
}
.fa-adjust:before {
  content: "\f042";
}
.fa-tint:before {
  content: "\f043";
}
.fa-edit:before,
.fa-pencil-square-o:before {
  content: "\f044";
}
.fa-share-square-o:before {
  content: "\f045";
}
.fa-check-square-o:before {
  content: "\f046";
}
.fa-arrows:before {
  content: "\f047";
}
.fa-step-backward:before {
  content: "\f048";
}
.fa-fast-backward:before {
  content: "\f049";
}
.fa-backward:before {
  content: "\f04a";
}
.fa-play:before {
  content: "\f04b";
}
.fa-pause:before {
  content: "\f04c";
}
.fa-stop:before {
  content: "\f04d";
}
.fa-forward:before {
  content: "\f04e";
}
.fa-fast-forward:before {
  content: "\f050";
}
.fa-step-forward:before {
  content: "\f051";
}
.fa-eject:before {
  content: "\f052";
}
.fa-chevron-left:before {
  content: "\f053";
}
.fa-chevron-right:before {
  content: "\f054";
}
.fa-plus-circle:before {
  content: "\f055";
}
.fa-minus-circle:before {
  content: "\f056";
}
.fa-times-circle:before {
  content: "\f057";
}
.fa-check-circle:before {
  content: "\f058";
}
.fa-question-circle:before {
  content: "\f059";
}
.fa-info-circle:before {
  content: "\f05a";
}
.fa-crosshairs:before {
  content: "\f05b";
}
.fa-times-circle-o:before {
  content: "\f05c";
}
.fa-check-circle-o:before {
  content: "\f05d";
}
.fa-ban:before {
  content: "\f05e";
}
.fa-arrow-left:before {
  content: "\f060";
}
.fa-arrow-right:before {
  content: "\f061";
}
.fa-arrow-up:before {
  content: "\f062";
}
.fa-arrow-down:before {
  content: "\f063";
}
.fa-mail-forward:before,
.fa-share:before {
  content: "\f064";
}
.fa-expand:before {
  content: "\f065";
}
.fa-compress:before {
  content: "\f066";
}
.fa-plus:before {
  content: "\f067";
}
.fa-minus:before {
  content: "\f068";
}
.fa-asterisk:before {
  content: "\f069";
}
.fa-exclamation-circle:before {
  content: "\f06a";
}
.fa-gift:before {
  content: "\f06b";
}
.fa-leaf:before {
  content: "\f06c";
}
.fa-fire:before {
  content: "\f06d";
}
.fa-eye:before {
  content: "\f06e";
}
.fa-eye-slash:before {
  content: "\f070";
}
.fa-warning:before,
.fa-exclamation-triangle:before {
  content: "\f071";
}
.fa-plane:before {
  content: "\f072";
}
.fa-calendar:before {
  content: "\f073";
}
.fa-random:before {
  content: "\f074";
}
.fa-comment:before {
  content: "\f075";
}
.fa-magnet:before {
  content: "\f076";
}
.fa-chevron-up:before {
  content: "\f077";
}
.fa-chevron-down:before {
  content: "\f078";
}
.fa-retweet:before {
  content: "\f079";
}
.fa-shopping-cart:before {
  content: "\f07a";
}
.fa-folder:before {
  content: "\f07b";
}
.fa-folder-open:before {
  content: "\f07c";
}
.fa-arrows-v:before {
  content: "\f07d";
}
.fa-arrows-h:before {
  content: "\f07e";
}
.fa-bar-chart-o:before,
.fa-bar-chart:before {
  content: "\f080";
}
.fa-twitter-square:before {
  content: "\f081";
}
.fa-facebook-square:before {
  content: "\f082";
}
.fa-camera-retro:before {
  content: "\f083";
}
.fa-key:before {
  content: "\f084";
}
.fa-gears:before,
.fa-cogs:before {
  content: "\f085";
}
.fa-comments:before {
  content: "\f086";
}
.fa-thumbs-o-up:before {
  content: "\f087";
}
.fa-thumbs-o-down:before {
  content: "\f088";
}
.fa-star-half:before {
  content: "\f089";
}
.fa-heart-o:before {
  content: "\f08a";
}
.fa-sign-out:before {
  content: "\f08b";
}
.fa-linkedin-square:before {
  content: "\f08c";
}
.fa-thumb-tack:before {
  content: "\f08d";
}
.fa-external-link:before {
  content: "\f08e";
}
.fa-sign-in:before {
  content: "\f090";
}
.fa-trophy:before {
  content: "\f091";
}
.fa-github-square:before {
  content: "\f092";
}
.fa-upload:before {
  content: "\f093";
}
.fa-lemon-o:before {
  content: "\f094";
}
.fa-phone:before {
  content: "\f095";
}
.fa-square-o:before {
  content: "\f096";
}
.fa-bookmark-o:before {
  content: "\f097";
}
.fa-phone-square:before {
  content: "\f098";
}
.fa-twitter:before {
  content: "\f099";
}
.fa-facebook-f:before,
.fa-facebook:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.fa-feed:before,
.fa-rss:before {
  content: "\f09e";
}
.fa-hdd-o:before {
  content: "\f0a0";
}
.fa-bullhorn:before {
  content: "\f0a1";
}
.fa-bell:before {
  content: "\f0f3";
}
.fa-certificate:before {
  content: "\f0a3";
}
.fa-hand-o-right:before {
  content: "\f0a4";
}
.fa-hand-o-left:before {
  content: "\f0a5";
}
.fa-hand-o-up:before {
  content: "\f0a6";
}
.fa-hand-o-down:before {
  content: "\f0a7";
}
.fa-arrow-circle-left:before {
  content: "\f0a8";
}
.fa-arrow-circle-right:before {
  content: "\f0a9";
}
.fa-arrow-circle-up:before {
  content: "\f0aa";
}
.fa-arrow-circle-down:before {
  content: "\f0ab";
}
.fa-globe:before {
  content: "\f0ac";
}
.fa-wrench:before {
  content: "\f0ad";
}
.fa-tasks:before {
  content: "\f0ae";
}
.fa-filter:before {
  content: "\f0b0";
}
.fa-briefcase:before {
  content: "\f0b1";
}
.fa-arrows-alt:before {
  content: "\f0b2";
}
.fa-group:before,
.fa-users:before {
  content: "\f0c0";
}
.fa-chain:before,
.fa-link:before {
  content: "\f0c1";
}
.fa-cloud:before {
  content: "\f0c2";
}
.fa-flask:before {
  content: "\f0c3";
}
.fa-cut:before,
.fa-scissors:before {
  content: "\f0c4";
}
.fa-copy:before,
.fa-files-o:before {
  content: "\f0c5";
}
.fa-paperclip:before {
  content: "\f0c6";
}
.fa-save:before,
.fa-floppy-o:before {
  content: "\f0c7";
}
.fa-square:before {
  content: "\f0c8";
}
.fa-navicon:before,
.fa-reorder:before,
.fa-bars:before {
  content: "\f0c9";
}
.fa-list-ul:before {
  content: "\f0ca";
}
.fa-list-ol:before {
  content: "\f0cb";
}
.fa-strikethrough:before {
  content: "\f0cc";
}
.fa-underline:before {
  content: "\f0cd";
}
.fa-table:before {
  content: "\f0ce";
}
.fa-magic:before {
  content: "\f0d0";
}
.fa-truck:before {
  content: "\f0d1";
}
.fa-pinterest:before {
  content: "\f0d2";
}
.fa-pinterest-square:before {
  content: "\f0d3";
}
.fa-google-plus-square:before {
  content: "\f0d4";
}
.fa-google-plus:before {
  content: "\f0d5";
}
.fa-money:before {
  content: "\f0d6";
}
.fa-caret-down:before {
  content: "\f0d7";
}
.fa-caret-up:before {
  content: "\f0d8";
}
.fa-caret-left:before {
  content: "\f0d9";
}
.fa-caret-right:before {
  content: "\f0da";
}
.fa-columns:before {
  content: "\f0db";
}
.fa-unsorted:before,
.fa-sort:before {
  content: "\f0dc";
}
.fa-sort-down:before,
.fa-sort-desc:before {
  content: "\f0dd";
}
.fa-sort-up:before,
.fa-sort-asc:before {
  content: "\f0de";
}
.fa-envelope:before {
  content: "\f0e0";
}
.fa-linkedin:before {
  content: "\f0e1";
}
.fa-rotate-left:before,
.fa-undo:before {
  content: "\f0e2";
}
.fa-legal:before,
.fa-gavel:before {
  content: "\f0e3";
}
.fa-dashboard:before,
.fa-tachometer:before {
  content: "\f0e4";
}
.fa-comment-o:before {
  content: "\f0e5";
}
.fa-comments-o:before {
  content: "\f0e6";
}
.fa-flash:before,
.fa-bolt:before {
  content: "\f0e7";
}
.fa-sitemap:before {
  content: "\f0e8";
}
.fa-umbrella:before {
  content: "\f0e9";
}
.fa-paste:before,
.fa-clipboard:before {
  content: "\f0ea";
}
.fa-lightbulb-o:before {
  content: "\f0eb";
}
.fa-exchange:before {
  content: "\f0ec";
}
.fa-cloud-download:before {
  content: "\f0ed";
}
.fa-cloud-upload:before {
  content: "\f0ee";
}
.fa-user-md:before {
  content: "\f0f0";
}
.fa-stethoscope:before {
  content: "\f0f1";
}
.fa-suitcase:before {
  content: "\f0f2";
}
.fa-bell-o:before {
  content: "\f0a2";
}
.fa-coffee:before {
  content: "\f0f4";
}
.fa-cutlery:before {
  content: "\f0f5";
}
.fa-file-text-o:before {
  content: "\f0f6";
}
.fa-building-o:before {
  content: "\f0f7";
}
.fa-hospital-o:before {
  content: "\f0f8";
}
.fa-ambulance:before {
  content: "\f0f9";
}
.fa-medkit:before {
  content: "\f0fa";
}
.fa-fighter-jet:before {
  content: "\f0fb";
}
.fa-beer:before {
  content: "\f0fc";
}
.fa-h-square:before {
  content: "\f0fd";
}
.fa-plus-square:before {
  content: "\f0fe";
}
.fa-angle-double-left:before {
  content: "\f100";
}
.fa-angle-double-right:before {
  content: "\f101";
}
.fa-angle-double-up:before {
  content: "\f102";
}
.fa-angle-double-down:before {
  content: "\f103";
}
.fa-angle-left:before {
  content: "\f104";
}
.fa-angle-right:before {
  content: "\f105";
}
.fa-angle-up:before {
  content: "\f106";
}
.fa-angle-down:before {
  content: "\f107";
}
.fa-desktop:before {
  content: "\f108";
}
.fa-laptop:before {
  content: "\f109";
}
.fa-tablet:before {
  content: "\f10a";
}
.fa-mobile-phone:before,
.fa-mobile:before {
  content: "\f10b";
}
.fa-circle-o:before {
  content: "\f10c";
}
.fa-quote-left:before {
  content: "\f10d";
}
.fa-quote-right:before {
  content: "\f10e";
}
.fa-spinner:before {
  content: "\f110";
}
.fa-circle:before {
  content: "\f111";
}
.fa-mail-reply:before,
.fa-reply:before {
  content: "\f112";
}
.fa-github-alt:before {
  content: "\f113";
}
.fa-folder-o:before {
  content: "\f114";
}
.fa-folder-open-o:before {
  content: "\f115";
}
.fa-smile-o:before {
  content: "\f118";
}
.fa-frown-o:before {
  content: "\f119";
}
.fa-meh-o:before {
  content: "\f11a";
}
.fa-gamepad:before {
  content: "\f11b";
}
.fa-keyboard-o:before {
  content: "\f11c";
}
.fa-flag-o:before {
  content: "\f11d";
}
.fa-flag-checkered:before {
  content: "\f11e";
}
.fa-terminal:before {
  content: "\f120";
}
.fa-code:before {
  content: "\f121";
}
.fa-mail-reply-all:before,
.fa-reply-all:before {
  content: "\f122";
}
.fa-star-half-empty:before,
.fa-star-half-full:before,
.fa-star-half-o:before {
  content: "\f123";
}
.fa-location-arrow:before {
  content: "\f124";
}
.fa-crop:before {
  content: "\f125";
}
.fa-code-fork:before {
  content: "\f126";
}
.fa-unlink:before,
.fa-chain-broken:before {
  content: "\f127";
}
.fa-question:before {
  content: "\f128";
}
.fa-info:before {
  content: "\f129";
}
.fa-exclamation:before {
  content: "\f12a";
}
.fa-superscript:before {
  content: "\f12b";
}
.fa-subscript:before {
  content: "\f12c";
}
.fa-eraser:before {
  content: "\f12d";
}
.fa-puzzle-piece:before {
  content: "\f12e";
}
.fa-microphone:before {
  content: "\f130";
}
.fa-microphone-slash:before {
  content: "\f131";
}
.fa-shield:before {
  content: "\f132";
}
.fa-calendar-o:before {
  content: "\f133";
}
.fa-fire-extinguisher:before {
  content: "\f134";
}
.fa-rocket:before {
  content: "\f135";
}
.fa-maxcdn:before {
  content: "\f136";
}
.fa-chevron-circle-left:before {
  content: "\f137";
}
.fa-chevron-circle-right:before {
  content: "\f138";
}
.fa-chevron-circle-up:before {
  content: "\f139";
}
.fa-chevron-circle-down:before {
  content: "\f13a";
}
.fa-html5:before {
  content: "\f13b";
}
.fa-css3:before {
  content: "\f13c";
}
.fa-anchor:before {
  content: "\f13d";
}
.fa-unlock-alt:before {
  content: "\f13e";
}
.fa-bullseye:before {
  content: "\f140";
}
.fa-ellipsis-h:before {
  content: "\f141";
}
.fa-ellipsis-v:before {
  content: "\f142";
}
.fa-rss-square:before {
  content: "\f143";
}
.fa-play-circle:before {
  content: "\f144";
}
.fa-ticket:before {
  content: "\f145";
}
.fa-minus-square:before {
  content: "\f146";
}
.fa-minus-square-o:before {
  content: "\f147";
}
.fa-level-up:before {
  content: "\f148";
}
.fa-level-down:before {
  content: "\f149";
}
.fa-check-square:before {
  content: "\f14a";
}
.fa-pencil-square:before {
  content: "\f14b";
}
.fa-external-link-square:before {
  content: "\f14c";
}
.fa-share-square:before {
  content: "\f14d";
}
.fa-compass:before {
  content: "\f14e";
}
.fa-toggle-down:before,
.fa-caret-square-o-down:before {
  content: "\f150";
}
.fa-toggle-up:before,
.fa-caret-square-o-up:before {
  content: "\f151";
}
.fa-toggle-right:before,
.fa-caret-square-o-right:before {
  content: "\f152";
}
.fa-euro:before,
.fa-eur:before {
  content: "\f153";
}
.fa-gbp:before {
  content: "\f154";
}
.fa-dollar:before,
.fa-usd:before {
  content: "\f155";
}
.fa-rupee:before,
.fa-inr:before {
  content: "\f156";
}
.fa-cny:before,
.fa-rmb:before,
.fa-yen:before,
.fa-jpy:before {
  content: "\f157";
}
.fa-ruble:before,
.fa-rouble:before,
.fa-rub:before {
  content: "\f158";
}
.fa-won:before,
.fa-krw:before {
  content: "\f159";
}
.fa-bitcoin:before,
.fa-btc:before {
  content: "\f15a";
}
.fa-file:before {
  content: "\f15b";
}
.fa-file-text:before {
  content: "\f15c";
}
.fa-sort-alpha-asc:before {
  content: "\f15d";
}
.fa-sort-alpha-desc:before {
  content: "\f15e";
}
.fa-sort-amount-asc:before {
  content: "\f160";
}
.fa-sort-amount-desc:before {
  content: "\f161";
}
.fa-sort-numeric-asc:before {
  content: "\f162";
}
.fa-sort-numeric-desc:before {
  content: "\f163";
}
.fa-thumbs-up:before {
  content: "\f164";
}
.fa-thumbs-down:before {
  content: "\f165";
}
.fa-youtube-square:before {
  content: "\f166";
}
.fa-youtube:before {
  content: "\f167";
}
.fa-xing:before {
  content: "\f168";
}
.fa-xing-square:before {
  content: "\f169";
}
.fa-youtube-play:before {
  content: "\f16a";
}
.fa-dropbox:before {
  content: "\f16b";
}
.fa-stack-overflow:before {
  content: "\f16c";
}
.fa-instagram:before {
  content: "\f16d";
}
.fa-flickr:before {
  content: "\f16e";
}
.fa-adn:before {
  content: "\f170";
}
.fa-bitbucket:before {
  content: "\f171";
}
.fa-bitbucket-square:before {
  content: "\f172";
}
.fa-tumblr:before {
  content: "\f173";
}
.fa-tumblr-square:before {
  content: "\f174";
}
.fa-long-arrow-down:before {
  content: "\f175";
}
.fa-long-arrow-up:before {
  content: "\f176";
}
.fa-long-arrow-left:before {
  content: "\f177";
}
.fa-long-arrow-right:before {
  content: "\f178";
}
.fa-apple:before {
  content: "\f179";
}
.fa-windows:before {
  content: "\f17a";
}
.fa-android:before {
  content: "\f17b";
}
.fa-linux:before {
  content: "\f17c";
}
.fa-dribbble:before {
  content: "\f17d";
}
.fa-skype:before {
  content: "\f17e";
}
.fa-foursquare:before {
  content: "\f180";
}
.fa-trello:before {
  content: "\f181";
}
.fa-female:before {
  content: "\f182";
}
.fa-male:before {
  content: "\f183";
}
.fa-gittip:before,
.fa-gratipay:before {
  content: "\f184";
}
.fa-sun-o:before {
  content: "\f185";
}
.fa-moon-o:before {
  content: "\f186";
}
.fa-archive:before {
  content: "\f187";
}
.fa-bug:before {
  content: "\f188";
}
.fa-vk:before {
  content: "\f189";
}
.fa-weibo:before {
  content: "\f18a";
}
.fa-renren:before {
  content: "\f18b";
}
.fa-pagelines:before {
  content: "\f18c";
}
.fa-stack-exchange:before {
  content: "\f18d";
}
.fa-arrow-circle-o-right:before {
  content: "\f18e";
}
.fa-arrow-circle-o-left:before {
  content: "\f190";
}
.fa-toggle-left:before,
.fa-caret-square-o-left:before {
  content: "\f191";
}
.fa-dot-circle-o:before {
  content: "\f192";
}
.fa-wheelchair:before {
  content: "\f193";
}
.fa-vimeo-square:before {
  content: "\f194";
}
.fa-turkish-lira:before,
.fa-try:before {
  content: "\f195";
}
.fa-plus-square-o:before {
  content: "\f196";
}
.fa-space-shuttle:before {
  content: "\f197";
}
.fa-slack:before {
  content: "\f198";
}
.fa-envelope-square:before {
  content: "\f199";
}
.fa-wordpress:before {
  content: "\f19a";
}
.fa-openid:before {
  content: "\f19b";
}
.fa-institution:before,
.fa-bank:before,
.fa-university:before {
  content: "\f19c";
}
.fa-mortar-board:before,
.fa-graduation-cap:before {
  content: "\f19d";
}
.fa-yahoo:before {
  content: "\f19e";
}
.fa-google:before {
  content: "\f1a0";
}
.fa-reddit:before {
  content: "\f1a1";
}
.fa-reddit-square:before {
  content: "\f1a2";
}
.fa-stumbleupon-circle:before {
  content: "\f1a3";
}
.fa-stumbleupon:before {
  content: "\f1a4";
}
.fa-delicious:before {
  content: "\f1a5";
}
.fa-digg:before {
  content: "\f1a6";
}
.fa-pied-piper-pp:before {
  content: "\f1a7";
}
.fa-pied-piper-alt:before {
  content: "\f1a8";
}
.fa-drupal:before {
  content: "\f1a9";
}
.fa-joomla:before {
  content: "\f1aa";
}
.fa-language:before {
  content: "\f1ab";
}
.fa-fax:before {
  content: "\f1ac";
}
.fa-building:before {
  content: "\f1ad";
}
.fa-child:before {
  content: "\f1ae";
}
.fa-paw:before {
  content: "\f1b0";
}
.fa-spoon:before {
  content: "\f1b1";
}
.fa-cube:before {
  content: "\f1b2";
}
.fa-cubes:before {
  content: "\f1b3";
}
.fa-behance:before {
  content: "\f1b4";
}
.fa-behance-square:before {
  content: "\f1b5";
}
.fa-steam:before {
  content: "\f1b6";
}
.fa-steam-square:before {
  content: "\f1b7";
}
.fa-recycle:before {
  content: "\f1b8";
}
.fa-automobile:before,
.fa-car:before {
  content: "\f1b9";
}
.fa-cab:before,
.fa-taxi:before {
  content: "\f1ba";
}
.fa-tree:before {
  content: "\f1bb";
}
.fa-spotify:before {
  content: "\f1bc";
}
.fa-deviantart:before {
  content: "\f1bd";
}
.fa-soundcloud:before {
  content: "\f1be";
}
.fa-database:before {
  content: "\f1c0";
}
.fa-file-pdf-o:before {
  content: "\f1c1";
}
.fa-file-word-o:before {
  content: "\f1c2";
}
.fa-file-excel-o:before {
  content: "\f1c3";
}
.fa-file-powerpoint-o:before {
  content: "\f1c4";
}
.fa-file-photo-o:before,
.fa-file-picture-o:before,
.fa-file-image-o:before {
  content: "\f1c5";
}
.fa-file-zip-o:before,
.fa-file-archive-o:before {
  content: "\f1c6";
}
.fa-file-sound-o:before,
.fa-file-audio-o:before {
  content: "\f1c7";
}
.fa-file-movie-o:before,
.fa-file-video-o:before {
  content: "\f1c8";
}
.fa-file-code-o:before {
  content: "\f1c9";
}
.fa-vine:before {
  content: "\f1ca";
}
.fa-codepen:before {
  content: "\f1cb";
}
.fa-jsfiddle:before {
  content: "\f1cc";
}
.fa-life-bouy:before,
.fa-life-buoy:before,
.fa-life-saver:before,
.fa-support:before,
.fa-life-ring:before {
  content: "\f1cd";
}
.fa-circle-o-notch:before {
  content: "\f1ce";
}
.fa-ra:before,
.fa-resistance:before,
.fa-rebel:before {
  content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
  content: "\f1d1";
}
.fa-git-square:before {
  content: "\f1d2";
}
.fa-git:before {
  content: "\f1d3";
}
.fa-y-combinator-square:before,
.fa-yc-square:before,
.fa-hacker-news:before {
  content: "\f1d4";
}
.fa-tencent-weibo:before {
  content: "\f1d5";
}
.fa-qq:before {
  content: "\f1d6";
}
.fa-wechat:before,
.fa-weixin:before {
  content: "\f1d7";
}
.fa-send:before,
.fa-paper-plane:before {
  content: "\f1d8";
}
.fa-send-o:before,
.fa-paper-plane-o:before {
  content: "\f1d9";
}
.fa-history:before {
  content: "\f1da";
}
.fa-circle-thin:before {
  content: "\f1db";
}
.fa-header:before {
  content: "\f1dc";
}
.fa-paragraph:before {
  content: "\f1dd";
}
.fa-sliders:before {
  content: "\f1de";
}
.fa-share-alt:before {
  content: "\f1e0";
}
.fa-share-alt-square:before {
  content: "\f1e1";
}
.fa-bomb:before {
  content: "\f1e2";
}
.fa-soccer-ball-o:before,
.fa-futbol-o:before {
  content: "\f1e3";
}
.fa-tty:before {
  content: "\f1e4";
}
.fa-binoculars:before {
  content: "\f1e5";
}
.fa-plug:before {
  content: "\f1e6";
}
.fa-slideshare:before {
  content: "\f1e7";
}
.fa-twitch:before {
  content: "\f1e8";
}
.fa-yelp:before {
  content: "\f1e9";
}
.fa-newspaper-o:before {
  content: "\f1ea";
}
.fa-wifi:before {
  content: "\f1eb";
}
.fa-calculator:before {
  content: "\f1ec";
}
.fa-paypal:before {
  content: "\f1ed";
}
.fa-google-wallet:before {
  content: "\f1ee";
}
.fa-cc-visa:before {
  content: "\f1f0";
}
.fa-cc-mastercard:before {
  content: "\f1f1";
}
.fa-cc-discover:before {
  content: "\f1f2";
}
.fa-cc-amex:before {
  content: "\f1f3";
}
.fa-cc-paypal:before {
  content: "\f1f4";
}
.fa-cc-stripe:before {
  content: "\f1f5";
}
.fa-bell-slash:before {
  content: "\f1f6";
}
.fa-bell-slash-o:before {
  content: "\f1f7";
}
.fa-trash:before {
  content: "\f1f8";
}
.fa-copyright:before {
  content: "\f1f9";
}
.fa-at:before {
  content: "\f1fa";
}
.fa-eyedropper:before {
  content: "\f1fb";
}
.fa-paint-brush:before {
  content: "\f1fc";
}
.fa-birthday-cake:before {
  content: "\f1fd";
}
.fa-area-chart:before {
  content: "\f1fe";
}
.fa-pie-chart:before {
  content: "\f200";
}
.fa-line-chart:before {
  content: "\f201";
}
.fa-lastfm:before {
  content: "\f202";
}
.fa-lastfm-square:before {
  content: "\f203";
}
.fa-toggle-off:before {
  content: "\f204";
}
.fa-toggle-on:before {
  content: "\f205";
}
.fa-bicycle:before {
  content: "\f206";
}
.fa-bus:before {
  content: "\f207";
}
.fa-ioxhost:before {
  content: "\f208";
}
.fa-angellist:before {
  content: "\f209";
}
.fa-cc:before {
  content: "\f20a";
}
.fa-shekel:before,
.fa-sheqel:before,
.fa-ils:before {
  content: "\f20b";
}
.fa-meanpath:before {
  content: "\f20c";
}
.fa-buysellads:before {
  content: "\f20d";
}
.fa-connectdevelop:before {
  content: "\f20e";
}
.fa-dashcube:before {
  content: "\f210";
}
.fa-forumbee:before {
  content: "\f211";
}
.fa-leanpub:before {
  content: "\f212";
}
.fa-sellsy:before {
  content: "\f213";
}
.fa-shirtsinbulk:before {
  content: "\f214";
}
.fa-simplybuilt:before {
  content: "\f215";
}
.fa-skyatlas:before {
  content: "\f216";
}
.fa-cart-plus:before {
  content: "\f217";
}
.fa-cart-arrow-down:before {
  content: "\f218";
}
.fa-diamond:before {
  content: "\f219";
}
.fa-ship:before {
  content: "\f21a";
}
.fa-user-secret:before {
  content: "\f21b";
}
.fa-motorcycle:before {
  content: "\f21c";
}
.fa-street-view:before {
  content: "\f21d";
}
.fa-heartbeat:before {
  content: "\f21e";
}
.fa-venus:before {
  content: "\f221";
}
.fa-mars:before {
  content: "\f222";
}
.fa-mercury:before {
  content: "\f223";
}
.fa-intersex:before,
.fa-transgender:before {
  content: "\f224";
}
.fa-transgender-alt:before {
  content: "\f225";
}
.fa-venus-double:before {
  content: "\f226";
}
.fa-mars-double:before {
  content: "\f227";
}
.fa-venus-mars:before {
  content: "\f228";
}
.fa-mars-stroke:before {
  content: "\f229";
}
.fa-mars-stroke-v:before {
  content: "\f22a";
}
.fa-mars-stroke-h:before {
  content: "\f22b";
}
.fa-neuter:before {
  content: "\f22c";
}
.fa-genderless:before {
  content: "\f22d";
}
.fa-facebook-official:before {
  content: "\f230";
}
.fa-pinterest-p:before {
  content: "\f231";
}
.fa-whatsapp:before {
  content: "\f232";
}
.fa-server:before {
  content: "\f233";
}
.fa-user-plus:before {
  content: "\f234";
}
.fa-user-times:before {
  content: "\f235";
}
.fa-hotel:before,
.fa-bed:before {
  content: "\f236";
}
.fa-viacoin:before {
  content: "\f237";
}
.fa-train:before {
  content: "\f238";
}
.fa-subway:before {
  content: "\f239";
}
.fa-medium:before {
  content: "\f23a";
}
.fa-yc:before,
.fa-y-combinator:before {
  content: "\f23b";
}
.fa-optin-monster:before {
  content: "\f23c";
}
.fa-opencart:before {
  content: "\f23d";
}
.fa-expeditedssl:before {
  content: "\f23e";
}
.fa-battery-4:before,
.fa-battery:before,
.fa-battery-full:before {
  content: "\f240";
}
.fa-battery-3:before,
.fa-battery-three-quarters:before {
  content: "\f241";
}
.fa-battery-2:before,
.fa-battery-half:before {
  content: "\f242";
}
.fa-battery-1:before,
.fa-battery-quarter:before {
  content: "\f243";
}
.fa-battery-0:before,
.fa-battery-empty:before {
  content: "\f244";
}
.fa-mouse-pointer:before {
  content: "\f245";
}
.fa-i-cursor:before {
  content: "\f246";
}
.fa-object-group:before {
  content: "\f247";
}
.fa-object-ungroup:before {
  content: "\f248";
}
.fa-sticky-note:before {
  content: "\f249";
}
.fa-sticky-note-o:before {
  content: "\f24a";
}
.fa-cc-jcb:before {
  content: "\f24b";
}
.fa-cc-diners-club:before {
  content: "\f24c";
}
.fa-clone:before {
  content: "\f24d";
}
.fa-balance-scale:before {
  content: "\f24e";
}
.fa-hourglass-o:before {
  content: "\f250";
}
.fa-hourglass-1:before,
.fa-hourglass-start:before {
  content: "\f251";
}
.fa-hourglass-2:before,
.fa-hourglass-half:before {
  content: "\f252";
}
.fa-hourglass-3:before,
.fa-hourglass-end:before {
  content: "\f253";
}
.fa-hourglass:before {
  content: "\f254";
}
.fa-hand-grab-o:before,
.fa-hand-rock-o:before {
  content: "\f255";
}
.fa-hand-stop-o:before,
.fa-hand-paper-o:before {
  content: "\f256";
}
.fa-hand-scissors-o:before {
  content: "\f257";
}
.fa-hand-lizard-o:before {
  content: "\f258";
}
.fa-hand-spock-o:before {
  content: "\f259";
}
.fa-hand-pointer-o:before {
  content: "\f25a";
}
.fa-hand-peace-o:before {
  content: "\f25b";
}
.fa-trademark:before {
  content: "\f25c";
}
.fa-registered:before {
  content: "\f25d";
}
.fa-creative-commons:before {
  content: "\f25e";
}
.fa-gg:before {
  content: "\f260";
}
.fa-gg-circle:before {
  content: "\f261";
}
.fa-tripadvisor:before {
  content: "\f262";
}
.fa-odnoklassniki:before {
  content: "\f263";
}
.fa-odnoklassniki-square:before {
  content: "\f264";
}
.fa-get-pocket:before {
  content: "\f265";
}
.fa-wikipedia-w:before {
  content: "\f266";
}
.fa-safari:before {
  content: "\f267";
}
.fa-chrome:before {
  content: "\f268";
}
.fa-firefox:before {
  content: "\f269";
}
.fa-opera:before {
  content: "\f26a";
}
.fa-internet-explorer:before {
  content: "\f26b";
}
.fa-tv:before,
.fa-television:before {
  content: "\f26c";
}
.fa-contao:before {
  content: "\f26d";
}
.fa-500px:before {
  content: "\f26e";
}
.fa-amazon:before {
  content: "\f270";
}
.fa-calendar-plus-o:before {
  content: "\f271";
}
.fa-calendar-minus-o:before {
  content: "\f272";
}
.fa-calendar-times-o:before {
  content: "\f273";
}
.fa-calendar-check-o:before {
  content: "\f274";
}
.fa-industry:before {
  content: "\f275";
}
.fa-map-pin:before {
  content: "\f276";
}
.fa-map-signs:before {
  content: "\f277";
}
.fa-map-o:before {
  content: "\f278";
}
.fa-map:before {
  content: "\f279";
}
.fa-commenting:before {
  content: "\f27a";
}
.fa-commenting-o:before {
  content: "\f27b";
}
.fa-houzz:before {
  content: "\f27c";
}
.fa-vimeo:before {
  content: "\f27d";
}
.fa-black-tie:before {
  content: "\f27e";
}
.fa-fonticons:before {
  content: "\f280";
}
.fa-reddit-alien:before {
  content: "\f281";
}
.fa-edge:before {
  content: "\f282";
}
.fa-credit-card-alt:before {
  content: "\f283";
}
.fa-codiepie:before {
  content: "\f284";
}
.fa-modx:before {
  content: "\f285";
}
.fa-fort-awesome:before {
  content: "\f286";
}
.fa-usb:before {
  content: "\f287";
}
.fa-product-hunt:before {
  content: "\f288";
}
.fa-mixcloud:before {
  content: "\f289";
}
.fa-scribd:before {
  content: "\f28a";
}
.fa-pause-circle:before {
  content: "\f28b";
}
.fa-pause-circle-o:before {
  content: "\f28c";
}
.fa-stop-circle:before {
  content: "\f28d";
}
.fa-stop-circle-o:before {
  content: "\f28e";
}
.fa-shopping-bag:before {
  content: "\f290";
}
.fa-shopping-basket:before {
  content: "\f291";
}
.fa-hashtag:before {
  content: "\f292";
}
.fa-bluetooth:before {
  content: "\f293";
}
.fa-bluetooth-b:before {
  content: "\f294";
}
.fa-percent:before {
  content: "\f295";
}
.fa-gitlab:before {
  content: "\f296";
}
.fa-wpbeginner:before {
  content: "\f297";
}
.fa-wpforms:before {
  content: "\f298";
}
.fa-envira:before {
  content: "\f299";
}
.fa-universal-access:before {
  content: "\f29a";
}
.fa-wheelchair-alt:before {
  content: "\f29b";
}
.fa-question-circle-o:before {
  content: "\f29c";
}
.fa-blind:before {
  content: "\f29d";
}
.fa-audio-description:before {
  content: "\f29e";
}
.fa-volume-control-phone:before {
  content: "\f2a0";
}
.fa-braille:before {
  content: "\f2a1";
}
.fa-assistive-listening-systems:before {
  content: "\f2a2";
}
.fa-asl-interpreting:before,
.fa-american-sign-language-interpreting:before {
  content: "\f2a3";
}
.fa-deafness:before,
.fa-hard-of-hearing:before,
.fa-deaf:before {
  content: "\f2a4";
}
.fa-glide:before {
  content: "\f2a5";
}
.fa-glide-g:before {
  content: "\f2a6";
}
.fa-signing:before,
.fa-sign-language:before {
  content: "\f2a7";
}
.fa-low-vision:before {
  content: "\f2a8";
}
.fa-viadeo:before {
  content: "\f2a9";
}
.fa-viadeo-square:before {
  content: "\f2aa";
}
.fa-snapchat:before {
  content: "\f2ab";
}
.fa-snapchat-ghost:before {
  content: "\f2ac";
}
.fa-snapchat-square:before {
  content: "\f2ad";
}
.fa-pied-piper:before {
  content: "\f2ae";
}
.fa-first-order:before {
  content: "\f2b0";
}
.fa-yoast:before {
  content: "\f2b1";
}
.fa-themeisle:before {
  content: "\f2b2";
}
.fa-google-plus-circle:before,
.fa-google-plus-official:before {
  content: "\f2b3";
}
.fa-fa:before,
.fa-font-awesome:before {
  content: "\f2b4";
}
.fa-handshake-o:before {
  content: "\f2b5";
}
.fa-envelope-open:before {
  content: "\f2b6";
}
.fa-envelope-open-o:before {
  content: "\f2b7";
}
.fa-linode:before {
  content: "\f2b8";
}
.fa-address-book:before {
  content: "\f2b9";
}
.fa-address-book-o:before {
  content: "\f2ba";
}
.fa-vcard:before,
.fa-address-card:before {
  content: "\f2bb";
}
.fa-vcard-o:before,
.fa-address-card-o:before {
  content: "\f2bc";
}
.fa-user-circle:before {
  content: "\f2bd";
}
.fa-user-circle-o:before {
  content: "\f2be";
}
.fa-user-o:before {
  content: "\f2c0";
}
.fa-id-badge:before {
  content: "\f2c1";
}
.fa-drivers-license:before,
.fa-id-card:before {
  content: "\f2c2";
}
.fa-drivers-license-o:before,
.fa-id-card-o:before {
  content: "\f2c3";
}
.fa-quora:before {
  content: "\f2c4";
}
.fa-free-code-camp:before {
  content: "\f2c5";
}
.fa-telegram:before {
  content: "\f2c6";
}
.fa-thermometer-4:before,
.fa-thermometer:before,
.fa-thermometer-full:before {
  content: "\f2c7";
}
.fa-thermometer-3:before,
.fa-thermometer-three-quarters:before {
  content: "\f2c8";
}
.fa-thermometer-2:before,
.fa-thermometer-half:before {
  content: "\f2c9";
}
.fa-thermometer-1:before,
.fa-thermometer-quarter:before {
  content: "\f2ca";
}
.fa-thermometer-0:before,
.fa-thermometer-empty:before {
  content: "\f2cb";
}
.fa-shower:before {
  content: "\f2cc";
}
.fa-bathtub:before,
.fa-s15:before,
.fa-bath:before {
  content: "\f2cd";
}
.fa-podcast:before {
  content: "\f2ce";
}
.fa-window-maximize:before {
  content: "\f2d0";
}
.fa-window-minimize:before {
  content: "\f2d1";
}
.fa-window-restore:before {
  content: "\f2d2";
}
.fa-times-rectangle:before,
.fa-window-close:before {
  content: "\f2d3";
}
.fa-times-rectangle-o:before,
.fa-window-close-o:before {
  content: "\f2d4";
}
.fa-bandcamp:before {
  content: "\f2d5";
}
.fa-grav:before {
  content: "\f2d6";
}
.fa-etsy:before {
  content: "\f2d7";
}
.fa-imdb:before {
  content: "\f2d8";
}
.fa-ravelry:before {
  content: "\f2d9";
}
.fa-eercast:before {
  content: "\f2da";
}
.fa-microchip:before {
  content: "\f2db";
}
.fa-snowflake-o:before {
  content: "\f2dc";
}
.fa-superpowers:before {
  content: "\f2dd";
}
.fa-wpexplorer:before {
  content: "\f2de";
}
.fa-meetup:before {
  content: "\f2e0";
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  padding: 0;
  margin: -1px;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
/*!
*
* IPython base
*
*/
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
code {
  color: #000;
}
pre {
  font-size: inherit;
  line-height: inherit;
}
label {
  font-weight: normal;
}
/* Make the page background atleast 100% the height of the view port */
/* Make the page itself atleast 70% the height of the view port */
.border-box-sizing {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.corner-all {
  border-radius: 2px;
}
.no-padding {
  padding: 0px;
}
/* Flexible box model classes */
/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
/* This file is a compatability layer.  It allows the usage of flexible box 
model layouts accross multiple browsers, including older browsers.  The newest,
universal implementation of the flexible box model is used when available (see
`Modern browsers` comments below).  Browsers that are known to implement this 
new spec completely include:

    Firefox 28.0+
    Chrome 29.0+
    Internet Explorer 11+ 
    Opera 17.0+

Browsers not listed, including Safari, are supported via the styling under the
`Old browsers` comments below.
*/
.hbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
.hbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.vbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
.vbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.hbox.reverse,
.vbox.reverse,
.reverse {
  /* Old browsers */
  -webkit-box-direction: reverse;
  -moz-box-direction: reverse;
  box-direction: reverse;
  /* Modern browsers */
  flex-direction: row-reverse;
}
.hbox.box-flex0,
.vbox.box-flex0,
.box-flex0 {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
  width: auto;
}
.hbox.box-flex1,
.vbox.box-flex1,
.box-flex1 {
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex,
.vbox.box-flex,
.box-flex {
  /* Old browsers */
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex2,
.vbox.box-flex2,
.box-flex2 {
  /* Old browsers */
  -webkit-box-flex: 2;
  -moz-box-flex: 2;
  box-flex: 2;
  /* Modern browsers */
  flex: 2;
}
.box-group1 {
  /*  Deprecated */
  -webkit-box-flex-group: 1;
  -moz-box-flex-group: 1;
  box-flex-group: 1;
}
.box-group2 {
  /* Deprecated */
  -webkit-box-flex-group: 2;
  -moz-box-flex-group: 2;
  box-flex-group: 2;
}
.hbox.start,
.vbox.start,
.start {
  /* Old browsers */
  -webkit-box-pack: start;
  -moz-box-pack: start;
  box-pack: start;
  /* Modern browsers */
  justify-content: flex-start;
}
.hbox.end,
.vbox.end,
.end {
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
}
.hbox.center,
.vbox.center,
.center {
  /* Old browsers */
  -webkit-box-pack: center;
  -moz-box-pack: center;
  box-pack: center;
  /* Modern browsers */
  justify-content: center;
}
.hbox.baseline,
.vbox.baseline,
.baseline {
  /* Old browsers */
  -webkit-box-pack: baseline;
  -moz-box-pack: baseline;
  box-pack: baseline;
  /* Modern browsers */
  justify-content: baseline;
}
.hbox.stretch,
.vbox.stretch,
.stretch {
  /* Old browsers */
  -webkit-box-pack: stretch;
  -moz-box-pack: stretch;
  box-pack: stretch;
  /* Modern browsers */
  justify-content: stretch;
}
.hbox.align-start,
.vbox.align-start,
.align-start {
  /* Old browsers */
  -webkit-box-align: start;
  -moz-box-align: start;
  box-align: start;
  /* Modern browsers */
  align-items: flex-start;
}
.hbox.align-end,
.vbox.align-end,
.align-end {
  /* Old browsers */
  -webkit-box-align: end;
  -moz-box-align: end;
  box-align: end;
  /* Modern browsers */
  align-items: flex-end;
}
.hbox.align-center,
.vbox.align-center,
.align-center {
  /* Old browsers */
  -webkit-box-align: center;
  -moz-box-align: center;
  box-align: center;
  /* Modern browsers */
  align-items: center;
}
.hbox.align-baseline,
.vbox.align-baseline,
.align-baseline {
  /* Old browsers */
  -webkit-box-align: baseline;
  -moz-box-align: baseline;
  box-align: baseline;
  /* Modern browsers */
  align-items: baseline;
}
.hbox.align-stretch,
.vbox.align-stretch,
.align-stretch {
  /* Old browsers */
  -webkit-box-align: stretch;
  -moz-box-align: stretch;
  box-align: stretch;
  /* Modern browsers */
  align-items: stretch;
}
div.error {
  margin: 2em;
  text-align: center;
}
div.error > h1 {
  font-size: 500%;
  line-height: normal;
}
div.error > p {
  font-size: 200%;
  line-height: normal;
}
div.traceback-wrapper {
  text-align: left;
  max-width: 800px;
  margin: auto;
}
div.traceback-wrapper pre.traceback {
  max-height: 600px;
  overflow: auto;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
body {
  background-color: #fff;
  /* This makes sure that the body covers the entire window and needs to
       be in a different element than the display: box in wrapper below */
  position: absolute;
  left: 0px;
  right: 0px;
  top: 0px;
  bottom: 0px;
  overflow: visible;
}
body > #header {
  /* Initially hidden to prevent FLOUC */
  display: none;
  background-color: #fff;
  /* Display over codemirror */
  position: relative;
  z-index: 100;
}
body > #header #header-container {
  display: flex;
  flex-direction: row;
  justify-content: space-between;
  padding: 5px;
  padding-bottom: 5px;
  padding-top: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
body > #header .header-bar {
  width: 100%;
  height: 1px;
  background: #e7e7e7;
  margin-bottom: -1px;
}
@media print {
  body > #header {
    display: none !important;
  }
}
#header-spacer {
  width: 100%;
  visibility: hidden;
}
@media print {
  #header-spacer {
    display: none;
  }
}
#ipython_notebook {
  padding-left: 0px;
  padding-top: 1px;
  padding-bottom: 1px;
}
[dir="rtl"] #ipython_notebook {
  margin-right: 10px;
  margin-left: 0;
}
[dir="rtl"] #ipython_notebook.pull-left {
  float: right !important;
  float: right;
}
.flex-spacer {
  flex: 1;
}
#noscript {
  width: auto;
  padding-top: 16px;
  padding-bottom: 16px;
  text-align: center;
  font-size: 22px;
  color: red;
  font-weight: bold;
}
#ipython_notebook img {
  height: 28px;
}
#site {
  width: 100%;
  display: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  overflow: auto;
}
@media print {
  #site {
    height: auto !important;
  }
}
/* Smaller buttons */
.ui-button .ui-button-text {
  padding: 0.2em 0.8em;
  font-size: 77%;
}
input.ui-button {
  padding: 0.3em 0.9em;
}
span#kernel_logo_widget {
  margin: 0 10px;
}
span#login_widget {
  float: right;
}
[dir="rtl"] span#login_widget {
  float: left;
}
span#login_widget > .button,
#logout {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button:focus,
#logout:focus,
span#login_widget > .button.focus,
#logout.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
span#login_widget > .button:hover,
#logout:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active:hover,
#logout:active:hover,
span#login_widget > .button.active:hover,
#logout.active:hover,
.open > .dropdown-togglespan#login_widget > .button:hover,
.open > .dropdown-toggle#logout:hover,
span#login_widget > .button:active:focus,
#logout:active:focus,
span#login_widget > .button.active:focus,
#logout.active:focus,
.open > .dropdown-togglespan#login_widget > .button:focus,
.open > .dropdown-toggle#logout:focus,
span#login_widget > .button:active.focus,
#logout:active.focus,
span#login_widget > .button.active.focus,
#logout.active.focus,
.open > .dropdown-togglespan#login_widget > .button.focus,
.open > .dropdown-toggle#logout.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  background-image: none;
}
span#login_widget > .button.disabled:hover,
#logout.disabled:hover,
span#login_widget > .button[disabled]:hover,
#logout[disabled]:hover,
fieldset[disabled] span#login_widget > .button:hover,
fieldset[disabled] #logout:hover,
span#login_widget > .button.disabled:focus,
#logout.disabled:focus,
span#login_widget > .button[disabled]:focus,
#logout[disabled]:focus,
fieldset[disabled] span#login_widget > .button:focus,
fieldset[disabled] #logout:focus,
span#login_widget > .button.disabled.focus,
#logout.disabled.focus,
span#login_widget > .button[disabled].focus,
#logout[disabled].focus,
fieldset[disabled] span#login_widget > .button.focus,
fieldset[disabled] #logout.focus {
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button .badge,
#logout .badge {
  color: #fff;
  background-color: #333;
}
.nav-header {
  text-transform: none;
}
#header > span {
  margin-top: 10px;
}
.modal_stretch .modal-dialog {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  min-height: 80vh;
}
.modal_stretch .modal-dialog .modal-body {
  max-height: calc(100vh - 200px);
  overflow: auto;
  flex: 1;
}
.modal-header {
  cursor: move;
}
@media (min-width: 768px) {
  .modal .modal-dialog {
    width: 700px;
  }
}
@media (min-width: 768px) {
  select.form-control {
    margin-left: 12px;
    margin-right: 12px;
  }
}
/*!
*
* IPython auth
*
*/
.center-nav {
  display: inline-block;
  margin-bottom: -4px;
}
[dir="rtl"] .center-nav form.pull-left {
  float: right !important;
  float: right;
}
[dir="rtl"] .center-nav .navbar-text {
  float: right;
}
[dir="rtl"] .navbar-inner {
  text-align: right;
}
[dir="rtl"] div.text-left {
  text-align: right;
}
/*!
*
* IPython tree view
*
*/
/* We need an invisible input field on top of the sentense*/
/* "Drag file onto the list ..." */
.alternate_upload {
  background-color: none;
  display: inline;
}
.alternate_upload.form {
  padding: 0;
  margin: 0;
}
.alternate_upload input.fileinput {
  position: absolute;
  display: block;
  width: 100%;
  height: 100%;
  overflow: hidden;
  cursor: pointer;
  opacity: 0;
  z-index: 2;
}
.alternate_upload .btn-xs > input.fileinput {
  margin: -1px -5px;
}
.alternate_upload .btn-upload {
  position: relative;
  height: 22px;
}
::-webkit-file-upload-button {
  cursor: pointer;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
ul#tabs {
  margin-bottom: 4px;
}
ul#tabs a {
  padding-top: 6px;
  padding-bottom: 4px;
}
[dir="rtl"] ul#tabs.nav-tabs > li {
  float: right;
}
[dir="rtl"] ul#tabs.nav.nav-tabs {
  padding-right: 0;
}
ul.breadcrumb a:focus,
ul.breadcrumb a:hover {
  text-decoration: none;
}
ul.breadcrumb i.icon-home {
  font-size: 16px;
  margin-right: 4px;
}
ul.breadcrumb span {
  color: #5e5e5e;
}
.list_toolbar {
  padding: 4px 0 4px 0;
  vertical-align: middle;
}
.list_toolbar .tree-buttons {
  padding-top: 1px;
}
[dir="rtl"] .list_toolbar .tree-buttons .pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .list_toolbar .col-sm-4,
[dir="rtl"] .list_toolbar .col-sm-8 {
  float: right;
}
.dynamic-buttons {
  padding-top: 3px;
  display: inline-block;
}
.list_toolbar [class*="span"] {
  min-height: 24px;
}
.list_header {
  font-weight: bold;
  background-color: #EEE;
}
.list_placeholder {
  font-weight: bold;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
}
.list_container {
  margin-top: 4px;
  margin-bottom: 20px;
  border: 1px solid #ddd;
  border-radius: 2px;
}
.list_container > div {
  border-bottom: 1px solid #ddd;
}
.list_container > div:hover .list-item {
  background-color: red;
}
.list_container > div:last-child {
  border: none;
}
.list_item:hover .list_item {
  background-color: #ddd;
}
.list_item a {
  text-decoration: none;
}
.list_item:hover {
  background-color: #fafafa;
}
.list_header > div,
.list_item > div {
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
.list_header > div input,
.list_item > div input {
  margin-right: 7px;
  margin-left: 14px;
  vertical-align: text-bottom;
  line-height: 22px;
  position: relative;
  top: -1px;
}
.list_header > div .item_link,
.list_item > div .item_link {
  margin-left: -1px;
  vertical-align: baseline;
  line-height: 22px;
}
[dir="rtl"] .list_item > div input {
  margin-right: 0;
}
.new-file input[type=checkbox] {
  visibility: hidden;
}
.item_name {
  line-height: 22px;
  height: 24px;
}
.item_icon {
  font-size: 14px;
  color: #5e5e5e;
  margin-right: 7px;
  margin-left: 7px;
  line-height: 22px;
  vertical-align: baseline;
}
.item_modified {
  margin-right: 7px;
  margin-left: 7px;
}
[dir="rtl"] .item_modified.pull-right {
  float: left !important;
  float: left;
}
.item_buttons {
  line-height: 1em;
  margin-left: -5px;
}
.item_buttons .btn,
.item_buttons .btn-group,
.item_buttons .input-group {
  float: left;
}
.item_buttons > .btn,
.item_buttons > .btn-group,
.item_buttons > .input-group {
  margin-left: 5px;
}
.item_buttons .btn {
  min-width: 13ex;
}
.item_buttons .running-indicator {
  padding-top: 4px;
  color: #5cb85c;
}
.item_buttons .kernel-name {
  padding-top: 4px;
  color: #5bc0de;
  margin-right: 7px;
  float: left;
}
[dir="rtl"] .item_buttons.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .item_buttons .kernel-name {
  margin-left: 7px;
  float: right;
}
.toolbar_info {
  height: 24px;
  line-height: 24px;
}
.list_item input:not([type=checkbox]) {
  padding-top: 3px;
  padding-bottom: 3px;
  height: 22px;
  line-height: 14px;
  margin: 0px;
}
.highlight_text {
  color: blue;
}
#project_name {
  display: inline-block;
  padding-left: 7px;
  margin-left: -2px;
}
#project_name > .breadcrumb {
  padding: 0px;
  margin-bottom: 0px;
  background-color: transparent;
  font-weight: bold;
}
.sort_button {
  display: inline-block;
  padding-left: 7px;
}
[dir="rtl"] .sort_button.pull-right {
  float: left !important;
  float: left;
}
#tree-selector {
  padding-right: 0px;
}
#button-select-all {
  min-width: 50px;
}
[dir="rtl"] #button-select-all.btn {
  float: right ;
}
#select-all {
  margin-left: 7px;
  margin-right: 2px;
  margin-top: 2px;
  height: 16px;
}
[dir="rtl"] #select-all.pull-left {
  float: right !important;
  float: right;
}
.menu_icon {
  margin-right: 2px;
}
.tab-content .row {
  margin-left: 0px;
  margin-right: 0px;
}
.folder_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f114";
}
.folder_icon:before.fa-pull-left {
  margin-right: .3em;
}
.folder_icon:before.fa-pull-right {
  margin-left: .3em;
}
.folder_icon:before.pull-left {
  margin-right: .3em;
}
.folder_icon:before.pull-right {
  margin-left: .3em;
}
.notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
}
.notebook_icon:before.fa-pull-left {
  margin-right: .3em;
}
.notebook_icon:before.fa-pull-right {
  margin-left: .3em;
}
.notebook_icon:before.pull-left {
  margin-right: .3em;
}
.notebook_icon:before.pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
  color: #5cb85c;
}
.running_notebook_icon:before.fa-pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.fa-pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before.pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.pull-right {
  margin-left: .3em;
}
.file_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f016";
  position: relative;
  top: -2px;
}
.file_icon:before.fa-pull-left {
  margin-right: .3em;
}
.file_icon:before.fa-pull-right {
  margin-left: .3em;
}
.file_icon:before.pull-left {
  margin-right: .3em;
}
.file_icon:before.pull-right {
  margin-left: .3em;
}
#notebook_toolbar .pull-right {
  padding-top: 0px;
  margin-right: -1px;
}
ul#new-menu {
  left: auto;
  right: 0;
}
#new-menu .dropdown-header {
  font-size: 10px;
  border-bottom: 1px solid #e5e5e5;
  padding: 0 0 3px;
  margin: -3px 20px 0;
}
.kernel-menu-icon {
  padding-right: 12px;
  width: 24px;
  content: "\f096";
}
.kernel-menu-icon:before {
  content: "\f096";
}
.kernel-menu-icon-current:before {
  content: "\f00c";
}
#tab_content {
  padding-top: 20px;
}
#running .panel-group .panel {
  margin-top: 3px;
  margin-bottom: 1em;
}
#running .panel-group .panel .panel-heading {
  background-color: #EEE;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
#running .panel-group .panel .panel-heading a:focus,
#running .panel-group .panel .panel-heading a:hover {
  text-decoration: none;
}
#running .panel-group .panel .panel-body {
  padding: 0px;
}
#running .panel-group .panel .panel-body .list_container {
  margin-top: 0px;
  margin-bottom: 0px;
  border: 0px;
  border-radius: 0px;
}
#running .panel-group .panel .panel-body .list_container .list_item {
  border-bottom: 1px solid #ddd;
}
#running .panel-group .panel .panel-body .list_container .list_item:last-child {
  border-bottom: 0px;
}
.delete-button {
  display: none;
}
.duplicate-button {
  display: none;
}
.rename-button {
  display: none;
}
.move-button {
  display: none;
}
.download-button {
  display: none;
}
.shutdown-button {
  display: none;
}
.dynamic-instructions {
  display: inline-block;
  padding-top: 4px;
}
/*!
*
* IPython text editor webapp
*
*/
.selected-keymap i.fa {
  padding: 0px 5px;
}
.selected-keymap i.fa:before {
  content: "\f00c";
}
#mode-menu {
  overflow: auto;
  max-height: 20em;
}
.edit_app #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.edit_app #menubar .navbar {
  /* Use a negative 1 bottom margin, so the border overlaps the border of the
    header */
  margin-bottom: -1px;
}
.dirty-indicator {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator.pull-left {
  margin-right: .3em;
}
.dirty-indicator.pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-dirty.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty.pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-clean.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f00c";
}
.dirty-indicator-clean:before.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.pull-right {
  margin-left: .3em;
}
#filename {
  font-size: 16pt;
  display: table;
  padding: 0px 5px;
}
#current-mode {
  padding-left: 5px;
  padding-right: 5px;
}
#texteditor-backdrop {
  padding-top: 20px;
  padding-bottom: 20px;
}
@media not print {
  #texteditor-backdrop {
    background-color: #EEE;
  }
}
@media print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container {
    padding: 0px;
    background-color: #fff;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
.CodeMirror-dialog {
  background-color: #fff;
}
/*!
*
* IPython notebook
*
*/
/* CSS font colors for translated ANSI escape sequences */
/* The color values are a mix of
   http://www.xcolors.net/dl/baskerville-ivorylight and
   http://www.xcolors.net/dl/euphrasia */
.ansi-black-fg {
  color: #3E424D;
}
.ansi-black-bg {
  background-color: #3E424D;
}
.ansi-black-intense-fg {
  color: #282C36;
}
.ansi-black-intense-bg {
  background-color: #282C36;
}
.ansi-red-fg {
  color: #E75C58;
}
.ansi-red-bg {
  background-color: #E75C58;
}
.ansi-red-intense-fg {
  color: #B22B31;
}
.ansi-red-intense-bg {
  background-color: #B22B31;
}
.ansi-green-fg {
  color: #00A250;
}
.ansi-green-bg {
  background-color: #00A250;
}
.ansi-green-intense-fg {
  color: #007427;
}
.ansi-green-intense-bg {
  background-color: #007427;
}
.ansi-yellow-fg {
  color: #DDB62B;
}
.ansi-yellow-bg {
  background-color: #DDB62B;
}
.ansi-yellow-intense-fg {
  color: #B27D12;
}
.ansi-yellow-intense-bg {
  background-color: #B27D12;
}
.ansi-blue-fg {
  color: #208FFB;
}
.ansi-blue-bg {
  background-color: #208FFB;
}
.ansi-blue-intense-fg {
  color: #0065CA;
}
.ansi-blue-intense-bg {
  background-color: #0065CA;
}
.ansi-magenta-fg {
  color: #D160C4;
}
.ansi-magenta-bg {
  background-color: #D160C4;
}
.ansi-magenta-intense-fg {
  color: #A03196;
}
.ansi-magenta-intense-bg {
  background-color: #A03196;
}
.ansi-cyan-fg {
  color: #60C6C8;
}
.ansi-cyan-bg {
  background-color: #60C6C8;
}
.ansi-cyan-intense-fg {
  color: #258F8F;
}
.ansi-cyan-intense-bg {
  background-color: #258F8F;
}
.ansi-white-fg {
  color: #C5C1B4;
}
.ansi-white-bg {
  background-color: #C5C1B4;
}
.ansi-white-intense-fg {
  color: #A1A6B2;
}
.ansi-white-intense-bg {
  background-color: #A1A6B2;
}
.ansi-default-inverse-fg {
  color: #FFFFFF;
}
.ansi-default-inverse-bg {
  background-color: #000000;
}
.ansi-bold {
  font-weight: bold;
}
.ansi-underline {
  text-decoration: underline;
}
/* The following styles are deprecated an will be removed in a future version */
.ansibold {
  font-weight: bold;
}
.ansi-inverse {
  outline: 0.5px dotted;
}
/* use dark versions for foreground, to improve visibility */
.ansiblack {
  color: black;
}
.ansired {
  color: darkred;
}
.ansigreen {
  color: darkgreen;
}
.ansiyellow {
  color: #c4a000;
}
.ansiblue {
  color: darkblue;
}
.ansipurple {
  color: darkviolet;
}
.ansicyan {
  color: steelblue;
}
.ansigray {
  color: gray;
}
/* and light for background, for the same reason */
.ansibgblack {
  background-color: black;
}
.ansibgred {
  background-color: red;
}
.ansibggreen {
  background-color: green;
}
.ansibgyellow {
  background-color: yellow;
}
.ansibgblue {
  background-color: blue;
}
.ansibgpurple {
  background-color: magenta;
}
.ansibgcyan {
  background-color: cyan;
}
.ansibggray {
  background-color: gray;
}
div.cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  border-radius: 2px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  border-width: 1px;
  border-style: solid;
  border-color: transparent;
  width: 100%;
  padding: 5px;
  /* This acts as a spacer between cells, that is outside the border */
  margin: 0px;
  outline: none;
  position: relative;
  overflow: visible;
}
div.cell:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: transparent;
}
div.cell.jupyter-soft-selected {
  border-left-color: #E3F2FD;
  border-left-width: 1px;
  padding-left: 5px;
  border-right-color: #E3F2FD;
  border-right-width: 1px;
  background: #E3F2FD;
}
@media print {
  div.cell.jupyter-soft-selected {
    border-color: transparent;
  }
}
div.cell.selected,
div.cell.selected.jupyter-soft-selected {
  border-color: #ababab;
}
div.cell.selected:before,
div.cell.selected.jupyter-soft-selected:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: #42A5F5;
}
@media print {
  div.cell.selected,
  div.cell.selected.jupyter-soft-selected {
    border-color: transparent;
  }
}
.edit_mode div.cell.selected {
  border-color: #66BB6A;
}
.edit_mode div.cell.selected:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: #66BB6A;
}
@media print {
  .edit_mode div.cell.selected {
    border-color: transparent;
  }
}
.prompt {
  /* This needs to be wide enough for 3 digit prompt numbers: In[100]: */
  min-width: 14ex;
  /* This padding is tuned to match the padding on the CodeMirror editor. */
  padding: 0.4em;
  margin: 0px;
  font-family: monospace;
  text-align: right;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
  /* Don't highlight prompt number selection */
  -webkit-touch-callout: none;
  -webkit-user-select: none;
  -khtml-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
  /* Use default cursor */
  cursor: default;
}
@media (max-width: 540px) {
  .prompt {
    text-align: left;
  }
}
div.inner_cell {
  min-width: 0;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_area {
  border: 1px solid #cfcfcf;
  border-radius: 2px;
  background: #f7f7f7;
  line-height: 1.21429em;
}
/* This is needed so that empty prompt areas can collapse to zero height when there
   is no content in the output_subarea and the prompt. The main purpose of this is
   to make sure that empty JavaScript output_subareas have no height. */
div.prompt:empty {
  padding-top: 0;
  padding-bottom: 0;
}
div.unrecognized_cell {
  padding: 5px 5px 5px 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.unrecognized_cell .inner_cell {
  border-radius: 2px;
  padding: 5px;
  font-weight: bold;
  color: red;
  border: 1px solid #cfcfcf;
  background: #eaeaea;
}
div.unrecognized_cell .inner_cell a {
  color: inherit;
  text-decoration: none;
}
div.unrecognized_cell .inner_cell a:hover {
  color: inherit;
  text-decoration: none;
}
@media (max-width: 540px) {
  div.unrecognized_cell > div.prompt {
    display: none;
  }
}
div.code_cell {
  /* avoid page breaking on code cells when printing */
}
@media print {
  div.code_cell {
    page-break-inside: avoid;
  }
}
/* any special styling for code cells that are currently running goes here */
div.input {
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.input {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_prompt {
  color: #303F9F;
  border-top: 1px solid transparent;
}
div.input_area > div.highlight {
  margin: 0.4em;
  border: none;
  padding: 0px;
  background-color: transparent;
}
div.input_area > div.highlight > pre {
  margin: 0px;
  border: none;
  padding: 0px;
  background-color: transparent;
}
/* The following gets added to the <head> if it is detected that the user has a
 * monospace font with inconsistent normal/bold/italic height.  See
 * notebookmain.js.  Such fonts will have keywords vertically offset with
 * respect to the rest of the text.  The user should select a better font.
 * See: https://github.com/ipython/ipython/issues/1503
 *
 * .CodeMirror span {
 *      vertical-align: bottom;
 * }
 */
.CodeMirror {
  line-height: 1.21429em;
  /* Changed from 1em to our global default */
  font-size: 14px;
  height: auto;
  /* Changed to auto to autogrow */
  background: none;
  /* Changed from white to allow our bg to show through */
}
.CodeMirror-scroll {
  /*  The CodeMirror docs are a bit fuzzy on if overflow-y should be hidden or visible.*/
  /*  We have found that if it is visible, vertical scrollbars appear with font size changes.*/
  overflow-y: hidden;
  overflow-x: auto;
}
.CodeMirror-lines {
  /* In CM2, this used to be 0.4em, but in CM3 it went to 4px. We need the em value because */
  /* we have set a different line-height and want this to scale with that. */
  /* Note that this should set vertical padding only, since CodeMirror assumes
       that horizontal padding will be set on CodeMirror pre */
  padding: 0.4em 0;
}
.CodeMirror-linenumber {
  padding: 0 8px 0 4px;
}
.CodeMirror-gutters {
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.CodeMirror pre {
  /* In CM3 this went to 4px from 0 in CM2. This sets horizontal padding only,
    use .CodeMirror-lines for vertical */
  padding: 0 0.4em;
  border: 0;
  border-radius: 0;
}
.CodeMirror-cursor {
  border-left: 1.4px solid black;
}
@media screen and (min-width: 2138px) and (max-width: 4319px) {
  .CodeMirror-cursor {
    border-left: 2px solid black;
  }
}
@media screen and (min-width: 4320px) {
  .CodeMirror-cursor {
    border-left: 4px solid black;
  }
}
/*

Original style from softwaremaniacs.org (c) Ivan Sagalaev <Maniac@SoftwareManiacs.Org>
Adapted from GitHub theme

*/
.highlight-base {
  color: #000;
}
.highlight-variable {
  color: #000;
}
.highlight-variable-2 {
  color: #1a1a1a;
}
.highlight-variable-3 {
  color: #333333;
}
.highlight-string {
  color: #BA2121;
}
.highlight-comment {
  color: #408080;
  font-style: italic;
}
.highlight-number {
  color: #080;
}
.highlight-atom {
  color: #88F;
}
.highlight-keyword {
  color: #008000;
  font-weight: bold;
}
.highlight-builtin {
  color: #008000;
}
.highlight-error {
  color: #f00;
}
.highlight-operator {
  color: #AA22FF;
  font-weight: bold;
}
.highlight-meta {
  color: #AA22FF;
}
/* previously not defined, copying from default codemirror */
.highlight-def {
  color: #00f;
}
.highlight-string-2 {
  color: #f50;
}
.highlight-qualifier {
  color: #555;
}
.highlight-bracket {
  color: #997;
}
.highlight-tag {
  color: #170;
}
.highlight-attribute {
  color: #00c;
}
.highlight-header {
  color: blue;
}
.highlight-quote {
  color: #090;
}
.highlight-link {
  color: #00c;
}
/* apply the same style to codemirror */
.cm-s-ipython span.cm-keyword {
  color: #008000;
  font-weight: bold;
}
.cm-s-ipython span.cm-atom {
  color: #88F;
}
.cm-s-ipython span.cm-number {
  color: #080;
}
.cm-s-ipython span.cm-def {
  color: #00f;
}
.cm-s-ipython span.cm-variable {
  color: #000;
}
.cm-s-ipython span.cm-operator {
  color: #AA22FF;
  font-weight: bold;
}
.cm-s-ipython span.cm-variable-2 {
  color: #1a1a1a;
}
.cm-s-ipython span.cm-variable-3 {
  color: #333333;
}
.cm-s-ipython span.cm-comment {
  color: #408080;
  font-style: italic;
}
.cm-s-ipython span.cm-string {
  color: #BA2121;
}
.cm-s-ipython span.cm-string-2 {
  color: #f50;
}
.cm-s-ipython span.cm-meta {
  color: #AA22FF;
}
.cm-s-ipython span.cm-qualifier {
  color: #555;
}
.cm-s-ipython span.cm-builtin {
  color: #008000;
}
.cm-s-ipython span.cm-bracket {
  color: #997;
}
.cm-s-ipython span.cm-tag {
  color: #170;
}
.cm-s-ipython span.cm-attribute {
  color: #00c;
}
.cm-s-ipython span.cm-header {
  color: blue;
}
.cm-s-ipython span.cm-quote {
  color: #090;
}
.cm-s-ipython span.cm-link {
  color: #00c;
}
.cm-s-ipython span.cm-error {
  color: #f00;
}
.cm-s-ipython span.cm-tab {
  background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
  background-position: right;
  background-repeat: no-repeat;
}
div.output_wrapper {
  /* this position must be relative to enable descendents to be absolute within it */
  position: relative;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  z-index: 1;
}
/* class for the output area when it should be height-limited */
div.output_scroll {
  /* ideally, this would be max-height, but FF barfs all over that */
  height: 24em;
  /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
  width: 100%;
  overflow: auto;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  display: block;
}
/* output div while it is collapsed */
div.output_collapsed {
  margin: 0px;
  padding: 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
div.out_prompt_overlay {
  height: 100%;
  padding: 0px 0.4em;
  position: absolute;
  border-radius: 2px;
}
div.out_prompt_overlay:hover {
  /* use inner shadow to get border that is computed the same on WebKit/FF */
  -webkit-box-shadow: inset 0 0 1px #000;
  box-shadow: inset 0 0 1px #000;
  background: rgba(240, 240, 240, 0.5);
}
div.output_prompt {
  color: #D84315;
}
/* This class is the outer container of all output sections. */
div.output_area {
  padding: 0px;
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.output_area .MathJax_Display {
  text-align: left !important;
}
div.output_area .rendered_html table {
  margin-left: 0;
  margin-right: 0;
}
div.output_area .rendered_html img {
  margin-left: 0;
  margin-right: 0;
}
div.output_area img,
div.output_area svg {
  max-width: 100%;
  height: auto;
}
div.output_area img.unconfined,
div.output_area svg.unconfined {
  max-width: none;
}
div.output_area .mglyph > img {
  max-width: none;
}
/* This is needed to protect the pre formating from global settings such
   as that of bootstrap */
.output {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.output_area {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
div.output_area pre {
  margin: 0;
  padding: 1px 0 1px 0;
  border: 0;
  vertical-align: baseline;
  color: black;
  background-color: transparent;
  border-radius: 0;
}
/* This class is for the output subarea inside the output_area and after
   the prompt div. */
div.output_subarea {
  overflow-x: auto;
  padding: 0.4em;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
  max-width: calc(100% - 14ex);
}
div.output_scroll div.output_subarea {
  overflow-x: visible;
}
/* The rest of the output_* classes are for special styling of the different
   output types */
/* all text output has this class: */
div.output_text {
  text-align: left;
  color: #000;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
}
/* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
div.output_stderr {
  background: #fdd;
  /* very light red background for stderr */
}
div.output_latex {
  text-align: left;
}
/* Empty output_javascript divs should have no height */
div.output_javascript:empty {
  padding: 0;
}
.js-error {
  color: darkred;
}
/* raw_input styles */
div.raw_input_container {
  line-height: 1.21429em;
  padding-top: 5px;
}
pre.raw_input_prompt {
  /* nothing needed here. */
}
input.raw_input {
  font-family: monospace;
  font-size: inherit;
  color: inherit;
  width: auto;
  /* make sure input baseline aligns with prompt */
  vertical-align: baseline;
  /* padding + margin = 0.5em between prompt and cursor */
  padding: 0em 0.25em;
  margin: 0em 0.25em;
}
input.raw_input:focus {
  box-shadow: none;
}
p.p-space {
  margin-bottom: 10px;
}
div.output_unrecognized {
  padding: 5px;
  font-weight: bold;
  color: red;
}
div.output_unrecognized a {
  color: inherit;
  text-decoration: none;
}
div.output_unrecognized a:hover {
  color: inherit;
  text-decoration: none;
}
.rendered_html {
  color: #000;
  /* any extras will just be numbers: */
}
.rendered_html em {
  font-style: italic;
}
.rendered_html strong {
  font-weight: bold;
}
.rendered_html u {
  text-decoration: underline;
}
.rendered_html :link {
  text-decoration: underline;
}
.rendered_html :visited {
  text-decoration: underline;
}
.rendered_html h1 {
  font-size: 185.7%;
  margin: 1.08em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h2 {
  font-size: 157.1%;
  margin: 1.27em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h3 {
  font-size: 128.6%;
  margin: 1.55em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h4 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h5 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h6 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h1:first-child {
  margin-top: 0.538em;
}
.rendered_html h2:first-child {
  margin-top: 0.636em;
}
.rendered_html h3:first-child {
  margin-top: 0.777em;
}
.rendered_html h4:first-child {
  margin-top: 1em;
}
.rendered_html h5:first-child {
  margin-top: 1em;
}
.rendered_html h6:first-child {
  margin-top: 1em;
}
.rendered_html ul:not(.list-inline),
.rendered_html ol:not(.list-inline) {
  padding-left: 2em;
}
.rendered_html ul {
  list-style: disc;
}
.rendered_html ul ul {
  list-style: square;
  margin-top: 0;
}
.rendered_html ul ul ul {
  list-style: circle;
}
.rendered_html ol {
  list-style: decimal;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin-top: 0;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
}
.rendered_html * + ul {
  margin-top: 1em;
}
.rendered_html * + ol {
  margin-top: 1em;
}
.rendered_html hr {
  color: black;
  background-color: black;
}
.rendered_html pre {
  margin: 1em 2em;
  padding: 0px;
  background-color: #fff;
}
.rendered_html code {
  background-color: #eff0f1;
}
.rendered_html p code {
  padding: 1px 5px;
}
.rendered_html pre code {
  background-color: #fff;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  color: #000;
  font-size: 100%;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: none;
  border-collapse: collapse;
  border-spacing: 0;
  color: black;
  font-size: 12px;
  table-layout: fixed;
}
.rendered_html thead {
  border-bottom: 1px solid black;
  vertical-align: bottom;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  text-align: right;
  vertical-align: middle;
  padding: 0.5em 0.5em;
  line-height: normal;
  white-space: normal;
  max-width: none;
  border: none;
}
.rendered_html th {
  font-weight: bold;
}
.rendered_html tbody tr:nth-child(odd) {
  background: #f5f5f5;
}
.rendered_html tbody tr:hover {
  background: rgba(66, 165, 245, 0.2);
}
.rendered_html * + table {
  margin-top: 1em;
}
.rendered_html p {
  text-align: left;
}
.rendered_html * + p {
  margin-top: 1em;
}
.rendered_html img {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.rendered_html * + img {
  margin-top: 1em;
}
.rendered_html img,
.rendered_html svg {
  max-width: 100%;
  height: auto;
}
.rendered_html img.unconfined,
.rendered_html svg.unconfined {
  max-width: none;
}
.rendered_html .alert {
  margin-bottom: initial;
}
.rendered_html * + .alert {
  margin-top: 1em;
}
[dir="rtl"] .rendered_html p {
  text-align: right;
}
div.text_cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.text_cell > div.prompt {
    display: none;
  }
}
div.text_cell_render {
  /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
  outline: none;
  resize: none;
  width: inherit;
  border-style: none;
  padding: 0.5em 0.5em 0.5em 0.4em;
  color: #000;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
a.anchor-link:link {
  text-decoration: none;
  padding: 0px 20px;
  visibility: hidden;
}
h1:hover .anchor-link,
h2:hover .anchor-link,
h3:hover .anchor-link,
h4:hover .anchor-link,
h5:hover .anchor-link,
h6:hover .anchor-link {
  visibility: visible;
}
.text_cell.rendered .input_area {
  display: none;
}
.text_cell.rendered .rendered_html {
  overflow-x: auto;
  overflow-y: hidden;
}
.text_cell.rendered .rendered_html tr,
.text_cell.rendered .rendered_html th,
.text_cell.rendered .rendered_html td {
  max-width: none;
}
.text_cell.unrendered .text_cell_render {
  display: none;
}
.text_cell .dropzone .input_area {
  border: 2px dashed #bababa;
  margin: -1px;
}
.cm-header-1,
.cm-header-2,
.cm-header-3,
.cm-header-4,
.cm-header-5,
.cm-header-6 {
  font-weight: bold;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
}
.cm-header-1 {
  font-size: 185.7%;
}
.cm-header-2 {
  font-size: 157.1%;
}
.cm-header-3 {
  font-size: 128.6%;
}
.cm-header-4 {
  font-size: 110%;
}
.cm-header-5 {
  font-size: 100%;
  font-style: italic;
}
.cm-header-6 {
  font-size: 100%;
  font-style: italic;
}
/*!
*
* IPython notebook webapp
*
*/
@media (max-width: 767px) {
  .notebook_app {
    padding-left: 0px;
    padding-right: 0px;
  }
}
#ipython-main-app {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook_panel {
  margin: 0px;
  padding: 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook {
  font-size: 14px;
  line-height: 20px;
  overflow-y: hidden;
  overflow-x: auto;
  width: 100%;
  /* This spaces the page away from the edge of the notebook area */
  padding-top: 20px;
  margin: 0px;
  outline: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  min-height: 100%;
}
@media not print {
  #notebook-container {
    padding: 15px;
    background-color: #fff;
    min-height: 0;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
@media print {
  #notebook-container {
    width: 100%;
  }
}
div.ui-widget-content {
  border: 1px solid #ababab;
  outline: none;
}
pre.dialog {
  background-color: #f7f7f7;
  border: 1px solid #ddd;
  border-radius: 2px;
  padding: 0.4em;
  padding-left: 2em;
}
p.dialog {
  padding: 0.2em;
}
/* Word-wrap output correctly.  This is the CSS3 spelling, though Firefox seems
   to not honor it correctly.  Webkit browsers (Chrome, rekonq, Safari) do.
 */
pre,
code,
kbd,
samp {
  white-space: pre-wrap;
}
#fonttest {
  font-family: monospace;
}
p {
  margin-bottom: 0;
}
.end_space {
  min-height: 100px;
  transition: height .2s ease;
}
.notebook_app > #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
@media not print {
  .notebook_app {
    background-color: #EEE;
  }
}
kbd {
  border-style: solid;
  border-width: 1px;
  box-shadow: none;
  margin: 2px;
  padding-left: 2px;
  padding-right: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
.jupyter-keybindings {
  padding: 1px;
  line-height: 24px;
  border-bottom: 1px solid gray;
}
.jupyter-keybindings input {
  margin: 0;
  padding: 0;
  border: none;
}
.jupyter-keybindings i {
  padding: 6px;
}
.well code {
  background-color: #ffffff;
  border-color: #ababab;
  border-width: 1px;
  border-style: solid;
  padding: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
/* CSS for the cell toolbar */
.celltoolbar {
  border: thin solid #CFCFCF;
  border-bottom: none;
  background: #EEE;
  border-radius: 2px 2px 0px 0px;
  width: 100%;
  height: 29px;
  padding-right: 4px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
  display: -webkit-flex;
}
@media print {
  .celltoolbar {
    display: none;
  }
}
.ctb_hideshow {
  display: none;
  vertical-align: bottom;
}
/* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
   Cell toolbars are only shown when the ctb_global_show class is also set.
*/
.ctb_global_show .ctb_show.ctb_hideshow {
  display: block;
}
.ctb_global_show .ctb_show + .input_area,
.ctb_global_show .ctb_show + div.text_cell_input,
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border-top-right-radius: 0px;
  border-top-left-radius: 0px;
}
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border: 1px solid #cfcfcf;
}
.celltoolbar {
  font-size: 87%;
  padding-top: 3px;
}
.celltoolbar select {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  width: inherit;
  font-size: inherit;
  height: 22px;
  padding: 0px;
  display: inline-block;
}
.celltoolbar select:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.celltoolbar select::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.celltoolbar select:-ms-input-placeholder {
  color: #999;
}
.celltoolbar select::-webkit-input-placeholder {
  color: #999;
}
.celltoolbar select::-ms-expand {
  border: 0;
  background-color: transparent;
}
.celltoolbar select[disabled],
.celltoolbar select[readonly],
fieldset[disabled] .celltoolbar select {
  background-color: #eeeeee;
  opacity: 1;
}
.celltoolbar select[disabled],
fieldset[disabled] .celltoolbar select {
  cursor: not-allowed;
}
textarea.celltoolbar select {
  height: auto;
}
select.celltoolbar select {
  height: 30px;
  line-height: 30px;
}
textarea.celltoolbar select,
select[multiple].celltoolbar select {
  height: auto;
}
.celltoolbar label {
  margin-left: 5px;
  margin-right: 5px;
}
.tags_button_container {
  width: 100%;
  display: flex;
}
.tag-container {
  display: flex;
  flex-direction: row;
  flex-grow: 1;
  overflow: hidden;
  position: relative;
}
.tag-container > * {
  margin: 0 4px;
}
.remove-tag-btn {
  margin-left: 4px;
}
.tags-input {
  display: flex;
}
.cell-tag:last-child:after {
  content: "";
  position: absolute;
  right: 0;
  width: 40px;
  height: 100%;
  /* Fade to background color of cell toolbar */
  background: linear-gradient(to right, rgba(0, 0, 0, 0), #EEE);
}
.tags-input > * {
  margin-left: 4px;
}
.cell-tag,
.tags-input input,
.tags-input button {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  box-shadow: none;
  width: inherit;
  font-size: inherit;
  height: 22px;
  line-height: 22px;
  padding: 0px 4px;
  display: inline-block;
}
.cell-tag:focus,
.tags-input input:focus,
.tags-input button:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.cell-tag::-moz-placeholder,
.tags-input input::-moz-placeholder,
.tags-input button::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.cell-tag:-ms-input-placeholder,
.tags-input input:-ms-input-placeholder,
.tags-input button:-ms-input-placeholder {
  color: #999;
}
.cell-tag::-webkit-input-placeholder,
.tags-input input::-webkit-input-placeholder,
.tags-input button::-webkit-input-placeholder {
  color: #999;
}
.cell-tag::-ms-expand,
.tags-input input::-ms-expand,
.tags-input button::-ms-expand {
  border: 0;
  background-color: transparent;
}
.cell-tag[disabled],
.tags-input input[disabled],
.tags-input button[disabled],
.cell-tag[readonly],
.tags-input input[readonly],
.tags-input button[readonly],
fieldset[disabled] .cell-tag,
fieldset[disabled] .tags-input input,
fieldset[disabled] .tags-input button {
  background-color: #eeeeee;
  opacity: 1;
}
.cell-tag[disabled],
.tags-input input[disabled],
.tags-input button[disabled],
fieldset[disabled] .cell-tag,
fieldset[disabled] .tags-input input,
fieldset[disabled] .tags-input button {
  cursor: not-allowed;
}
textarea.cell-tag,
textarea.tags-input input,
textarea.tags-input button {
  height: auto;
}
select.cell-tag,
select.tags-input input,
select.tags-input button {
  height: 30px;
  line-height: 30px;
}
textarea.cell-tag,
textarea.tags-input input,
textarea.tags-input button,
select[multiple].cell-tag,
select[multiple].tags-input input,
select[multiple].tags-input button {
  height: auto;
}
.cell-tag,
.tags-input button {
  padding: 0px 4px;
}
.cell-tag {
  background-color: #fff;
  white-space: nowrap;
}
.tags-input input[type=text]:focus {
  outline: none;
  box-shadow: none;
  border-color: #ccc;
}
.completions {
  position: absolute;
  z-index: 110;
  overflow: hidden;
  border: 1px solid #ababab;
  border-radius: 2px;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  line-height: 1;
}
.completions select {
  background: white;
  outline: none;
  border: none;
  padding: 0px;
  margin: 0px;
  overflow: auto;
  font-family: monospace;
  font-size: 110%;
  color: #000;
  width: auto;
}
.completions select option.context {
  color: #286090;
}
#kernel_logo_widget .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
[dir="rtl"] #kernel_logo_widget {
  float: left !important;
  float: left;
}
.modal .modal-body .move-path {
  display: flex;
  flex-direction: row;
  justify-content: space;
  align-items: center;
}
.modal .modal-body .move-path .server-root {
  padding-right: 20px;
}
.modal .modal-body .move-path .path-input {
  flex: 1;
}
#menubar {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  margin-top: 1px;
}
#menubar .navbar {
  border-top: 1px;
  border-radius: 0px 0px 2px 2px;
  margin-bottom: 0px;
}
#menubar .navbar-toggle {
  float: left;
  padding-top: 7px;
  padding-bottom: 7px;
  border: none;
}
#menubar .navbar-collapse {
  clear: left;
}
[dir="rtl"] #menubar .navbar-toggle {
  float: right;
}
[dir="rtl"] #menubar .navbar-collapse {
  clear: right;
}
[dir="rtl"] #menubar .navbar-nav {
  float: right;
}
[dir="rtl"] #menubar .nav {
  padding-right: 0px;
}
[dir="rtl"] #menubar .navbar-nav > li {
  float: right;
}
[dir="rtl"] #menubar .navbar-right {
  float: left !important;
}
[dir="rtl"] ul.dropdown-menu {
  text-align: right;
  left: auto;
}
[dir="rtl"] ul#new-menu.dropdown-menu {
  right: auto;
  left: 0;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
[dir="rtl"] i.menu-icon.pull-right {
  float: left !important;
  float: left;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
[dir="rtl"] ul#help_menu li a {
  padding-left: 2.2em;
}
[dir="rtl"] ul#help_menu li a i {
  margin-right: 0;
  margin-left: -1.2em;
}
[dir="rtl"] ul#help_menu li a i.pull-right {
  float: left !important;
  float: left;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -1px;
}
[dir="rtl"] .dropdown-submenu > .dropdown-menu {
  right: 100%;
  margin-right: -1px;
}
.dropdown-submenu:hover > .dropdown-menu {
  display: block;
}
.dropdown-submenu > a:after {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  display: block;
  content: "\f0da";
  float: right;
  color: #333333;
  margin-top: 2px;
  margin-right: -10px;
}
.dropdown-submenu > a:after.fa-pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.fa-pull-right {
  margin-left: .3em;
}
.dropdown-submenu > a:after.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
[dir="rtl"] .dropdown-submenu > a:after {
  float: left;
  content: "\f0d9";
  margin-right: 0;
  margin-left: -10px;
}
.dropdown-submenu:hover > a:after {
  color: #262626;
}
.dropdown-submenu.pull-left {
  float: none;
}
.dropdown-submenu.pull-left > .dropdown-menu {
  left: -100%;
  margin-left: 10px;
}
#notification_area {
  float: right !important;
  float: right;
  z-index: 10;
}
[dir="rtl"] #notification_area {
  float: left !important;
  float: left;
}
.indicator_area {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
[dir="rtl"] .indicator_area {
  float: left !important;
  float: left;
}
#kernel_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  border-left: 1px solid;
}
#kernel_indicator .kernel_indicator_name {
  padding-left: 5px;
  padding-right: 5px;
}
[dir="rtl"] #kernel_indicator {
  float: left !important;
  float: left;
  border-left: 0;
  border-right: 1px solid;
}
#modal_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
[dir="rtl"] #modal_indicator {
  float: left !important;
  float: left;
}
#readonly-indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  margin-top: 2px;
  margin-bottom: 0px;
  margin-left: 0px;
  margin-right: 0px;
  display: none;
}
.modal_indicator:before {
  width: 1.28571429em;
  text-align: center;
}
.edit_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f040";
}
.edit_mode .modal_indicator:before.fa-pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.fa-pull-right {
  margin-left: .3em;
}
.edit_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: ' ';
}
.command_mode .modal_indicator:before.fa-pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.fa-pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f10c";
}
.kernel_idle_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f111";
}
.kernel_busy_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f1e2";
}
.kernel_dead_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f127";
}
.kernel_disconnected_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.pull-right {
  margin-left: .3em;
}
.notification_widget {
  color: #777;
  z-index: 10;
  background: rgba(240, 240, 240, 0.5);
  margin-right: 4px;
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget:focus,
.notification_widget.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.notification_widget:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active:hover,
.notification_widget.active:hover,
.open > .dropdown-toggle.notification_widget:hover,
.notification_widget:active:focus,
.notification_widget.active:focus,
.open > .dropdown-toggle.notification_widget:focus,
.notification_widget:active.focus,
.notification_widget.active.focus,
.open > .dropdown-toggle.notification_widget.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  background-image: none;
}
.notification_widget.disabled:hover,
.notification_widget[disabled]:hover,
fieldset[disabled] .notification_widget:hover,
.notification_widget.disabled:focus,
.notification_widget[disabled]:focus,
fieldset[disabled] .notification_widget:focus,
.notification_widget.disabled.focus,
.notification_widget[disabled].focus,
fieldset[disabled] .notification_widget.focus {
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget .badge {
  color: #fff;
  background-color: #333;
}
.notification_widget.warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning:focus,
.notification_widget.warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.notification_widget.warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active:hover,
.notification_widget.warning.active:hover,
.open > .dropdown-toggle.notification_widget.warning:hover,
.notification_widget.warning:active:focus,
.notification_widget.warning.active:focus,
.open > .dropdown-toggle.notification_widget.warning:focus,
.notification_widget.warning:active.focus,
.notification_widget.warning.active.focus,
.open > .dropdown-toggle.notification_widget.warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  background-image: none;
}
.notification_widget.warning.disabled:hover,
.notification_widget.warning[disabled]:hover,
fieldset[disabled] .notification_widget.warning:hover,
.notification_widget.warning.disabled:focus,
.notification_widget.warning[disabled]:focus,
fieldset[disabled] .notification_widget.warning:focus,
.notification_widget.warning.disabled.focus,
.notification_widget.warning[disabled].focus,
fieldset[disabled] .notification_widget.warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.notification_widget.success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success:focus,
.notification_widget.success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.notification_widget.success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active:hover,
.notification_widget.success.active:hover,
.open > .dropdown-toggle.notification_widget.success:hover,
.notification_widget.success:active:focus,
.notification_widget.success.active:focus,
.open > .dropdown-toggle.notification_widget.success:focus,
.notification_widget.success:active.focus,
.notification_widget.success.active.focus,
.open > .dropdown-toggle.notification_widget.success.focus {
  color: #fff;
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fieldset[disabled] .notification_widget.success:focus,
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fieldset[disabled] .notification_widget.success.focus {
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.open > .dropdown-toggle.notification_widget.info:focus,
.notification_widget.info:active.focus,
.notification_widget.info.active.focus,
.open > .dropdown-toggle.notification_widget.info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
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fieldset[disabled] .notification_widget.info:hover,
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fieldset[disabled] .notification_widget.info:focus,
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fieldset[disabled] .notification_widget.info.focus {
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  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
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.notification_widget.danger.active:hover,
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.notification_widget.danger:active.focus,
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fieldset[disabled] .notification_widget.danger:focus,
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fieldset[disabled] .notification_widget.danger.focus {
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  border-color: #d43f3a;
}
.notification_widget.danger .badge {
  color: #d9534f;
  background-color: #fff;
}
div#pager {
  background-color: #fff;
  font-size: 14px;
  line-height: 20px;
  overflow: hidden;
  display: none;
  position: fixed;
  bottom: 0px;
  width: 100%;
  max-height: 50%;
  padding-top: 8px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  /* Display over codemirror */
  z-index: 100;
  /* Hack which prevents jquery ui resizable from changing top. */
  top: auto !important;
}
div#pager pre {
  line-height: 1.21429em;
  color: #000;
  background-color: #f7f7f7;
  padding: 0.4em;
}
div#pager #pager-button-area {
  position: absolute;
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  right: 20px;
}
div#pager #pager-contents {
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  height: 100%;
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div#pager #pager-contents #pager-container {
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  padding: 15px 0px;
  box-sizing: border-box;
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  -webkit-box-sizing: border-box;
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div#pager .ui-resizable-handle {
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}
div#pager .ui-resizable-handle::after {
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  left: 50%;
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  width: 30px;
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}
.quickhelp {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  line-height: 1.8em;
}
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  width: 21ex;
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}
.shortcut_descr {
  display: inline-block;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
span.save_widget {
  height: 30px;
  margin-top: 4px;
  display: flex;
  justify-content: flex-start;
  align-items: baseline;
  width: 50%;
  flex: 1;
}
span.save_widget span.filename {
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  line-height: 1em;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  text-overflow: ellipsis;
  overflow: hidden;
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span.save_widget span.filename:hover {
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}
[dir="rtl"] span.save_widget.pull-left {
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  float: right;
}
[dir="rtl"] span.save_widget span.filename {
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  margin-right: 16px;
}
span.checkpoint_status,
span.autosave_status {
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  white-space: nowrap;
  padding: 0 5px;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
    padding: 0 0 0 5px;
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  span.checkpoint_status,
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}
@media (min-width: 768px) and (max-width: 991px) {
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.toolbar {
  padding: 0px;
  margin-left: -5px;
  margin-top: 2px;
  margin-bottom: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.toolbar select,
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  vertical-align: middle;
  margin-right: 2px;
  margin-bottom: 0px;
  display: inline;
  font-size: 92%;
  margin-left: 0.3em;
  margin-right: 0.3em;
  padding: 0px;
  padding-top: 3px;
}
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}
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  margin-left: 5px;
}
.toolbar-btn-label {
  margin-left: 6px;
}
#maintoolbar {
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  margin-top: -8px;
  border: 0px;
  min-height: 27px;
  margin-left: 0px;
  padding-top: 11px;
  padding-bottom: 3px;
}
#maintoolbar .navbar-text {
  float: none;
  vertical-align: middle;
  text-align: right;
  margin-left: 5px;
  margin-right: 0px;
  margin-top: 0px;
}
.select-xs {
  height: 24px;
}
[dir="rtl"] .btn-group > .btn,
.btn-group-vertical > .btn {
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}
.pulse,
.dropdown-menu > li > a.pulse,
li.pulse > a.dropdown-toggle,
li.pulse.open > a.dropdown-toggle {
  background-color: #F37626;
  color: white;
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/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
/** WARNING IF YOU ARE EDITTING THIS FILE, if this is a .css file, It has a lot
 * of chance of beeing generated from the ../less/[samename].less file, you can
 * try to get back the less file by reverting somme commit in history
 **/
/*
 * We'll try to get something pretty, so we
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 */
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@-webkit-keyframes fadeOut {
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@-moz-keyframes fadeIn {
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@-webkit-keyframes fadeIn {
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  height: 200px;
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  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
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/*properties of tooltip before "expand"*/
.smalltooltip {
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  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
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}
.tooltipbuttons {
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  padding-right: 15px;
  top: 0px;
  right: 0px;
}
.tooltiptext {
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}
.ipython_tooltip {
  max-width: 700px;
  /*fade-in animation when inserted*/
  -webkit-animation: fadeOut 400ms;
  -moz-animation: fadeOut 400ms;
  animation: fadeOut 400ms;
  -webkit-animation: fadeIn 400ms;
  -moz-animation: fadeIn 400ms;
  animation: fadeIn 400ms;
  vertical-align: middle;
  background-color: #f7f7f7;
  overflow: visible;
  border: #ababab 1px solid;
  outline: none;
  padding: 3px;
  margin: 0px;
  padding-left: 7px;
  font-family: monospace;
  min-height: 50px;
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  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
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  border-radius: 0;
  font-size: 100%;
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  margin: 0px;
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  width: 40px;
  height: 16px;
  overflow: hidden;
  position: absolute;
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.pretooltiparrow:before {
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  border: 1px #ababab solid;
  z-index: 11;
  content: "";
  position: absolute;
  left: 15px;
  top: 10px;
  width: 25px;
  height: 25px;
  -webkit-transform: rotate(45deg);
  -moz-transform: rotate(45deg);
  -ms-transform: rotate(45deg);
  -o-transform: rotate(45deg);
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ul.typeahead-list i {
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[dir="rtl"] ul.typeahead-list i {
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ul.typeahead-list {
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.cmd-palette .modal-body {
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}
.cmd-palette form {
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}
.cmd-palette input {
  outline: none;
}
.no-shortcut {
  min-width: 20px;
  color: transparent;
}
[dir="rtl"] .no-shortcut.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .command-shortcut.pull-right {
  float: left !important;
  float: left;
}
.command-shortcut:before {
  content: "(command mode)";
  padding-right: 3px;
  color: #777777;
}
.edit-shortcut:before {
  content: "(edit)";
  padding-right: 3px;
  color: #777777;
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[dir="rtl"] .edit-shortcut.pull-right {
  float: left !important;
  float: left;
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#find-and-replace #replace-preview .match,
#find-and-replace #replace-preview .insert {
  background-color: #BBDEFB;
  border-color: #90CAF9;
  border-style: solid;
  border-width: 1px;
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}
[dir="ltr"] #find-and-replace .input-group-btn + .form-control {
  border-left: none;
}
[dir="rtl"] #find-and-replace .input-group-btn + .form-control {
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#find-and-replace #replace-preview {
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  overflow: auto;
}
#find-and-replace #replace-preview pre {
  padding: 5px 10px;
}
.terminal-app {
  background: #EEE;
}
.terminal-app #header {
  background: #fff;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
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.terminal-app .terminal {
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  float: left;
  font-family: monospace;
  color: white;
  background: black;
  padding: 0.4em;
  border-radius: 2px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
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.terminal-app .terminal,
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  font-size: 14px;
}
.terminal-app .terminal .xterm-rows {
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  background: white;
}
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  margin-top: 20px;
}
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<style type="text/css">
/* Overrides of notebook CSS for static HTML export */
body {
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div#notebook {
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}
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    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</span>
<span class="kn">from</span> <span class="nn">sklearn</span> <span class="kn">import</span> <span class="n">preprocessing</span>
<span class="kn">from</span> <span class="nn">sklearn</span> <span class="kn">import</span> <span class="n">model_selection</span>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="kn">import</span> <span class="n">cross_val_score</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="kn">import</span> <span class="n">accuracy_score</span><span class="p">,</span> <span class="n">f1_score</span><span class="p">,</span> <span class="n">classification_report</span><span class="p">,</span> <span class="n">precision_score</span><span class="p">,</span> <span class="n">recall_score</span><span class="p">,</span> <span class="n">confusion_matrix</span>
<span class="kn">from</span> <span class="nn">sklearn</span> <span class="kn">import</span> <span class="n">tree</span>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="kn">import</span> <span class="n">train_test_split</span>
<span class="kn">from</span> <span class="nn">imblearn.over_sampling</span> <span class="kn">import</span> <span class="n">RandomOverSampler</span><span class="p">,</span><span class="n">SMOTE</span><span class="p">,</span> <span class="n">ADASYN</span>
<span class="kn">from</span> <span class="nn">sklearn.ensemble</span> <span class="kn">import</span> <span class="n">RandomForestClassifier</span>
<span class="kn">from</span> <span class="nn">sklearn.linear_model</span> <span class="kn">import</span> <span class="n">LogisticRegression</span>
<span class="kn">from</span> <span class="nn">sklearn.tree</span> <span class="kn">import</span> <span class="n">DecisionTreeClassifier</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Import data &amp; cursory inspection of data</span>
<span class="n">strokedata_train</span><span class="o">=</span><span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;train_2v.csv&#39;</span><span class="p">)</span>
<span class="n">strokedata_test</span><span class="o">=</span><span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;test_2v.csv&#39;</span><span class="p">)</span>
<span class="n">strokedata_train</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>id</th>
      <th>gender</th>
      <th>age</th>
      <th>hypertension</th>
      <th>heart_disease</th>
      <th>ever_married</th>
      <th>work_type</th>
      <th>Residence_type</th>
      <th>avg_glucose_level</th>
      <th>bmi</th>
      <th>smoking_status</th>
      <th>stroke</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>30669</td>
      <td>Male</td>
      <td>3.0</td>
      <td>0</td>
      <td>0</td>
      <td>No</td>
      <td>children</td>
      <td>Rural</td>
      <td>95.12</td>
      <td>18.0</td>
      <td>NaN</td>
      <td>0</td>
    </tr>
    <tr>
      <th>1</th>
      <td>30468</td>
      <td>Male</td>
      <td>58.0</td>
      <td>1</td>
      <td>0</td>
      <td>Yes</td>
      <td>Private</td>
      <td>Urban</td>
      <td>87.96</td>
      <td>39.2</td>
      <td>never smoked</td>
      <td>0</td>
    </tr>
    <tr>
      <th>2</th>
      <td>16523</td>
      <td>Female</td>
      <td>8.0</td>
      <td>0</td>
      <td>0</td>
      <td>No</td>
      <td>Private</td>
      <td>Urban</td>
      <td>110.89</td>
      <td>17.6</td>
      <td>NaN</td>
      <td>0</td>
    </tr>
    <tr>
      <th>3</th>
      <td>56543</td>
      <td>Female</td>
      <td>70.0</td>
      <td>0</td>
      <td>0</td>
      <td>Yes</td>
      <td>Private</td>
      <td>Rural</td>
      <td>69.04</td>
      <td>35.9</td>
      <td>formerly smoked</td>
      <td>0</td>
    </tr>
    <tr>
      <th>4</th>
      <td>46136</td>
      <td>Male</td>
      <td>14.0</td>
      <td>0</td>
      <td>0</td>
      <td>No</td>
      <td>Never_worked</td>
      <td>Rural</td>
      <td>161.28</td>
      <td>19.1</td>
      <td>NaN</td>
      <td>0</td>
    </tr>
  </tbody>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Inspecting and cleaning data.</span>
<span class="c1">#drop id feature (not informative of stroke)</span>
<span class="n">strokedf_train</span><span class="o">=</span><span class="n">strokedata_train</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;id&#39;</span><span class="p">,</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">strokedf_train</span><span class="o">.</span><span class="n">describe</span><span class="p">()</span>
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>age</th>
      <th>hypertension</th>
      <th>heart_disease</th>
      <th>avg_glucose_level</th>
      <th>bmi</th>
      <th>stroke</th>
    </tr>
  </thead>
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    <tr>
      <th>count</th>
      <td>43400.000000</td>
      <td>43400.000000</td>
      <td>43400.000000</td>
      <td>43400.000000</td>
      <td>41938.000000</td>
      <td>43400.000000</td>
    </tr>
    <tr>
      <th>mean</th>
      <td>42.217894</td>
      <td>0.093571</td>
      <td>0.047512</td>
      <td>104.482750</td>
      <td>28.605038</td>
      <td>0.018041</td>
    </tr>
    <tr>
      <th>std</th>
      <td>22.519649</td>
      <td>0.291235</td>
      <td>0.212733</td>
      <td>43.111751</td>
      <td>7.770020</td>
      <td>0.133103</td>
    </tr>
    <tr>
      <th>min</th>
      <td>0.080000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>55.000000</td>
      <td>10.100000</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>25%</th>
      <td>24.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>77.540000</td>
      <td>23.200000</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>50%</th>
      <td>44.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>91.580000</td>
      <td>27.700000</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>75%</th>
      <td>60.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>112.070000</td>
      <td>32.900000</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>max</th>
      <td>82.000000</td>
      <td>1.000000</td>
      <td>1.000000</td>
      <td>291.050000</td>
      <td>97.600000</td>
      <td>1.000000</td>
    </tr>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">strokedf_test</span><span class="o">=</span><span class="n">strokedata_test</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;id&#39;</span><span class="p">,</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">strokedf_test</span><span class="o">.</span><span class="n">describe</span><span class="p">()</span>
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>age</th>
      <th>hypertension</th>
      <th>heart_disease</th>
      <th>avg_glucose_level</th>
      <th>bmi</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>count</th>
      <td>18601.000000</td>
      <td>18601.000000</td>
      <td>18601.000000</td>
      <td>18601.000000</td>
      <td>18010.000000</td>
    </tr>
    <tr>
      <th>mean</th>
      <td>42.056504</td>
      <td>0.093167</td>
      <td>0.048062</td>
      <td>104.386359</td>
      <td>28.545325</td>
    </tr>
    <tr>
      <th>std</th>
      <td>22.528018</td>
      <td>0.290674</td>
      <td>0.213903</td>
      <td>42.606714</td>
      <td>7.757092</td>
    </tr>
    <tr>
      <th>min</th>
      <td>0.080000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>55.000000</td>
      <td>10.200000</td>
    </tr>
    <tr>
      <th>25%</th>
      <td>24.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>77.550000</td>
      <td>23.300000</td>
    </tr>
    <tr>
      <th>50%</th>
      <td>43.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>91.830000</td>
      <td>27.700000</td>
    </tr>
    <tr>
      <th>75%</th>
      <td>60.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>112.310000</td>
      <td>32.800000</td>
    </tr>
    <tr>
      <th>max</th>
      <td>82.000000</td>
      <td>1.000000</td>
      <td>1.000000</td>
      <td>275.720000</td>
      <td>88.300000</td>
    </tr>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Inspect catagories within data to see nature of classifications and why count differences between features.</span>
<span class="nb">print</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">())</span>
<span class="nb">print</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;hypertension&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">())</span>
<span class="nb">print</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;heart_disease&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">())</span>
<span class="nb">print</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;ever_married&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">())</span>
<span class="nb">print</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;work_type&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">())</span>
<span class="nb">print</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;Residence_type&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">())</span>
<span class="nb">print</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;smoking_status&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">())</span>
<span class="nb">print</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;stroke&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">())</span>
<span class="nb">print</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">min</span><span class="p">())</span>
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<pre>[&#39;Male&#39; &#39;Female&#39; &#39;Other&#39;]
[0 1]
[0 1]
[&#39;No&#39; &#39;Yes&#39;]
[&#39;children&#39; &#39;Private&#39; &#39;Never_worked&#39; &#39;Self-employed&#39; &#39;Govt_job&#39;]
[&#39;Rural&#39; &#39;Urban&#39;]
[nan &#39;never smoked&#39; &#39;formerly smoked&#39; &#39;smokes&#39;]
[0 1]
0.08
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Notced null values, searching for others.</span>
<span class="c1">#identify number of null values in dataframe.</span>
<span class="n">strokedf_train</span><span class="o">.</span><span class="n">isnull</span><span class="p">()</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
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<pre>gender                   0
age                      0
hypertension             0
heart_disease            0
ever_married             0
work_type                0
Residence_type           0
avg_glucose_level        0
bmi                   1462
smoking_status       13292
stroke                   0
dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Deciding what to do with null features.</span>
<span class="c1">#Identify how many of the features with null values are not null.</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;BMI # avaliable (%):&quot;</span><span class="o">+</span><span class="nb">str</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">)</span><span class="o">-</span><span class="mi">1462</span><span class="p">)</span> <span class="o">+</span> <span class="s1">&#39;(&#39;</span><span class="o">+</span><span class="nb">str</span><span class="p">((</span><span class="nb">len</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">)</span><span class="o">-</span><span class="mi">1462</span><span class="p">)</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">))</span><span class="o">+</span><span class="s1">&#39;)&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;smoking # avaliable (%):&quot;</span><span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">)</span><span class="o">-</span><span class="mi">13292</span><span class="p">)</span> <span class="o">+</span><span class="s1">&#39;(&#39;</span><span class="o">+</span><span class="nb">str</span><span class="p">((</span><span class="nb">len</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">)</span><span class="o">-</span><span class="mi">13292</span><span class="p">)</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">))</span><span class="o">+</span><span class="s1">&#39;)&#39;</span><span class="p">)</span>
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<pre>BMI # avaliable (%):41938(0.9663133640552996)
smoking # avaliable (%):30108(0.6937327188940092)
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Considering removing entries with NULL bmi value (3% of data) or retaining.</span>
<span class="n">sns</span><span class="o">.</span><span class="n">boxplot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="s1">&#39;stroke&#39;</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="s1">&#39;bmi&#39;</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">strokedf_train</span><span class="p">)</span>
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<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0x7fd269e6eef0&gt;</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Inspect distribution of gender (Noticed &quot;Other&quot; classification).</span>
<span class="n">sns</span><span class="o">.</span><span class="n">countplot</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">])</span>
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<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0x7fd2676ee710&gt;</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Want to see &quot;Other&quot; contribution to data.</span>
<span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">count</span><span class="p">(</span><span class="s2">&quot;Other&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
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<pre>11</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Decide to remove &quot;Other&quot; from data on grounds that:</span>
<span class="c1">#1) Paucity of data (11 values) thereby difficult to reliably predict relation to stroke using ML.</span>
<span class="c1">#2) &quot;Other&quot; as a gender category in itself is ambiguous in that subject could be male to female, or female to male, or non-gender identifying. Thereby the potentialf or at least three different categories within that 11.</span>
<span class="c1">#3) Difficulty finding scientific literature which inspects causation between not identifying as a male or female and stroke prevalance.</span>
<span class="n">strokedf_train</span> <span class="o">=</span> <span class="n">strokedf_train</span><span class="p">[</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">]</span> <span class="o">!=</span> <span class="s2">&quot;Other&quot;</span><span class="p">]</span>
<span class="n">strokedf_test</span> <span class="o">=</span> <span class="n">strokedf_test</span><span class="p">[</span><span class="n">strokedf_test</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">]</span> <span class="o">!=</span> <span class="s2">&quot;Other&quot;</span><span class="p">]</span>
<span class="n">sns</span><span class="o">.</span><span class="n">countplot</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">])</span>
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<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0x7fd267656400&gt;</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Inspecting distribution of other features with regards to stroke .</span>
<span class="n">sns</span><span class="o">.</span><span class="n">catplot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="s1">&#39;hypertension&#39;</span><span class="p">,</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;count&#39;</span><span class="p">,</span><span class="n">data</span><span class="o">=</span><span class="n">strokedf_train</span><span class="p">,</span> <span class="n">hue</span><span class="o">=</span><span class="s1">&#39;stroke&#39;</span><span class="p">,</span> <span class="n">legend</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">loc</span><span class="o">=</span><span class="s1">&#39;upper right&#39;</span><span class="p">,</span> <span class="n">labels</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;No-stroke&#39;</span><span class="p">,</span> <span class="s1">&#39;Stroke&#39;</span><span class="p">])</span>
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<pre>&lt;matplotlib.legend.Legend at 0x7fd267483dd8&gt;</pre>
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<div class="prompt input_prompt">In&nbsp;[13]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">catplot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="s1">&#39;heart_disease&#39;</span><span class="p">,</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;count&#39;</span><span class="p">,</span><span class="n">hue</span><span class="o">=</span><span class="s1">&#39;stroke&#39;</span><span class="p">,</span> <span class="n">legend</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span><span class="n">data</span><span class="o">=</span><span class="n">strokedf_train</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">loc</span><span class="o">=</span><span class="s1">&#39;upper right&#39;</span><span class="p">,</span> <span class="n">labels</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;No-stroke&#39;</span><span class="p">,</span> <span class="s1">&#39;Stroke&#39;</span><span class="p">])</span>
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    <div class="prompt output_prompt">Out[13]:</div>


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<pre>&lt;matplotlib.legend.Legend at 0x7fd2674798d0&gt;</pre>
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<div class="prompt input_prompt">In&nbsp;[14]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">catplot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="s1">&#39;ever_married&#39;</span><span class="p">,</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;count&#39;</span><span class="p">,</span><span class="n">hue</span><span class="o">=</span><span class="s1">&#39;stroke&#39;</span><span class="p">,</span> <span class="n">legend</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span><span class="n">data</span><span class="o">=</span><span class="n">strokedf_train</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">loc</span><span class="o">=</span><span class="s1">&#39;upper right&#39;</span><span class="p">,</span> <span class="n">labels</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;No-stroke&#39;</span><span class="p">,</span> <span class="s1">&#39;Stroke&#39;</span><span class="p">])</span>
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    <div class="prompt output_prompt">Out[14]:</div>


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<pre>&lt;matplotlib.legend.Legend at 0x7fd26746cc88&gt;</pre>
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<div class="prompt input_prompt">In&nbsp;[15]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">catplot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="s1">&#39;work_type&#39;</span><span class="p">,</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;count&#39;</span><span class="p">,</span><span class="n">hue</span><span class="o">=</span><span class="s1">&#39;stroke&#39;</span><span class="p">,</span> <span class="n">legend</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span><span class="n">data</span><span class="o">=</span><span class="n">strokedf_train</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">loc</span><span class="o">=</span><span class="s1">&#39;upper right&#39;</span><span class="p">,</span> <span class="n">labels</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;No-stroke&#39;</span><span class="p">,</span> <span class="s1">&#39;Stroke&#39;</span><span class="p">])</span>
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    <div class="prompt output_prompt">Out[15]:</div>


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<pre>&lt;matplotlib.legend.Legend at 0x7fd266e9c198&gt;</pre>
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<div class="prompt input_prompt">In&nbsp;[16]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">catplot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="s1">&#39;Residence_type&#39;</span><span class="p">,</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;count&#39;</span><span class="p">,</span><span class="n">hue</span><span class="o">=</span><span class="s1">&#39;stroke&#39;</span><span class="p">,</span> <span class="n">legend</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span><span class="n">data</span><span class="o">=</span><span class="n">strokedf_train</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">loc</span><span class="o">=</span><span class="s1">&#39;upper right&#39;</span><span class="p">,</span> <span class="n">labels</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;No-stroke&#39;</span><span class="p">,</span> <span class="s1">&#39;Stroke&#39;</span><span class="p">])</span>
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    <div class="prompt output_prompt">Out[16]:</div>


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<pre>&lt;matplotlib.legend.Legend at 0x7fd2670f6b38&gt;</pre>
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TcD96W3y4H9i5p2TzWaqa8B9pTUIV11F7c3M2vXWvWKW9I+RW9PBhqeOJkJDJfUUVIvoDfwBPAk0Ds9QbILhRuYMyMigLnAqWn7UcAvWuMczMwqrWxX3JJmAAOBbpLqgcuAgZL6AQEsA84DiIhnJd0FPAdsAMZHxMa0nwuAWUAVMCUink2H+Bpwh6SJwNPALeU6FzOztqRswR0RI5ooNxuuEXElcGUT9fuB+5uoL6Xw1ImZ2Q7Fn5w0M8uMg9vMLDMObjOzzDi4zcwy4+A2M8uMg9vMLDMObjOzzDi4zcwy4+A2M8uMg9vMLDMObjOzzDi4zcwy4+A2M8uMg9vMLDMObjOzzDi4zcwy4+A2M8uMg9vMLDMObjOzzDi4zcwy4+A2M8uMg9vMLDMObjOzzDi4zcwy4+A2M8tM2YJb0hRJKyUtLqpdJen3khZK+pmkPVO9p6R3JNWm101F2xwhaZGkOknXS1Kq7yVptqQX0s8u5ToXM7O2pJxX3FOBIY1qs4E+EXEY8H/A14vW/SEi+qXXuKL6JOBcoHd6NezzUmBORPQG5qT3ZmbtXtmCOyIeAdY2qj0YERvS28eB7lvah6R9gM4R8XhEBHAb8MW0eigwLS1PK6qbmbVrlRzjPhv4VdH7XpKelvSwpGNTbT+gvqhNfaoB7B0RK9LyK8DezR1I0lhJ8yXNX7VqVQt138ysMioS3JK+AWwApqfSCqBHRBwOXAz8RFLnUveXrsZjC+snR0RNRNRUV1dvR8/NzCqvQ2sfUNJo4J+AQSlwiYj3gPfS8lOS/gAcDCznw8Mp3VMN4FVJ+0TEijSksrKVTsHMrKJa9Ypb0hDgq8BJEfF2Ub1aUlVaPpDCTcilaSjkDUkD0tMkI4FfpM1mAqPS8qiiuplZu1a2K25JM4CBQDdJ9cBlFJ4i6QjMTk/1PZ6eIPl74ApJfwHeB8ZFRMONzfMpPKGyK4Ux8YZx8e8Cd0k6B3gROL1c52Jm1paULbgjYkQT5VuaaXsPcE8z6+YDfZqorwEGbU8fzcxy5E9OmpllpqTgljSnlJqZmZXfFodKJHUCdqMwTt0FUFrVmQ+epzYzs1a0tTHu84CLgH2Bp/gguN8AfljGfpmZWTO2GNwRcR1wnaQJEXFDK/XJzMy2oKSnSiLiBklHAz2Lt4mI28rULzMza0ZJwS3pduATQC2wMZUbJn0yM7NWVOpz3DXAoQ0fUTczs8op9TnuxcBfl7MjZmZWmlKvuLsBz0l6gjQZFEBEnFSWXpmZWbNKDe7Ly9kJMzMrXalPlTxc7o6YmVlpSn2q5E0++KKCXYCdgbciouQvOzAzs5ZR6hX3Hg3LaV7socCAcnXKzMyat82zA0bBz4HPl6E/Zma2FaUOlXyp6O1OFJ7rfrcsPTIzsy0q9amSLxQtbwCWURguMTOzVlbqGPeYcnfEzMxKU+oXKXSX9DNJK9PrHkndt76lmZm1tFJvTt5K4VvV902vX6aamZm1slKDuzoibo2IDek1FaguY7/MzKwZpQb3GklnSqpKrzOBNeXsmJmZNa3U4D4bOB14BVgBnAqMLlOfzMxsC0p9HPAKYFREvAYgaS/gagqBbmZmrajUK+7DGkIbICLWAoeXp0tmZrYlpQb3TpK6NLxJV9xbvVqXNCU9Pri4eFtJsyW9kH52SXVJul5SnaSFkvoXbTMqtX9B0qii+hGSFqVtrk/zqJiZtWulBvc1wDxJ35b0beC3wPdL2G4qMKRR7VJgTkT0Buak9wAnAL3TaywwCTb9I3EZcBRwJHBZ0T8ik4Bzi7ZrfCwzs3anpOBO3+b+JeDV9PpSRNxewnaPAGsblYcC09LyNOCLRfXb0iRWjwN7StqHwmRWsyNibRqumQ0MSes6R8Tj6bswbyval5lZu1XqzUki4jnguRY45t4RsSItvwLsnZb3A14qalefaluq1zdR34yksRSu4unRo8d2dt/MrLK2eVrXlpSulMv+zfERMTkiaiKiprranxsys7xVIrhfTcMcpJ8rU305sH9Ru+6ptqV69ybqZmbtWiWCeybQ8GTIKOAXRfWR6emSAcC6NKQyCxgsqUu6KTkYmJXWvSFpQHqaZGTRvszM2q2Sx7g/CkkzgIFAN0n1FJ4O+S5wl6RzgBcpfCIT4H7gRKAOeBsYA4VnxtOTLE+mdlek58gBzqfw5MquwK/Sy8ysXStrcEfEiGZWDWqibQDjm9nPFGBKE/X5QJ/t6aOZWW4qenPSzMy2nYPbzCwzDm4zs8w4uM3MMuPgNjPLjIPbzCwzDm4zs8w4uM3MMuPgNjPLjIPbzCwzDm4zs8w4uM3MMuPgNjPLjIPbzCwzDm4zs8w4uM3MMuPgNjPLjIPbzCwzDm4zs8w4uM3MMuPgNjPLjIPbzCwzDm4zs8w4uM3MMuPgNjPLTKsHt6RDJNUWvd6QdJGkyyUtL6qfWLTN1yXVSVoi6fNF9SGpVifp0tY+FzOzSujQ2geMiCVAPwBJVcBy4GfAGODaiLi6uL2kQ4HhwKeAfYFfSzo4rb4ROB6oB56UNDMinmuVEzEzq5BWD+5GBgF/iIgXJTXXZihwR0S8B/xRUh1wZFpXFxFLASTdkdo6uM2sXav0GPdwYEbR+wskLZQ0RVKXVNsPeKmoTX2qNVffjKSxkuZLmr9q1aqW672ZWQVULLgl7QKcBPw0lSYBn6AwjLICuKaljhURkyOiJiJqqqurW2q3ZmYVUcmhkhOABRHxKkDDTwBJNwP3pbfLgf2LtuueamyhbmbWblVyqGQERcMkkvYpWncysDgtzwSGS+ooqRfQG3gCeBLoLalXunofntqambVrFbnilvQxCk+DnFdU/r6kfkAAyxrWRcSzku6icNNxAzA+Ijam/VwAzAKqgCkR8WyrnYSZWYVUJLgj4i2ga6PaWVtofyVwZRP1+4H7W7yDZmZtWKWfKjEzs23k4DYzy4yD28wsMw5uM7PMOLjNzDLj4DYzy4yD28wsMw5uM7PMOLjNzDLj4DYzy4yD28wsMw5uM7PMOLjNzDLj4DYzy4yD28wsMw5uM7PMOLjNzDLj4DYzy4yD28wsMw5uM7PMOLjNzDLj4DYzy4yD28wsMw5uM7PMOLjNzDJTseCWtEzSIkm1kuan2l6SZkt6If3skuqSdL2kOkkLJfUv2s+o1P4FSaMqdT5mZq2l0lfcx0VEv4ioSe8vBeZERG9gTnoPcALQO73GApOgEPTAZcBRwJHAZQ1hb2bWXlU6uBsbCkxLy9OALxbVb4uCx4E9Je0DfB6YHRFrI+I1YDYwpLU7bWbWmioZ3AE8KOkpSWNTbe+IWJGWXwH2Tsv7AS8VbVufas3VzczarQ4VPPbfRcRySX8FzJb0++KVERGSoiUOlP5hGAvQo0ePltilmVnFVOyKOyKWp58rgZ9RGKN+NQ2BkH6uTM2XA/sXbd491ZqrNz7W5IioiYia6urqlj4VM7NWVZHglvQxSXs0LAODgcXATKDhyZBRwC/S8kxgZHq6ZACwLg2pzAIGS+qSbkoOTjUzs3arUkMlewM/k9TQh59ExAOSngTuknQO8CJwemp/P3AiUAe8DYwBiIi1kr4NPJnaXRERa1vvNMzMWl9FgjsilgKfbqK+BhjURD2A8c3sawowpaX7aGbWVrW1xwHNzGwrHNxmZplxcJuZZcbBbWaWGQe3mVlmHNxmZplxcJuZZcbBbWaWGQe3mVlmHNxmZplxcJuZZcbBbWaWGQe3mVlmHNxmZplxcJuZZcbBbWaWGQe3mVlmHNxmZplxcJuZZcbBbWaWGQe3mVlmHNxmZplxcJuZZcbBbWaWGQe3mVlmHNxmZplp9eCWtL+kuZKek/SspK+k+uWSlkuqTa8Ti7b5uqQ6SUskfb6oPiTV6iRd2trnYmZWCR0qcMwNwCURsUDSHsBTkmandddGxNXFjSUdCgwHPgXsC/xa0sFp9Y3A8UA98KSkmRHxXKuchZlZhbR6cEfECmBFWn5T0vPAflvYZChwR0S8B/xRUh1wZFpXFxFLASTdkdo6uM2sXavoGLeknsDhwO9S6QJJCyVNkdQl1fYDXirarD7Vmqs3dZyxkuZLmr9q1aoWPAMzs9ZXseCWtDtwD3BRRLwBTAI+AfSjcEV+TUsdKyImR0RNRNRUV1e31G7NzCqiEmPcSNqZQmhPj4h7ASLi1aL1NwP3pbfLgf2LNu+eamyhbmbWblXiqRIBtwDPR8QPiur7FDU7GViclmcCwyV1lNQL6A08ATwJ9JbUS9IuFG5gzmyNczAzq6RKXHEfA5wFLJJUm2r/BoyQ1A8IYBlwHkBEPCvpLgo3HTcA4yNiI4CkC4BZQBUwJSKebc0TMTOrhEo8VfIooCZW3b+Fba4Ermyifv+WtjMza4/8yUkzs8w4uM3MMuPgNjPLjIPbzCwzDm4zs8w4uM3MMuPgNjPLjIPbzCwzDm4zs8w4uM3MMuPgNjPLjIPbzCwzDm4zs8w4uM3MMuPgNjPLjIPbzCwzDm4zs8w4uM3MMuPgNjPLjIPbzCwzDm4zs8w4uM3MMtOh0h0wsx3Ln67oW+kutKoe/7Goxffp4LZm+S+YWdvkoRIzs8xkH9yShkhaIqlO0qWV7o+ZWbllHdySqoAbgROAQ4ERkg6tbK/MzMor6+AGjgTqImJpRPwZuAMYWuE+mZmVVe43J/cDXip6Xw8c1biRpLHA2PR2vaQlrdC37B0A3YDVle5Hq7lMle7BDsG/V9vkgYgY0riYe3CXJCImA5Mr3Y/cSJofETWV7oe1L/692n65D5UsB/Yvet891czM2q3cg/tJoLekXpJ2AYYDMyvcJzOzssp6qCQiNki6AJgFVAFTIuLZCnerPfHwkpWDf6+2kyKi0n0wM7NtkPtQiZnZDsfBbWaWGQf3DkTSRkm1khZL+qWkPVtw35dL+peW2p+1bZJ6SlrcqNbk74CkqZJObb3etX8O7h3LOxHRLyL6AGuB8duycZpiwKxkkrJ+AKKtcnDvuOZR+OQpkgZKuq9hhaQfShqdlpdJ+p6kBcBpks6V9KSkZyTdI2m3ivTe2ixJD0n6T0nzga+k8j9Imi/p/yT9U2rXU9JvJC1Ir6NTfWDax92Sfi9puiR/rLWI/zXcAaUr50HALSVusiYi+qdtu0bEzWl5InAOcENZOmo526Xh05GSpgI9Kcwt9AlgrqSDgJXA8RHxrqTewAyg4ROVhwOfAl4GHgOOAR5tzRNoy3zFvWPZVVIt8AqwNzC7xO3uLFruk66SFgFnUPjLZTue5p4jbqjf2ah+V0S8HxEvAEuBvwF2Bm5Ov0s/pTDDZ4MnIqI+It4HaikEvyUO7h3LOxHRDzgAEB+McW/gw78LnRpt91bR8lTggojoC3yriba2Y1gDdGlU24sPJo96q9G6xkEfwD8DrwKfpnClvUvR+veKljfi0YEPcXDvgCLibeBC4JJ08+hF4FBJHdOTJoO2sPkewApJO1O44rYdUESsp/B78DkASXsBQ2h+OOM0STtJ+gRwILAE+DiwIl1Vn0Xh089WAgf3DioingYWAiMi4iXgLmBx+vn0Fjb9d+B3FMYdf1/uflqbNhL49zT89r/AtyLiD820/RPwBPArYFxEvAv8FzBK0jMUhk4aX6VbM/yRdzOzzPiK28wsMw5uM7PMOLjNzDLj4DYzy4yD28wsMw5uM7PMOLgtGy01La2k/5Z0aBP10ZJ+uP09/WjS5EpHV+r4lg8Ht+Vku6albRAR/y8inmvZrrWIgYCD27bKwW252jQtLYCkf03TzS6U9K1U+5ik/0lT0C6WNCzVH5LUMHPdmDTV6BMUZqBr2F91mrb2yfQ6JtUvlzQl7WOppAuLthmZjv+MpNu3tJ/GJPUExgH/nP5XcaykP6apBZDUueF9OvZ1Rf/7OLLofKdIekLS05KGttwft7UlnrjFstN4WlpJg4HeFKYNFTBT0t8D1cDLEfGPqd3HG+1nHwoTZR0BrAPm8sHH/a8Dro2IRyX1AGYBn0zr/gY4jsK8LUskTQIOBr4JHB0Rq9PcHVvbzyYRsUzSTcD6iLg69e8h4B+BnwPDgXsj4i9paurdIqJfOs8pQB/gG8D/RsTZaRjpCUm/jgh/lLydcXBbThqmpd0PeJ4PpqUdnF4Nobs7hSD/DXCNpO8B90XEb+ihuP8AAAHfSURBVBrt7yjgoYhYBSDpTgoBDPAPFCbeamjbWdLuafl/IuI94D1JKylMkfs54KcRsRogItZuaT9pkqat+W/gqxSCewxwbtG6Gek4j6Sr8T3Tn8FJ+uDrwzoBPdKflbUjDm7LyTvpKnM3Cleu44HrKVxlfyciftR4A0n9gROBiZLmRMQVJR5rJ2BAmgypeH+wbVOONrmfUkTEY+lbYgYCVRFR/B2PTU2TKuCUiFiyrceyvHiM27LTxLS0s4CzG66IJe0n6a8k7Qu8HRE/Bq4C+jfa1e+Az0rqmsaSTyta9yAwoeGNpH5b6db/Upi6tGtq3zBUsi37eZPC8Eux24CfALc2qjeM1/8dsC4i1lH4c5ig9K+LpMO30mfLlIPbstRoWtoHKYTbvPRtKndTCMC+FMZ5a4HLgImN9rECuJzCjc7H+PCQwoVATbrZ+ByFG4db6s+zwJXAw2ma0h98hP38Eji54eZkqk2n8IUFMxq1fVfS08BNFL4+DuDbFL5VZqGkZ9N7a4c8ratZGybpVGBoRJxVVHsI+JeImF+xjllFeYzbrI2SdANwAoUxerNNfMVt1sokjQG+0qj8WER8pA8U2Y7HwW1mlhnfnDQzy4yD28wsMw5uM7PMOLjNzDLz/wFvbt4j+T8ZuAAAAABJRU5ErkJggg==
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<div class="prompt input_prompt">In&nbsp;[17]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">catplot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="s1">&#39;smoking_status&#39;</span><span class="p">,</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;count&#39;</span><span class="p">,</span><span class="n">hue</span><span class="o">=</span><span class="s1">&#39;stroke&#39;</span><span class="p">,</span> <span class="n">legend</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span><span class="n">data</span><span class="o">=</span><span class="n">strokedf_train</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">loc</span><span class="o">=</span><span class="s1">&#39;upper right&#39;</span><span class="p">,</span> <span class="n">labels</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;No-stroke&#39;</span><span class="p">,</span> <span class="s1">&#39;Stroke&#39;</span><span class="p">])</span>
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    <div class="prompt output_prompt">Out[17]:</div>


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<pre>&lt;matplotlib.legend.Legend at 0x7fd2673d2710&gt;</pre>
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<div class="prompt input_prompt">In&nbsp;[18]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">distplot</span><span class="p">(</span><span class="n">strokedf_train</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;stroke&#39;</span><span class="p">]</span><span class="o">==</span><span class="mi">0</span><span class="p">][</span><span class="s1">&#39;age&#39;</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;No stroke&#39;</span><span class="p">,</span><span class="n">norm_hist</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="mi">20</span><span class="p">)</span>
<span class="n">sns</span><span class="o">.</span><span class="n">distplot</span><span class="p">(</span><span class="n">strokedf_train</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;stroke&#39;</span><span class="p">]</span><span class="o">==</span><span class="mi">1</span><span class="p">][</span><span class="s1">&#39;age&#39;</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Stroke&#39;</span><span class="p">,</span><span class="n">norm_hist</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="mi">20</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
</pre></div>

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    <div class="prompt output_prompt">Out[18]:</div>


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<pre>&lt;matplotlib.legend.Legend at 0x7fd266fe1438&gt;</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Decesion to remove samples with age less than 16 because:</span>
<span class="c1">#1) Many of the features in the data are strictly dependent on age being over 16 (marriage, smoking, employment).</span>
<span class="c1">#2) Research investigating causation between age and stroke typically omits ages under 15.</span>
<span class="c1">#3) Science has demonstrated that genetic predisposition (e.g. sickle cell anemia), environment (e.g. carbon monoxide levels), and conginental conditions are related to stroke in children. </span>
<span class="c1">#https://www.chp.edu/our-services/brain/neurology/stroke-program/causes-and-symptoms.</span>
<span class="n">strokedf_train</span> <span class="o">=</span> <span class="n">strokedf_train</span><span class="p">[</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">16</span><span class="p">]</span>
<span class="n">strokedf_test</span> <span class="o">=</span> <span class="n">strokedf_test</span><span class="p">[</span><span class="n">strokedf_test</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">16</span><span class="p">]</span>
<span class="n">sns</span><span class="o">.</span><span class="n">distplot</span><span class="p">(</span><span class="n">strokedf_train</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;stroke&#39;</span><span class="p">]</span><span class="o">==</span><span class="mi">0</span><span class="p">][</span><span class="s1">&#39;age&#39;</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;No stroke&#39;</span><span class="p">,</span><span class="n">norm_hist</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="mi">20</span><span class="p">)</span>
<span class="n">sns</span><span class="o">.</span><span class="n">distplot</span><span class="p">(</span><span class="n">strokedf_train</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;stroke&#39;</span><span class="p">]</span><span class="o">==</span><span class="mi">1</span><span class="p">][</span><span class="s1">&#39;age&#39;</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Stroke&#39;</span><span class="p">,</span><span class="n">norm_hist</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="mi">20</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
</pre></div>

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    <div class="prompt output_prompt">Out[19]:</div>


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<pre>&lt;matplotlib.legend.Legend at 0x7fd2673d23c8&gt;</pre>
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    <div class="prompt"></div>


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<div class="prompt input_prompt">In&nbsp;[20]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Non-uniform distribution of ages.</span>
<span class="c1">#Considering grouping data by age.</span>
<span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">nunique</span><span class="p">()</span>
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<pre>66</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">distplot</span><span class="p">(</span><span class="n">strokedf_train</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;stroke&#39;</span><span class="p">]</span><span class="o">==</span><span class="mi">0</span><span class="p">][</span><span class="s1">&#39;avg_glucose_level&#39;</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;No stroke&#39;</span><span class="p">,</span><span class="n">norm_hist</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="mi">20</span><span class="p">)</span>
<span class="n">sns</span><span class="o">.</span><span class="n">distplot</span><span class="p">(</span><span class="n">strokedf_train</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;stroke&#39;</span><span class="p">]</span><span class="o">==</span><span class="mi">1</span><span class="p">][</span><span class="s1">&#39;avg_glucose_level&#39;</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Stroke&#39;</span><span class="p">,</span><span class="n">norm_hist</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="mi">20</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
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<pre>&lt;matplotlib.legend.Legend at 0x7fd2675cb908&gt;</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Data shows bimodal distribution for both stroke cases.</span>
<span class="c1">#Considering grouping data by blood glucose risk groups.</span>
<span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;avg_glucose_level&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">nunique</span><span class="p">()</span>
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<pre>12112</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">distplot</span><span class="p">(</span><span class="n">strokedf_train</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;stroke&#39;</span><span class="p">]</span><span class="o">==</span><span class="mi">0</span><span class="p">][</span><span class="s1">&#39;bmi&#39;</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;No stroke&#39;</span><span class="p">,</span> <span class="n">norm_hist</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="mi">20</span><span class="p">)</span>
<span class="n">sns</span><span class="o">.</span><span class="n">distplot</span><span class="p">(</span><span class="n">strokedf_train</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;stroke&#39;</span><span class="p">]</span><span class="o">==</span><span class="mi">1</span><span class="p">][</span><span class="s1">&#39;bmi&#39;</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Stroke&#39;</span><span class="p">,</span> <span class="n">norm_hist</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="mi">20</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
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<pre>&lt;matplotlib.legend.Legend at 0x7fd267509710&gt;</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Data slightly right skewed.</span>
<span class="c1">#Considering organising BMI by groups.</span>
<span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">nunique</span><span class="p">()</span>
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<pre>530</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Chose to retain BMI and replaced null values with median due to number of outliers.</span>
<span class="c1">#Considered predicting BMI however do not possess metrics to explicitly calculate. </span>
<span class="c1">#Consider possibility of predicting BMI using remaining data albeit may converge on predisposed bias in data.</span>
<span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">median</span><span class="p">(),</span> <span class="n">inplace</span><span class="o">=</span> <span class="kc">True</span><span class="p">)</span>
<span class="n">strokedf_test</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">median</span><span class="p">(),</span> <span class="n">inplace</span><span class="o">=</span> <span class="kc">True</span><span class="p">)</span>
<span class="c1">#Considering removing data with smoking status or replacing with unknown.</span>
<span class="c1">#However null smoking status constitutes 30% of data.</span>
<span class="c1">#Chose to retain and assign &quot;unknown&quot;.</span>
<span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;smoking_status&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="n">value</span><span class="o">=</span><span class="s1">&#39;unknown&#39;</span><span class="p">,</span><span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">strokedf_test</span><span class="p">[</span><span class="s1">&#39;smoking_status&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="n">value</span><span class="o">=</span><span class="s1">&#39;unknown&#39;</span><span class="p">,</span><span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Checking if null values remain</span>
<span class="n">strokedf_train</span><span class="o">.</span><span class="n">isnull</span><span class="p">()</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
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<pre>gender               0
age                  0
hypertension         0
heart_disease        0
ever_married         0
work_type            0
Residence_type       0
avg_glucose_level    0
bmi                  0
smoking_status       0
stroke               0
dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Checking values across dataframe</span>
<span class="n">strokedf_train</span><span class="o">.</span><span class="n">info</span><span class="p">()</span>
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<pre>&lt;class &#39;pandas.core.frame.DataFrame&#39;&gt;
Int64Index: 36325 entries, 1 to 43399
Data columns (total 11 columns):
 #   Column             Non-Null Count  Dtype  
---  ------             --------------  -----  
 0   gender             36325 non-null  object 
 1   age                36325 non-null  float64
 2   hypertension       36325 non-null  int64  
 3   heart_disease      36325 non-null  int64  
 4   ever_married       36325 non-null  object 
 5   work_type          36325 non-null  object 
 6   Residence_type     36325 non-null  object 
 7   avg_glucose_level  36325 non-null  float64
 8   bmi                36325 non-null  float64
 9   smoking_status     36325 non-null  object 
 10  stroke             36325 non-null  int64  
dtypes: float64(3), int64(3), object(5)
memory usage: 3.3+ MB
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Paucity of data relating to stroke occurances, caution of potential overfitting to non-stroke due to imbalance in data.</span>
<span class="n">sns</span><span class="o">.</span><span class="n">countplot</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;stroke&#39;</span><span class="p">])</span>
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<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0x7fd267128470&gt;</pre>
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<img src="data:image/png;base64,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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#For building a decesion tree features need to be numerical</span>
<span class="n">enc</span><span class="o">=</span><span class="n">preprocessing</span><span class="o">.</span><span class="n">LabelEncoder</span><span class="p">()</span>

<span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">])</span>
<span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;ever_married&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;ever_married&#39;</span><span class="p">])</span>
<span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;work_type&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;work_type&#39;</span><span class="p">])</span>
<span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;Residence_type&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;Residence_type&#39;</span><span class="p">])</span>
<span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;smoking_status&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;smoking_status&#39;</span><span class="p">])</span>
<span class="n">strokedf_test</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedf_test</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">])</span>
<span class="n">strokedf_test</span><span class="p">[</span><span class="s1">&#39;ever_married&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedf_test</span><span class="p">[</span><span class="s1">&#39;ever_married&#39;</span><span class="p">])</span>
<span class="n">strokedf_test</span><span class="p">[</span><span class="s1">&#39;work_type&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedf_test</span><span class="p">[</span><span class="s1">&#39;work_type&#39;</span><span class="p">])</span>
<span class="n">strokedf_test</span><span class="p">[</span><span class="s1">&#39;Residence_type&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedf_test</span><span class="p">[</span><span class="s1">&#39;Residence_type&#39;</span><span class="p">])</span>
<span class="n">strokedf_test</span><span class="p">[</span><span class="s1">&#39;smoking_status&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedf_test</span><span class="p">[</span><span class="s1">&#39;smoking_status&#39;</span><span class="p">])</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Clear imbalance in stroke data as mentioned earlier, going to address now before ML to mitigate overfitting.</span>
<span class="nb">print</span><span class="p">(</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;stroke&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">())</span>
<span class="c1">#ros=RandomOverSampler(random_state=77)</span>
<span class="n">smote</span> <span class="o">=</span> <span class="n">SMOTE</span><span class="p">(</span><span class="n">random_state</span><span class="o">=</span><span class="mi">77</span><span class="p">)</span>
<span class="c1">#Use ROSE method</span>
<span class="n">X_resamp</span><span class="p">,</span> <span class="n">y_resamp</span><span class="o">=</span><span class="n">smote</span><span class="o">.</span><span class="n">fit_resample</span><span class="p">(</span><span class="n">strokedf_train</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span><span class="n">strokedf_train</span><span class="o">.</span><span class="n">columns</span><span class="o">!=</span><span class="s1">&#39;stroke&#39;</span><span class="p">],</span><span class="n">strokedf_train</span><span class="p">[</span><span class="s1">&#39;stroke&#39;</span><span class="p">])</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">format</span><span class="p">(</span><span class="n">X_resamp</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">format</span><span class="p">(</span><span class="n">y_resamp</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
<span class="n">y_resamp</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
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<pre>0    35544
1      781
Name: stroke, dtype: int64
(71088, 10)
(71088,)
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<pre>1    35544
0    35544
Name: stroke, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Split and train data</span>
<span class="n">X_train</span><span class="p">,</span> <span class="n">X_test</span><span class="p">,</span> <span class="n">y_train</span><span class="p">,</span> <span class="n">y_test</span> <span class="o">=</span> <span class="n">train_test_split</span><span class="p">(</span><span class="n">X_resamp</span><span class="p">,</span> <span class="n">y_resamp</span><span class="p">,</span> <span class="n">test_size</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">77</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Train and fit Logistic Regression model.</span>
<span class="n">LoRmod</span><span class="o">=</span><span class="n">LogisticRegression</span><span class="p">(</span><span class="n">max_iter</span><span class="o">=</span><span class="mi">10000</span><span class="p">)</span>
<span class="n">LoRmod</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span><span class="n">y_train</span><span class="p">)</span>
<span class="c1">#Score LR training</span>
<span class="n">LoRmod</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">y_train</span><span class="p">)</span>
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<pre>0.782275364867241</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Predict from manufactured test and score</span>
<span class="n">LoRpred</span><span class="o">=</span> <span class="n">LoRmod</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Accuracy score:&#39;</span><span class="p">,</span> <span class="n">accuracy_score</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span><span class="n">LoRpred</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;F1 score:&#39;</span><span class="p">,</span> <span class="n">f1_score</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">LoRpred</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Recall score:&#39;</span><span class="p">,</span> <span class="n">recall_score</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">LoRpred</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Precision score:&#39;</span><span class="p">,</span> <span class="n">precision_score</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">LoRpred</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Confusion matrix:&#39;</span><span class="p">,</span> <span class="n">confusion_matrix</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">LoRpred</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Classification report:&#39;</span><span class="p">,</span> <span class="n">classification_report</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">LoRpred</span><span class="p">))</span>
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<pre>Accuracy score: 78.29511886341257
F1 score: 78.49177585726233
Recall score: 79.39932318104907
Precision score: 77.60474090407938
Confusion matrix: [[5501 1625]
 [1461 5631]]
Classification report:               precision    recall  f1-score   support

           0       0.79      0.77      0.78      7126
           1       0.78      0.79      0.78      7092

    accuracy                           0.78     14218
   macro avg       0.78      0.78      0.78     14218
weighted avg       0.78      0.78      0.78     14218

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Predict stroke in case study using LoR.</span>
<span class="n">LoRprestest</span> <span class="o">=</span> <span class="n">LoRmod</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">strokedf_test</span><span class="p">)</span>
<span class="n">LoRpred</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">LoRprestest</span><span class="p">,</span><span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;prediction&#39;</span><span class="p">])</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">strokedf_test</span><span class="p">))</span>
<span class="n">LoRpred</span><span class="p">[</span><span class="s1">&#39;prediction&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
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<pre>15568
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<pre>0    11929
1     3639
Name: prediction, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Train and fit Decesion tree model.</span>
<span class="n">DTmod</span><span class="o">=</span><span class="n">DecisionTreeClassifier</span><span class="p">(</span><span class="n">criterion</span><span class="o">=</span><span class="s1">&#39;gini&#39;</span><span class="p">,</span> <span class="n">random_state</span> <span class="o">=</span> <span class="mi">77</span><span class="p">,</span><span class="n">max_depth</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
<span class="n">DTmod</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span><span class="n">y_train</span><span class="p">)</span>
<span class="c1">#Score DT fit.</span>
<span class="n">DTmod</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">y_train</span><span class="p">)</span>
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<pre>0.8709161244944611</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Predict from manufactured test and score</span>
<span class="n">DTpred</span> <span class="o">=</span> <span class="n">DTmod</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Accuracy score:&#39;</span><span class="p">,</span> <span class="n">accuracy_score</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span><span class="n">DTpred</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;F1 score:&#39;</span><span class="p">,</span> <span class="n">f1_score</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">DTpred</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Recall score:&#39;</span><span class="p">,</span> <span class="n">recall_score</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">DTpred</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Precision score:&#39;</span><span class="p">,</span> <span class="n">precision_score</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">DTpred</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Confusion matrix:&#39;</span><span class="p">,</span> <span class="n">confusion_matrix</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">DTpred</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Classification report:&#39;</span><span class="p">,</span> <span class="n">classification_report</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">DTpred</span><span class="p">))</span>
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<pre>Accuracy score: 85.99662399774934
F1 score: 87.00306808538417
Recall score: 93.96503102086858
Precision score: 81.00158016287833
Confusion matrix: [[5563 1563]
 [ 428 6664]]
Classification report:               precision    recall  f1-score   support

           0       0.93      0.78      0.85      7126
           1       0.81      0.94      0.87      7092

    accuracy                           0.86     14218
   macro avg       0.87      0.86      0.86     14218
weighted avg       0.87      0.86      0.86     14218

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Determine how DT weighted features.</span>
<span class="n">featurelist</span><span class="o">=</span><span class="nb">list</span><span class="p">(</span><span class="n">strokedf_train</span><span class="o">.</span><span class="n">columns</span><span class="p">[:])</span>
<span class="n">plt</span><span class="o">.</span><span class="n">bar</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">DTmod</span><span class="o">.</span><span class="n">feature_importances_</span><span class="p">)),</span> <span class="n">DTmod</span><span class="o">.</span><span class="n">feature_importances_</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">&quot;feature&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;importance&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;feature importance&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xticks</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">DTmod</span><span class="o">.</span><span class="n">feature_importances_</span><span class="p">)),</span> <span class="n">featurelist</span><span class="p">,</span><span class="n">rotation</span><span class="o">=</span><span class="s1">&#39;vertical&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
<span class="nb">print</span><span class="p">(</span><span class="n">featurelist</span><span class="p">)</span>
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<pre>[&#39;gender&#39;, &#39;age&#39;, &#39;hypertension&#39;, &#39;heart_disease&#39;, &#39;ever_married&#39;, &#39;work_type&#39;, &#39;Residence_type&#39;, &#39;avg_glucose_level&#39;, &#39;bmi&#39;, &#39;smoking_status&#39;, &#39;stroke&#39;]
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Predict stroke in case study using DT.</span>
<span class="n">DTprestest</span> <span class="o">=</span> <span class="n">DTmod</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">strokedf_test</span><span class="p">)</span>
<span class="n">DTpredf</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">DTprestest</span><span class="p">,</span><span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;prediction&#39;</span><span class="p">])</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">strokedf_test</span><span class="p">))</span>
<span class="n">DTpredf</span><span class="p">[</span><span class="s1">&#39;prediction&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
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<pre>15568
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<pre>0    12006
1     3562
Name: prediction, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Train and fit Random Forest model.</span>
<span class="n">RFmod</span><span class="o">=</span><span class="n">RandomForestClassifier</span><span class="p">(</span><span class="n">n_estimators</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span><span class="n">random_state</span><span class="o">=</span><span class="mi">77</span><span class="p">)</span>
<span class="n">RFmod</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span><span class="n">y_train</span><span class="p">)</span>
<span class="c1">#Score RF fit.</span>
<span class="n">RFmod</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">y_train</span><span class="p">)</span>
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<pre>0.9999824160365747</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Predict from manufactured test and score</span>
<span class="n">RFpred</span> <span class="o">=</span> <span class="n">RFmod</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Accuracy score:&#39;</span><span class="p">,</span> <span class="n">accuracy_score</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span><span class="n">RFpred</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;F1 score:&#39;</span><span class="p">,</span> <span class="n">f1_score</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">RFpred</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Recall score:&#39;</span><span class="p">,</span> <span class="n">recall_score</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">RFpred</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Precision score:&#39;</span><span class="p">,</span> <span class="n">precision_score</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">RFpred</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Confusion matrix:&#39;</span><span class="p">,</span> <span class="n">confusion_matrix</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">RFpred</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Classification report:&#39;</span><span class="p">,</span> <span class="n">classification_report</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">RFpred</span><span class="p">))</span>
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<pre>Accuracy score: 96.97566465044311
F1 score: 96.99594802291463
Recall score: 97.88494077834179
Precision score: 96.12295762946552
Confusion matrix: [[6846  280]
 [ 150 6942]]
Classification report:               precision    recall  f1-score   support

           0       0.98      0.96      0.97      7126
           1       0.96      0.98      0.97      7092

    accuracy                           0.97     14218
   macro avg       0.97      0.97      0.97     14218
weighted avg       0.97      0.97      0.97     14218

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Determine how RF weighted features.</span>
<span class="n">featurelist</span><span class="o">=</span><span class="nb">list</span><span class="p">(</span><span class="n">strokedf_train</span><span class="o">.</span><span class="n">columns</span><span class="p">[:])</span>
<span class="n">plt</span><span class="o">.</span><span class="n">bar</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">RFmod</span><span class="o">.</span><span class="n">feature_importances_</span><span class="p">)),</span> <span class="n">RFmod</span><span class="o">.</span><span class="n">feature_importances_</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">&quot;feature&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;importance&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;feature importance&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xticks</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">RFmod</span><span class="o">.</span><span class="n">feature_importances_</span><span class="p">)),</span> <span class="n">featurelist</span><span class="p">,</span><span class="n">rotation</span><span class="o">=</span><span class="s1">&#39;vertical&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
<span class="nb">print</span><span class="p">(</span><span class="n">featurelist</span><span class="p">)</span>
</pre></div>

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ykT4F7aVqMiIqJ/Y00QL7Z9n+27bL/f9juAF7XZsIiI6NdYE8ShDfteuxTbERER48xi+yAkHQy8CthiaNGedYA/tdmwiIjo12id1JdQOqQ3Ak4Y2H83cHVbjYqIiP4tNkHY/q2kucB9mU0dEbFiGbUPwvZDwMOS1uugPRERMU6MdR7EX4BrJJ1HGeYKgO2jWmlVRET0bqwJ4tv1FhERK4ixVnP9Up1JvVXddb3tB9trVkRE9G2sa1I/F/gScBMgYFNJh9r+aXtNi4iIPo11otwJwF62d7f9HGBv4BOjHSRpH0nXS5ot6ZiGx98h6TpJV0s6X9LmA48dKumGemuaqBcRES0aax/EKravH9mw/T+SVlncAZImUEqC7wnMBaZLmja0dOhVwFTb90h6C3A8cKCkDYH3AlMBAzPrsXeM+Z1FxLgy6ZizW49x04f3bT3GimSsZxAzJH1e0nPr7XPAjFGO2QWYbXuO7QeAM4EDBp9g+ye276mblwGb1Pt7A+fZ/lNNCueR8uIREZ0aa4J4C3AdcFS9XVf3Lc7GwM0D23PrvkU5DPjBkhwr6XBJMyTNmDdv3ijNiYiIJTHWUUz3S/oMcD7wMGUU0wNLqxGSDqFcTtp9SY6zfQpwCsDUqVO9tNoTERFjX5N6X+BG4JOU5UdnS3rhKIfdQlk3YsQmdd/wa78AeDewv+37l+TYiIhoz5KMYtrD9nNt7w7sweijmKYDUyRNrnMoDgIGK8IiaUfgZEpy+MPAQ+cCe0naQNIGwF51X0REdGSso5jurmtSj5hDqei6SLbnSzqS8sE+ATjN9rWSjgNm2J4GfBRYG/iGJIDf2d7f9p8kfYCSZACOs53y4hERHRprgpgh6Rzg65Rhp6+gDFt9KYDtxjIcts8Bzhna956B+y9YVEDbpwGnjbF9ERGxlI01QawO3MaCTuR5wBrAfpSEkTpNERHLmbGOYnpd2w2JiIjxZay1mCYDbwMmDR5je/92mhUREX0b6yWm7wKnAmdR5kFERMRybqwJ4j7bn2q1JRERMa6MNUF8UtJ7gR8BI5PZsH1lK62KiIjejTVBPAV4DfA8Flxict2OiIjl0FgTxCuALZZm/aWIiBjfxlpq45fA+m02JCIixpexnkGsD/xa0nQW7oPIMNeIiOXUWBPEe1ttRUREjDtjnUl9UdsNiYiI8WWxCULSz20/S9LdlFFLjzwE2Pa6rbYuIiJ6s9gEYftZ9d91umlORESMF2MdxRQRESuYVhOEpH0kXS9ptqRjGh5/jqQrJc2X9PKhxx6SNKvepg0fGxER7RrrKKYlJmkCcCKwJzCXssDQNNvXDTztd8BrgX9ueIl7be/QVvsiYsUx6ZizW49x04f3bT1G11pLEMAuwGzbcwAknQkcADySIGzfVB9LhdiIiHGmzUtMGwM3D2zPrfvGanVJMyRdJunFTU+QdHh9zox58+b9PW2NiIgh47mTenPbU4FXAf8pacvhJ9g+xfZU21MnTpzYfQsjIpZjbSaIW4BNB7Y3qfvGxPYt9d85wIXAjkuzcRERsXhtJojpwBRJkyWtChwEjGk0kqQNJK1W728EPJOBvouIiGhfawnC9nzgSOBc4FfA121fK+k4SfsDSNpZ0lxKOfGTJV1bD/8HYIakXwA/AT48NPopIiJa1uYoJmyfA5wztO89A/enUy49DR93CWWRooiI6Ml47qSOiIgeJUFERESjJIiIiGiUBBEREY2SICIiolESRERENEqCiIiIRkkQERHRKAkiIiIaJUFERESjJIiIiGiUBBEREY2SICIiolESRERENEqCiIiIRkkQERHRqNUEIWkfSddLmi3pmIbHnyPpSknzJb186LFDJd1Qb4e22c6IiHi01hKEpAnAicALgW2BgyVtO/S03wGvBc4YOnZD4L3ArsAuwHslbdBWWyMi4tHaPIPYBZhte47tB4AzgQMGn2D7JttXAw8PHbs3cJ7tP9m+AzgP2KfFtkZExJA2E8TGwM0D23PrvqV2rKTDJc2QNGPevHl/c0MjIuLRlulOatun2J5qe+rEiRP7bk5ExHKlzQRxC7DpwPYmdV/bx0ZExFLQZoKYDkyRNFnSqsBBwLQxHnsusJekDWrn9F51X0REdKS1BGF7PnAk5YP9V8DXbV8r6ThJ+wNI2lnSXOAVwMmSrq3H/gn4ACXJTAeOq/siIqIjK7f54rbPAc4Z2veegfvTKZePmo49DTitzfZFRMSiLdOd1BER0Z4kiIiIaJQEERERjZIgIiKiURJEREQ0SoKIiIhGSRAREdEoCSIiIholQURERKMkiIiIaJQEERERjZIgIiKiURJEREQ0arWaa0TEim7SMWe3HuOmD+/byuvmDCIiIhq1miAk7SPpekmzJR3T8Phqkr5WH79c0qS6f5KkeyXNqreT2mxnREQ8WmuXmCRNAE4E9gTmAtMlTbN93cDTDgPusP0kSQcBHwEOrI/daHuHttoXERGL1+YZxC7AbNtzbD8AnAkcMPScA4Av1fvfBJ4vSS22KSIixqjNBLExcPPA9ty6r/E5dQ3rO4HH1McmS7pK0kWSnt1iOyMiosF4HcV0K7CZ7dslPQ34rqTtbN81+CRJhwOHA2y22WY9NDMiYvnV5hnELcCmA9ub1H2Nz5G0MrAecLvt+23fDmB7JnAjsNVwANun2J5qe+rEiRNbeAsRESuuNs8gpgNTJE2mJIKDgFcNPWcacChwKfBy4ALbljQR+JPthyRtAUwB5rTY1ojOLMvj4mPF0lqCsD1f0pHAucAE4DTb10o6DphhexpwKvAVSbOBP1GSCMBzgOMkPQg8DLzZ9p/aamtERDxaq30Qts8Bzhna956B+/cBr2g47lvAt9psW0RELN547aSOiBbk8lYsiZTaiIiIRkkQERHRKAkiIiIaJUFERESjdFJX6byLiFhYziAiIqJREkRERDRKgoiIiEZJEBER0Sid1Cu4FbVzfkV93xFLImcQERHRKAkiIiIaJUFERESj9EFEb9IPEDG+5QwiIiIatZogJO0j6XpJsyUd0/D4apK+Vh+/XNKkgcfeVfdfL2nvNtsZERGP1lqCkDQBOBF4IbAtcLCkbYeedhhwh+0nAZ8APlKP3Zay/Oh2wD7AZ+vrRURER9o8g9gFmG17ju0HgDOBA4aecwDwpXr/m8DzJanuP9P2/bZ/A8yurxcRER2R7XZeWHo5sI/tN9Tt1wC72j5y4Dm/rM+ZW7dvBHYF3gdcZvu/6/5TgR/Y/uZQjMOBw+vm1sD1rbyZZhsBf+wwXmIndmKvOPG7jL257YlNDyzTo5hsnwKc0kdsSTNsT03sxE7s5S923/H7fu8j2rzEdAuw6cD2JnVf43MkrQysB9w+xmMjIqJFbSaI6cAUSZMlrUrpdJ429JxpwKH1/suBC1yueU0DDqqjnCYDU4ArWmxrREQMae0Sk+35ko4EzgUmAKfZvlbSccAM29OAU4GvSJoN/ImSRKjP+zpwHTAfOML2Q2219W/Uy6WtxE7sxF4h4vf93oEWO6kjImLZlpnUERHRKAkiIiIaJUFERESjJIgxkjRB0tvHQTvW7LsNfZC0hqSt+27HiiQ/80gn9RKQdIXtXkp+SHoG8HlgbdubSXoq8Cbbb+0g9lbAO4HNGRj5Zvt5bceu8fcDPgasanuypB2A42zv31K8s4BF/mG0FXeoDQJeDWxh+zhJmwGPt93JcO+uf+Y15jU0/9wF2Pb2LcX9uu1XNsRvNW5DO7YE5tq+X9Jzge2BL9v+cxfxG9uUBDF2kj4BrAJ8DfjryH7bV3YQ+3LKXJFptnes+35p+8kdxP4FcBIwE3hkuLHtmW3HrvFnAs8DLhx479fYfkpL8Xavd18KPB7477p9MHCb7dbPJCX9F/Aw8Dzb/yBpA+BHtnduO3aN3+nPvL7+5ot73PZvW4r7BNu3Lip+W3Eb2jELmApMAs4BvgdsZ/sfu4jfZJkutdGDHeq/xw3sM+UPqXW2by5fLB/R1dyQ+bb/q6NYTR60fefQe2/tm43tiwAknTBU7uAsSTPaijtkV9s7SbqqtumOOuG0K53+zGHhD+L6YT3F9o8lrUG7c7ZuHYwvad024y3Gw3X+2EuAT9v+9Mj/f1+SIJaA7T16DH9zvcxkSasARwO/6ij2WZLeCnwHuH9kp+0/dRT/WkmvAiZImgIcBVzSQdy1JG1hew5AndW/VgdxAR6sJe5dY0+knFF0pa+fOZLeSCnCuSGwJaXUzknA81uO+ybg/cB9LEiGBrZoM+6AByUdTKkusV/dt0pHsRvlEtMSkPQ44EPAE22/sK5bsZvtUzuIvRHwSeAFlGujPwKOtn17B7F/07Dbtjv5w6kd8+8G9qK893OBD9i+r+W4+1BmtM6pcTen9Puc22bcGvvVwIHA04AvUi4vHmv7G23HrvF7+ZnX2LMo5f0v7+ryVo1xA+XvuZcKrvXz5M3Apba/Wr+QvNL2R/poDyRBLBFJPwC+ALzb9lNrgcGr2v7FjQXqt+q1bN/VUbzVgG3q5q9t37+45y/l2Nuw4FvzBba7OmMcbMO6lC8Dd3cY83Lbu0q6yvaO9e/syrY7iyX9EHip7XvajLMsySWmJbOR7a9Lehc8Um+qk34ASZ9q2H0npa7V91qOvQrwFuA5ddeFwMm2H2wz7kD8MyjfrB6iFIFcV9InbX+05bhrAu+g1Mt/o6Qpkra2/f024w5Yk1LHzMAaHcUEQNLOwGnAOnX7TuD1HQ1MuEjSvwJrSNoTeCtwVgdx3wVcUgeEDF5KPaqD2CNn6o/6xt7VmXqTzINYMn+V9BgWXBd+OuVDugurUzrJb6i37SnXZg+T9J8tx/4vyqWOz9bb0+q+rmxbzxheDPwAmAy8poO4XwAeAHar27cA/95BXCS9h7La4oaUxWO+IOnYLmJXpwJvtT3J9iTgCMrPowvHAPOAa4A3UUb0dPHeTwYuAC6jjNgbuXVlKrBzvT0b+BQLRtD1w3ZuY7wBOwEXU5LCxcD/ANt3FPsyYMLA9srApZRvmNe1HPsXY9nXYvxrKZ113wB27yo+5ewMymXETt83ZXXE1Qe21wCu7/BnflXDvis7iv1SYLWu3uvi3nPfN2Bmn/FziWkJ2L6yjpHfmtJxd707uswCbACszYIzlrWADW0/JKnt6+IPSdrS9o0AkraguyG2UL7Z3QT8AvhpHQLZRR/EA3WI5cgZ45YMXHpo2e8pZ40jncKr0e2iWRdJOhn4KuX9HwhcKGknaH3uz37AJyT9lDLn6Ie257cYb8QPVJYxPoseRuuN/GyrlShnFL1+RqeTegwkvXRxj9v+dgdtOIxymn0hJTk9hzKi6qvA+2y/s8XYz6dcXhgczfM62z9pK+YY2rRy2x8a9fr3scC2lFFjzwRea/vCNuPW2N+lXGo4j/IBvSdl0ay50P51cUmL+7+1W55FX/u9XkhJTM8CznNd377FmL32AQz9zOcDvwFOsH19F/GbJEGMgaSRa6+PBZ5BuU4JsAdwie0XddSOJ1Kuvf+KcjYx1/ZPO4q9GuXMCcqZU2ejeWr8fYHtKN+qAbB93KKPWGpxHwM8nZIYL3NHQyAlHbq4x21/qeX4E9zzIl01SewDvA54ju2NWo63BqVD/FmURPEz4CTb97YZdyD+I3NuBvZNtt00zLwTSRBLQNKPgENdZ15KegLwRdt7dxD7DZTJcZsAsygfWpe2+U1O0vNsX7CoM6guzpxqO06ijOjZg1KP6uXAFbYPayneNrZ/PXTK/4iWL6+MtGE/4GzbXU6OG4w/B/gWZSXITofXSho5c3gu5Yz565QyI22fMX6dcuny9LrrVcB6tl/ZZtyB+Ffa3mlo30zbT+sifpP0QSyZTUeSQ3UbsFlHsY+mXHK4zPYedYz8h1qOuTvlbGm/hscMdJIggGfY3l7S1bbfL+kEymimtryDMpP3hIbHuiqtciDwn5JGPqR/3UHMQU+lLAF8qqSVKENez3Q380/+idL38KaOz1SfbHvbge2fSLqu7aD1b3k7YL2hL2PrMnDG3IckiCVzvqRzKdf9ofwR/7ij2PfZvk8Sklar33BbLcVs+73139e1GWcMRk7x76mX2W4HntBWMNuH1w/FY21f3FacUdpwSJ2kdjDwRUmm9AN91R1MWqsxPgd8rg7MOF1E+uUAABYJSURBVIPScfxNyozq2S3GPrgORHg28Egtpg7e95WSnm77MgBJuwJd1N7aGngRsD4Lfxm7G3hjB/EXKQliCdg+smb4Z9ddp9j+Tkfh50paH/gucJ6kO4CuqkweTflwGvnQ2Ak4xvaPuogPfL++948CV1K+xX++zYC2H5b0GWDHNuOM0oa76gfyGsD/AV4CvFPSp2x/us3Ydcb6vpTr/5MoZ1OnU373zwG2ajF2p7WYtKDM9yqUiXK/q9ubA62fublMdP2epN1sX9p2vCWRPohlUP1Gtx5l+N8DHcT7hUtpkb0pM5qPBb4yfL20C7WzfHXbrU9QlPQxylyTb7vjPxRJBwCvBZ4EfBn4ku0/1Nnd17lMXmsz/hzgJ8Cpti8ZeuxTbY6iUse1mNRTmfGGdqwOHMajB2O8vov4TXIGsQTq2cNHKKOZxIIFRdbtsh2u5ag7NFLz+R8pC5hcKy1cB7rV4OVD8f8Cm7mUvNhM0rPdfsmLN1H6I+ZLuo9u/79fCnxieJSa7XvqkOe2/ZPtnw/ukPRM2xe3PcQWuN/2AyO/Yiq1mNos795JAhiDr1DOWPamLCnwarqr2NwopTaWzPHA/rbXs72u7XW6Tg49mVlHcP0jcK6kdei29PQXKBOXOit5URPgdrZXsr1qD//f/zucHCR9BMD2+R3Eb6r91eplrQHDtZi+QTe1mPr2JNv/Bvy1DmPeF9i1zwblDGLJ3Nb1kL9x4jBKHag59RvsYyjXpruype0DVWrlj3yLbvUMxrYlnQ30Val3T+Bfhva9sGHfUiVpN8pcn4mS3jHw0LqUsi5dOIbyOzdYi6nVPqdxYqQqw58lPRn4X8rVit4kQSyZGZK+RukoHpyK39Vwz17UDtvbgG3r6X7X+ip5caWknW1P7yAWAJLeQpmstaWkqwceWodS/6ttq1ImYa5cY464izL/pHV17sfn6m1FcorK0rLHAtMo/w//1meD0km9BAZmVA9yn51IXaiXNg4ErmNBDSa7xQXsh+L3UvJC0q8pncS/paxB3voi9pLWo9Td+g/KN+kRd3ugJpCkDWzf0WI7Nl/ctXlJn7b9tqUcc2Q0UaM2f+7jQdOs6cykjnFP0vWUqrWdltcYakPnJS8WNbplPHRqNs26Xdbjj5fRRH3JTOplnKStKOsgPM72kyVtT+m07mSNgB7NoYwR7yVBSHomMMv22ZIOAf5VZcGgVj8wvGAR+8fS84zWBp2NIuvKWP8/JV1qe7fRn7lsyEzq5cfngHdSyk9j+2qV1c6W9wRxDzBL0vn0sNIWJSk/VdJTKcNOT6XMDdi9zaCS9qdMEHsi8AfKxKlfUf6Y+7Yin/qPt2T998pM6uXEmravGBpA00Wd+r5Nq7e+zK+jig4ATrR9akdzAT5Auaz1Y5e1kfcADukg7rKgzzOY5So5jueZ1EkQS+aPdQTNyGialwO3Lv6QZZ/tL9VRRJu5n9r0d6usA34I8JxaJ2mVDuI+aPt2SStJWsn2T9T+8q5j1ckHtKQ1bd/T8NAnu4i/gnmJpGsptcd+SFlW+O22e1t2NBPllswRlMtL20i6hVIf5839Nql9KqWnZ1F+aZG0g6QuzygOpFzaOsz2/1Jq83y0g7h/lrQ28FPgdEmfpIxmal3TGZKkDw9stlKXaCDWM1Qqmf66bj9V0mdHHrf9xTbjj2K563+p9qrVcl9EWUHxSZRL2r3JKKYlMDBxaA1Kcv0rZQnQmbZn9dawlkmaSSlxfeFAbZxf2n5yvy1rl6S1KEt+ilL2YD3gdNu3dxD7nBrr9Lp9IqUGVReX1pB0OWXew7Q+/s/riKYpth9VzVXSk23/sot2dEnStba3k/R54Ju2fzhSB62vNuUS05KZWm/TKB8ahwBXA2+W9A3bx/fZuBY9aPvOob6X1kttSPq57WdJupuFrzt3UhPJ9l9rO9al+1IPLwOmSXqYsqran7tKDiNs3zz0f97JCnMapZrr8pgcqrPq3Jt7gbdImsiCNcl7kQSxZDYBdrL9FwBJ7wXOpqwPPZNSq2l5dK2kVwETJE0BjgIuGeWYv5vtZ9V/1xntuW2Q9Cbg/ZQ/0oepiQlobY1iSRsObL6BMmv/YuD9kjYcnCzXspslPQOwytKfR9Nd4bgjqNVcAWzfUIcaL9dsHyPpeOBO2w9Jugc4YORxSXvaPq/LNiVBLJnHsvBcgAcpcyLuldTbJLIOvA14N+W9nwGcSxnh06qhD8tH6eDD8p8pq4x1sg51NZNHny3tW2+tJqchb6Z0RG9MKY74I8oHdxc6reY6ngz+Ttcz2ME+r48ASRDj2OnA5ZK+V7f3A86o16pbX5qwR/vafjclSQAg6RWUKpttGvmwFGVp1zvq/fWB3wGTW45/I2UOSGdsT66jtHZzT6vZ1Xb8kdLv0ofhaq5vZcWo5jqazjvn00m9hCRNpdQCArjYdhdLEvZqESUAOiv1IOlzwHdsn1O3Xwi82PabWo67I6XU+OV0PEFQ0lUjncN9kPQl4Gjbf67bGwAndFF3rCbIw4C9KB+K5wKf9wr+YdVHeZUkiFik+kH8j8ArKYvIj1gX2Nb2Lh2141GriTXtayHuFcDPKWWnH+mUr7X6W6UeV7Or8R+VoPpIWvUy4ya2rx71ycu5PhJELjHF4vyesmj7/pTLPSPuBt7eZTskHQuMTBh6dW1b21ax/Y7Rn9aKkdXsHpJ0L92vXrjSYMXY+kHdyeeFpAspv3MrU37v/iDpEttd/s6NRzd1HTBnELFYKovXf8X2q3psw4bAeymjxUyZuHZc253Ukj5E+aM8i4UvMXU1kqg3kv4J+FdKP5MocyI+aPsrHcS+qpY2eQOwqe33Srp6BSj3/dKG3XcC19j+Q9ftgSSIGANJPwOeb/uBvtvSRC2sTVBft6kOv213MpKoFgt8Tt280O2vwT0cfztgj7p5ge1OBmKorAuxF/Al4N22p68gCeJsyrK6P6m7nks5g5pM+ULUenIelktMMRa/AS6u5TUeGXZn++P9NWkhzxz9KUvO9mJHSbU5Lr2W1diZMnIO4GhJz7T9rjbiLcKvKSPHVq5t2sz27zqIexylY/rimhy2AG7oIG7fVgb+wfZtAJIeR6lavCvlrLnzBJEziBhVnRD4KLbf33VbmvTRedd2XJXlRndwWX5z5FLfVV19i5b0NsplvdsoM6hbX01vRSfpOtvbDmwLuNb2tn2NassZRIxqJBEsprLniqrtcenrAyP9Heu1HGvY0cDWXdSdGiZpE+DTLDgz/BllyO3crtvSsQslfZ8F84teVvetBfy5jwalmmuMStJui6vsOQ70Vd2zzdPvDwFXSvpinZMwE/hgi/GG3UzpIO3DFyj1zp5Yb2fVfcu7I4AvAjvU25eBI2z/1fYeizuwLbnEFKMaB5U9X2H7G4vaJ+m1fZSfbvkS038D/0PpA7gJmF5LnXdC0qmUlc7OZuERXK33O0maZXuH0fZF+3IGEWNi++ahXZ1U9qyaOmYf2ddGclBZJOgZozztpqUdd8Cp9d/9KTWRTpR0dIvxhv2OUvdnVWCdgVsXbpd0iKQJ9XYI0Pmlrq5JeqmkGyTdKekuSXdLuqvXNuUMIkYj6ZvAx4HPUEZUHA1MtX1Qy3F7nck9DspdTKCMZNqDUjzvXtvbdNyGzvudVNaC+DRlyKcplYOP6mgEVW8kzQb2s91V1dxRpZM6xmKwsufvKUMQu6js2fdM7vMlvYweyl1IOh9Yi1Ju42fAzl1OlpK0G+UsZm1gM0lPBd5k+61tx7b9W8r/+YrmtvGUHCBnEDHO9TmTW2WhorUol9M6LXch6RPA0yjX/y+mjIO/1Pa9bceu8Xvrd+qzUGCfVJa0fTxlDZDBfp9v99WmnEHEqOpEpU8CT6ec8l9KWUx9Ttux68Ipm0pateuZ3H0tVFRjvx1A0jrAaymjeB4PrNZhG3pZUQ7YfiQ51HbcUSvrLu/WpZSX32tgn4EkiBjXzgBOBF5Stw8Cvkrpj+hCLzO560SlVwOTbX9A0qbAE2xf0WbcGvtI4NmUs4ibgNMol5q60ueKcr0VCuyT7df13YZhy/0PPZaKNYfqwPy3pHd2GP/GeluJ7kbSAHyWUub7eZQV9P5CSZQ7dxB7dcrAgJm253cQb1ifK8qdAFwqaaFCgR3F7pyk/2f7eEmfpmFuTRfrjyxK+iBiVJI+QhmPfyblF/hAYAPgo7D8VjcdmecwOJpJ0i9sP7Xvti3vJG1LSczQYaHAPkjaz/ZZkg5teryL9UcWJQkiRrWIqqYjWq9uKmki8P+A7SjfrEcCP2+RBy2duJcDz6BMUtuptuNHfQ59bduivsWO6OLbrKTNFhF7eR/mOtn2b4b27Wx7el9tyiWmGNVoVU07cDplHsSLKJc+DgXmdRD3U8B3gMdK+iDlUsexHcTt08gSus8EtmXB/JNX0N2662ezIEmtQSl3fT3lC8Ly7JuS9rd9C4Ck3Slzj1pdOXFxcgYRo5I0kzIm/ozB0SVdxrf9tME1ASRNt916X4CkbYDnU66Fnz/exqm3RdJlwLNG+j9qR/XPbD+9h7bsBLzV9hu6jt0lSTtT+r32A3YC/gN4UUMVg87kDCLG4kDgdcAMSTMoQy5/1OHksQfrv7dK2pcygW7DtoNK+hRwpu0T2441Dm1AGXY50r+0dt3XOdtXSupqxFxv6toXR1EGBNwHvMB2F2fKi5QziBgzSStRLvP8F2VM/BeAT7bdSS3pRZQhnptSSjCsC7zf9rSW4x5KSY5bUy41nWl7xuKPWj5Ieh3wPsrqZqKsbPe+LjpMJQ2uA74S5dv0Y2zv3XbsPkg6i4X7fbYFbqUMDMF2b7PKkyBiTCRtD7weeCGl1MbpwLOA1yzvVTbrOPyXUeZ/bGZ7Ss9N6oSkx7NgrsvlXVWTHVqgaj5lHsi3bN/XRfyu1b6GRbJ9UVdtGZYEEaOqfRB/Bj5PqUt0/8Bj37bdtNj60oy/FeWs5XG2n1yT1f62/73NuAPxd6GcSRwA/Mr2fl3E7YOkbWz/ul73fxTbV3bdphWJyjKjI31rV3RZf6uxPUkQMZo6Jn1HYHMG+q1sH9dR/IuAdwInd1kXSNLxwIuBOZQ5IN/to5O+S5JOsX24pJ80POw2hxY3XGoZDr5cF/CT9ErK3KILKZf1ng280/Y3+2pTOqljLD5OOYO4koEiYh1a0/YVQ3WBuphdfBPw78Ak21+UtJmkrbootdEX24fXf/tYwexjPcQcT97NQNXeOu/mx0ASRIxrm9jep8f4f5S0JfXbpaSXUzrx2vYUFpTaOI5SZvxbdFNqo1eSXgH80Pbdko6ldBR/wPZVbcXs81r7OLHS0CWl2+l5UbckiBiLSyQ9xfY1PcU/AjgF2EbSLZTifa/uIO6uI6U24JGqoqt2EHc8+Dfb35D0LOAFlEsfJ9FBgUZJ1/DoS013Uibx/bvt5XV1uR9KOpdSCBNKv9cPemxPEkQs2sAf6srA6yTNoVxiGlkXYfuOmnILZUjtTyjzH+6izKZuuw/kwboexciZy0TKGcWKYKS0977AKbbPltTJoADKh+JDlCrCUEaPrQn8L/BFykSy5Y7td9YFqp5Zd51i+zt9timd1LFIdenHRaorf3XRjh+yoA/kkTUJbJ/QctxXU77F7QR8iVpqw/Y32ow7Hkj6PiUx70l5//dSRtW0XqhwpEhi0z5J19jurfREFySty8KDQXorhpkziFikrhLAGPTSB2L79DrEd6TUxotXlFIblHXA9wE+ZvvPkp5AGUnWhQmSdhkZDFBLUEyoj/VR+rwTkt4EvJ8yi/ph6pk60GoxzMVJgohlQW99ILZ/Dfy667h9s32PpD9QJkPeQPlgvqGj8G8ATpO0dt2+GzhM0lqU+kTLq38Gnmz7j303ZEQuMcW4NdQHMoUyH6GPPpAVTp3NPBXY2vZWkp4IfMP2M0c5dGm2YT0A23cO7T+0zzUS2lIvpb7U9j19t2VEEkSMW+OlD2RFJGkWZXLklQOTE68eD0m5qY9ieVDX3f4CcDkD8436XFEul5hi3EoC6NUDti1pZATXWn03aIBGf8oy6WTgAuAaxslouSSIiGjydUknA+tLeiOlUOPne27TiOX1sscqtt8x+tO6k0tMEdFI0p7AXpRv7OfaPq/nJgEwuEb48kTShyjlXc5i4UtMvQ1zTYKIiFHVtUAOtn36OGjLZ2wf2Xc7lrahtd8f+WBue833xUmCiIhH1ElaRwAbA9OA8+r2PwO/sH1AB21ousxyJzDT9qy24/elVnP9oe27JP0bC+pf9VZiPQkiIh4h6XuUlcwupUwQfCzlEtPRXX04SzqDMsT2rLrrRcDVwCTKUNvju2hH10ZGidX6Vx+gVLd9j+3elltNgoiIRwyWsqh1qG6lrKLX2Wpukn4K/KPtv9TttYGzKTO7Z9retqu2dGmkb0XSfwDX2D6j7/6WXkvJRsS48+DIHdsPAXN7WOrzsSy87siDlNUE76Wf9Ui6cksdOXYgcI6k1Ui574gYR54q6a56X8AadXtk9vq6HbThdODyerkLSvXWM+pcjOs6iN+XPutfNcolpogYdyRNZUHZ64ttz+izPSuqJIiIGFckfQo40/YlfbdlRZc+iIgYb2YCx0q6UdLH6tlE9CBnEBExLknaEHgZZUW5zWxP6blJK5ycQUTEePUkYBtgc1bANTnGg5xBRMS4Iul44CXAjcCZwHdt/7nfVq2YMsw1IsabG4FnUJbaXA3YXhK2f9pvs1Y8SRARMd48TFkXYRNgFvB0SumP5/XZqBVR+iAiYrw5CtgZ+K3tPSgr2+USUw+SICJivLlvpLyHpNVs/xrYuuc2rZByiSkixpu5ktYHvgucJ+kOIMvP9iCjmCJi3JK0O7AeZZ2EB/puz4omCSIiIhqlDyIiIholQURERKMkiIhRSDpK0q8knb6Ex02S9Kq22hXRtiSIiNG9FdjT9quX8LhJwBIniLrUZ0TvkiAiFkPSSZSSDz+Q9G5Jp0m6QtJVkg6oz5kk6WeSrqy3Z9TDPww8W9IsSW+X9FpJnxl47e9Lem69/xdJJ0j6BbCbpKdJukjSTEnn1tXFIjqVBBGxGLbfDPwe2ANYC7jA9i51+6N1Gcw/UM4wdqKsJ/ypevgxwM9s72D7E6OEWgu43PZTgcuBTwMvt/004DTgg0v5rUWMKhPlIsZuL2B/Sf9ct1cHNqMkkM9I2gF4CNjqb3jth4Bv1ftbA0+mTBIDmADc+ne0O+JvkgQRMXYCXmb7+oV2Su8DbgOeSjkrv28Rx89n4bP21Qfu32f7oYE419rebWk0OuJvlUtMEWN3LvA21a/1knas+9cDbrX9MPAayjd+gLuBdQaOvwnYQdJKkjYFdllEnOuBiZJ2q3FWkbTdUn0nEWOQBBExdh8AVgGulnRt3Qb4LHBo7WDeBvhr3X818JCkX0h6O3Ax8BvgOko/xZVNQWpJiZcDH6mvOYuyPkJEp1JqIyIiGuUMIiIiGiVBREREoySIiIholAQRERGNkiAiIqJREkRERDRKgoiIiEZJEBER0ej/A53qBxKTnXA9AAAAAElFTkSuQmCC
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<pre>[&#39;gender&#39;, &#39;age&#39;, &#39;hypertension&#39;, &#39;heart_disease&#39;, &#39;ever_married&#39;, &#39;work_type&#39;, &#39;Residence_type&#39;, &#39;avg_glucose_level&#39;, &#39;bmi&#39;, &#39;smoking_status&#39;, &#39;stroke&#39;]
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Predict stroke in case study using RF.</span>
<span class="n">RFprestest</span> <span class="o">=</span> <span class="n">RFmod</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">strokedf_test</span><span class="p">)</span>
<span class="n">RFpredf</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">RFprestest</span><span class="p">,</span><span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;prediction&#39;</span><span class="p">])</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">strokedf_test</span><span class="p">))</span>
<span class="n">RFpredf</span><span class="p">[</span><span class="s1">&#39;prediction&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
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<pre>15568
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<pre>0    14932
1      636
Name: prediction, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">kfold</span> <span class="o">=</span> <span class="n">model_selection</span><span class="o">.</span><span class="n">KFold</span><span class="p">(</span><span class="n">n_splits</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">77</span><span class="p">)</span>
<span class="n">cv_LoR</span> <span class="o">=</span> <span class="n">model_selection</span><span class="o">.</span><span class="n">cross_val_score</span><span class="p">(</span><span class="n">LogisticRegression</span><span class="p">(</span><span class="n">max_iter</span><span class="o">=</span><span class="mi">10000</span><span class="p">),</span> <span class="n">X_train</span><span class="p">,</span> <span class="n">y_train</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="n">kfold</span><span class="p">,</span> <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;accuracy&#39;</span><span class="p">)</span>
<span class="n">cv_DT</span> <span class="o">=</span> <span class="n">model_selection</span><span class="o">.</span><span class="n">cross_val_score</span><span class="p">(</span><span class="n">DecisionTreeClassifier</span><span class="p">(</span><span class="n">criterion</span><span class="o">=</span><span class="s1">&#39;gini&#39;</span><span class="p">,</span> <span class="n">random_state</span> <span class="o">=</span> <span class="mi">77</span><span class="p">,</span><span class="n">max_depth</span><span class="o">=</span><span class="mi">11</span><span class="p">),</span> <span class="n">X_train</span><span class="p">,</span> <span class="n">y_train</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="n">kfold</span><span class="p">,</span> <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;accuracy&#39;</span><span class="p">)</span>
<span class="n">cv_RF</span> <span class="o">=</span> <span class="n">model_selection</span><span class="o">.</span><span class="n">cross_val_score</span><span class="p">(</span><span class="n">RandomForestClassifier</span><span class="p">(</span><span class="n">n_estimators</span><span class="o">=</span><span class="mi">100</span><span class="p">),</span> <span class="n">X_train</span><span class="p">,</span> <span class="n">y_train</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="n">kfold</span><span class="p">,</span> <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;accuracy&#39;</span><span class="p">)</span>
<span class="n">results</span><span class="o">=</span><span class="p">[</span><span class="n">cv_LoR</span><span class="p">,</span><span class="n">cv_DT</span><span class="p">,</span><span class="n">cv_RF</span><span class="p">]</span>
<span class="n">names</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;LoR&quot;</span><span class="p">,</span><span class="s2">&quot;DT&quot;</span><span class="p">,</span><span class="s2">&quot;RF&quot;</span><span class="p">]</span>
<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
<span class="n">fig</span><span class="o">.</span><span class="n">suptitle</span><span class="p">(</span><span class="s1">&#39;Algorithm Comparison&#39;</span><span class="p">)</span>
<span class="n">ax</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">111</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">boxplot</span><span class="p">(</span><span class="n">results</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">(</span><span class="n">names</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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<pre>/home/a/miniconda3/lib/python3.6/site-packages/sklearn/model_selection/_split.py:296: FutureWarning: Setting a random_state has no effect since shuffle is False. This will raise an error in 0.24. You should leave random_state to its default (None), or set shuffle=True.
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Curated approach (v1), repeating cleaning from naive approach v1</span>
<span class="n">strokedatacur_train</span><span class="o">=</span><span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;train_2v.csv&#39;</span><span class="p">)</span>
<span class="n">strokedatacur_test</span><span class="o">=</span><span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;test_2v.csv&#39;</span><span class="p">)</span>
<span class="n">strokedatadfcur_train</span><span class="o">=</span><span class="n">strokedatacur_train</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;id&#39;</span><span class="p">,</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">strokedatadfcur_test</span><span class="o">=</span><span class="n">strokedatacur_test</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;id&#39;</span><span class="p">,</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">strokedatadfcur_train</span> <span class="o">=</span> <span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">]</span> <span class="o">!=</span> <span class="s2">&quot;Other&quot;</span><span class="p">]</span>
<span class="n">strokedatadfcur_test</span> <span class="o">=</span> <span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">]</span> <span class="o">!=</span> <span class="s2">&quot;Other&quot;</span><span class="p">]</span>
<span class="n">strokedatadfcur_train</span> <span class="o">=</span> <span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">16</span><span class="p">]</span>
<span class="n">strokedatadfcur_test</span> <span class="o">=</span> <span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">16</span><span class="p">]</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">median</span><span class="p">(),</span> <span class="n">inplace</span><span class="o">=</span> <span class="kc">True</span><span class="p">)</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">median</span><span class="p">(),</span> <span class="n">inplace</span><span class="o">=</span> <span class="kc">True</span><span class="p">)</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;smoking_status&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="n">value</span><span class="o">=</span><span class="s1">&#39;unknown&#39;</span><span class="p">,</span><span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;smoking_status&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="n">value</span><span class="o">=</span><span class="s1">&#39;unknown&#39;</span><span class="p">,</span><span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">strokedatadfcur_train</span><span class="o">.</span><span class="n">isnull</span><span class="p">()</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
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<pre>gender               0
age                  0
hypertension         0
heart_disease        0
ever_married         0
work_type            0
Residence_type       0
avg_glucose_level    0
bmi                  0
smoking_status       0
stroke               0
dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">strokedatadfcur_test</span><span class="o">.</span><span class="n">isnull</span><span class="p">()</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
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<pre>gender               0
age                  0
hypertension         0
heart_disease        0
ever_married         0
work_type            0
Residence_type       0
avg_glucose_level    0
bmi                  0
smoking_status       0
dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">strokedatadfcur_train</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>gender</th>
      <th>age</th>
      <th>hypertension</th>
      <th>heart_disease</th>
      <th>ever_married</th>
      <th>work_type</th>
      <th>Residence_type</th>
      <th>avg_glucose_level</th>
      <th>bmi</th>
      <th>smoking_status</th>
      <th>stroke</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>1</th>
      <td>Male</td>
      <td>58.0</td>
      <td>1</td>
      <td>0</td>
      <td>Yes</td>
      <td>Private</td>
      <td>Urban</td>
      <td>87.96</td>
      <td>39.2</td>
      <td>never smoked</td>
      <td>0</td>
    </tr>
    <tr>
      <th>3</th>
      <td>Female</td>
      <td>70.0</td>
      <td>0</td>
      <td>0</td>
      <td>Yes</td>
      <td>Private</td>
      <td>Rural</td>
      <td>69.04</td>
      <td>35.9</td>
      <td>formerly smoked</td>
      <td>0</td>
    </tr>
    <tr>
      <th>5</th>
      <td>Female</td>
      <td>47.0</td>
      <td>0</td>
      <td>0</td>
      <td>Yes</td>
      <td>Private</td>
      <td>Urban</td>
      <td>210.95</td>
      <td>50.1</td>
      <td>unknown</td>
      <td>0</td>
    </tr>
    <tr>
      <th>6</th>
      <td>Female</td>
      <td>52.0</td>
      <td>0</td>
      <td>0</td>
      <td>Yes</td>
      <td>Private</td>
      <td>Urban</td>
      <td>77.59</td>
      <td>17.7</td>
      <td>formerly smoked</td>
      <td>0</td>
    </tr>
    <tr>
      <th>7</th>
      <td>Female</td>
      <td>75.0</td>
      <td>0</td>
      <td>1</td>
      <td>Yes</td>
      <td>Self-employed</td>
      <td>Rural</td>
      <td>243.53</td>
      <td>27.0</td>
      <td>never smoked</td>
      <td>0</td>
    </tr>
    <tr>
      <th>8</th>
      <td>Female</td>
      <td>32.0</td>
      <td>0</td>
      <td>0</td>
      <td>Yes</td>
      <td>Private</td>
      <td>Rural</td>
      <td>77.67</td>
      <td>32.3</td>
      <td>smokes</td>
      <td>0</td>
    </tr>
    <tr>
      <th>9</th>
      <td>Female</td>
      <td>74.0</td>
      <td>1</td>
      <td>0</td>
      <td>Yes</td>
      <td>Self-employed</td>
      <td>Urban</td>
      <td>205.84</td>
      <td>54.6</td>
      <td>never smoked</td>
      <td>0</td>
    </tr>
    <tr>
      <th>10</th>
      <td>Female</td>
      <td>79.0</td>
      <td>0</td>
      <td>0</td>
      <td>Yes</td>
      <td>Govt_job</td>
      <td>Urban</td>
      <td>77.08</td>
      <td>35.0</td>
      <td>unknown</td>
      <td>0</td>
    </tr>
    <tr>
      <th>11</th>
      <td>Male</td>
      <td>79.0</td>
      <td>0</td>
      <td>1</td>
      <td>Yes</td>
      <td>Private</td>
      <td>Urban</td>
      <td>57.08</td>
      <td>22.0</td>
      <td>formerly smoked</td>
      <td>0</td>
    </tr>
    <tr>
      <th>12</th>
      <td>Female</td>
      <td>37.0</td>
      <td>0</td>
      <td>0</td>
      <td>Yes</td>
      <td>Private</td>
      <td>Rural</td>
      <td>162.96</td>
      <td>39.4</td>
      <td>never smoked</td>
      <td>0</td>
    </tr>
  </tbody>
</table>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Going to group age classes becase:</span>
<span class="c1">#1) Distribution of ages as seen in earlier graph.</span>
<span class="c1">#2) Literature indicates that stroke prevalance doubles every 10 years.</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span><span class="o">=</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span><span class="s2">&quot;16-24&quot;</span> <span class="k">if</span> <span class="mi">16</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">25</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;25-34&quot;</span> <span class="k">if</span> <span class="mi">25</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">35</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;35-44&quot;</span> <span class="k">if</span> <span class="mi">35</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">44</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;45-54&quot;</span> <span class="k">if</span> <span class="mi">45</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">54</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;55-64&quot;</span> <span class="k">if</span> <span class="mi">55</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">64</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;65-74&quot;</span> <span class="k">if</span> <span class="mi">65</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">74</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;75-84&quot;</span> <span class="k">if</span> <span class="mi">75</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">84</span> <span class="k">else</span> <span class="s2">&quot;85+&quot;</span><span class="p">)))))))</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span><span class="o">=</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span><span class="s2">&quot;16-24&quot;</span> <span class="k">if</span> <span class="mi">16</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">25</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;25-34&quot;</span> <span class="k">if</span> <span class="mi">25</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">35</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;35-44&quot;</span> <span class="k">if</span> <span class="mi">35</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">44</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;45-54&quot;</span> <span class="k">if</span> <span class="mi">45</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">54</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;55-64&quot;</span> <span class="k">if</span> <span class="mi">55</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">64</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;65-74&quot;</span> <span class="k">if</span> <span class="mi">65</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">74</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;75-84&quot;</span> <span class="k">if</span> <span class="mi">75</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">84</span> <span class="k">else</span> <span class="s2">&quot;85+&quot;</span><span class="p">)))))))</span>
<span class="c1">#Going to group data by average glucose levels because:</span>
<span class="c1">#1) Literaure on the subjective partitions the glucose levels after meals as grouped below.</span>
<span class="c1">#2) While the distribution shows a clear bimodality I am curious how the model will perform.</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;avg_glucose_level&#39;</span><span class="p">]</span><span class="o">=</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;avg_glucose_level&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span><span class="s2">&quot;healthy&quot;</span> <span class="k">if</span> <span class="n">x</span><span class="o">&lt;</span><span class="mi">140</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;pre-diabetes&quot;</span> <span class="k">if</span> <span class="mi">140</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">200</span> <span class="k">else</span> <span class="s2">&quot;diabetes&quot;</span><span class="p">))</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;avg_glucose_level&#39;</span><span class="p">]</span><span class="o">=</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;avg_glucose_level&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span><span class="s2">&quot;healthy&quot;</span> <span class="k">if</span> <span class="n">x</span><span class="o">&lt;</span><span class="mi">140</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;pre-diabetes&quot;</span> <span class="k">if</span> <span class="mi">140</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">200</span> <span class="k">else</span> <span class="s2">&quot;diabetes&quot;</span><span class="p">))</span>
<span class="c1">#Going to group data by average glucose levels because:</span>
<span class="c1">#1) Literaure on the subjective partitions the BMI as grouped below.</span>
<span class="c1">#2) While the distribution shows only a slight right skewness perhaps redistributing as below will introduce symmetry to the distribution.</span>
<span class="c1">#3) I am curious on how it will perform.</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">]</span><span class="o">=</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span><span class="s2">&quot;&lt;20&quot;</span> <span class="k">if</span> <span class="n">x</span><span class="o">&lt;</span><span class="mi">20</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;20-22&quot;</span> <span class="k">if</span> <span class="mi">20</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">23</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;23-24&quot;</span> <span class="k">if</span> <span class="mi">23</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">25</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;25-26&quot;</span> <span class="k">if</span> <span class="mi">25</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">27</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;27-29&quot;</span> <span class="k">if</span> <span class="mi">27</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">30</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;30-34&quot;</span> <span class="k">if</span> <span class="mi">30</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">35</span> <span class="k">else</span> <span class="s2">&quot;35+&quot;</span><span class="p">))))))</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">]</span><span class="o">=</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span><span class="s2">&quot;&lt;20&quot;</span> <span class="k">if</span> <span class="n">x</span><span class="o">&lt;</span><span class="mi">20</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;20-22&quot;</span> <span class="k">if</span> <span class="mi">20</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">23</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;23-24&quot;</span> <span class="k">if</span> <span class="mi">23</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">25</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;25-26&quot;</span> <span class="k">if</span> <span class="mi">25</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">27</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;27-29&quot;</span> <span class="k">if</span> <span class="mi">27</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">30</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;30-34&quot;</span> <span class="k">if</span> <span class="mi">30</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">35</span> <span class="k">else</span> <span class="s2">&quot;35+&quot;</span><span class="p">))))))</span>
<span class="n">strokedatadfcur_train</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
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<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>gender</th>
      <th>age</th>
      <th>hypertension</th>
      <th>heart_disease</th>
      <th>ever_married</th>
      <th>work_type</th>
      <th>Residence_type</th>
      <th>avg_glucose_level</th>
      <th>bmi</th>
      <th>smoking_status</th>
      <th>stroke</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>1</th>
      <td>Male</td>
      <td>55-64</td>
      <td>1</td>
      <td>0</td>
      <td>Yes</td>
      <td>Private</td>
      <td>Urban</td>
      <td>healthy</td>
      <td>35+</td>
      <td>never smoked</td>
      <td>0</td>
    </tr>
    <tr>
      <th>3</th>
      <td>Female</td>
      <td>65-74</td>
      <td>0</td>
      <td>0</td>
      <td>Yes</td>
      <td>Private</td>
      <td>Rural</td>
      <td>healthy</td>
      <td>35+</td>
      <td>formerly smoked</td>
      <td>0</td>
    </tr>
    <tr>
      <th>5</th>
      <td>Female</td>
      <td>45-54</td>
      <td>0</td>
      <td>0</td>
      <td>Yes</td>
      <td>Private</td>
      <td>Urban</td>
      <td>diabetes</td>
      <td>35+</td>
      <td>unknown</td>
      <td>0</td>
    </tr>
    <tr>
      <th>6</th>
      <td>Female</td>
      <td>45-54</td>
      <td>0</td>
      <td>0</td>
      <td>Yes</td>
      <td>Private</td>
      <td>Urban</td>
      <td>healthy</td>
      <td>&lt;20</td>
      <td>formerly smoked</td>
      <td>0</td>
    </tr>
    <tr>
      <th>7</th>
      <td>Female</td>
      <td>75-84</td>
      <td>0</td>
      <td>1</td>
      <td>Yes</td>
      <td>Self-employed</td>
      <td>Rural</td>
      <td>diabetes</td>
      <td>27-29</td>
      <td>never smoked</td>
      <td>0</td>
    </tr>
    <tr>
      <th>8</th>
      <td>Female</td>
      <td>25-34</td>
      <td>0</td>
      <td>0</td>
      <td>Yes</td>
      <td>Private</td>
      <td>Rural</td>
      <td>healthy</td>
      <td>30-34</td>
      <td>smokes</td>
      <td>0</td>
    </tr>
    <tr>
      <th>9</th>
      <td>Female</td>
      <td>85+</td>
      <td>1</td>
      <td>0</td>
      <td>Yes</td>
      <td>Self-employed</td>
      <td>Urban</td>
      <td>diabetes</td>
      <td>35+</td>
      <td>never smoked</td>
      <td>0</td>
    </tr>
    <tr>
      <th>10</th>
      <td>Female</td>
      <td>75-84</td>
      <td>0</td>
      <td>0</td>
      <td>Yes</td>
      <td>Govt_job</td>
      <td>Urban</td>
      <td>healthy</td>
      <td>35+</td>
      <td>unknown</td>
      <td>0</td>
    </tr>
    <tr>
      <th>11</th>
      <td>Male</td>
      <td>75-84</td>
      <td>0</td>
      <td>1</td>
      <td>Yes</td>
      <td>Private</td>
      <td>Urban</td>
      <td>healthy</td>
      <td>20-22</td>
      <td>formerly smoked</td>
      <td>0</td>
    </tr>
    <tr>
      <th>12</th>
      <td>Female</td>
      <td>35-44</td>
      <td>0</td>
      <td>0</td>
      <td>Yes</td>
      <td>Private</td>
      <td>Rural</td>
      <td>pre-diabetes</td>
      <td>35+</td>
      <td>never smoked</td>
      <td>0</td>
    </tr>
  </tbody>
</table>
</div>
</div>

</div>

</div>
</div>

</div>
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<div class="prompt input_prompt">In&nbsp;[48]:</div>
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    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">catplot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="s1">&#39;age&#39;</span><span class="p">,</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;count&#39;</span><span class="p">,</span><span class="n">col</span><span class="o">=</span><span class="s1">&#39;stroke&#39;</span><span class="p">,</span><span class="n">data</span><span class="o">=</span><span class="n">strokedatadfcur_train</span><span class="p">,</span> <span class="n">order</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;16-24&#39;</span><span class="p">,</span><span class="s1">&#39;25-34&#39;</span><span class="p">,</span><span class="s1">&#39;35-44&#39;</span><span class="p">,</span><span class="s1">&#39;45-54&#39;</span><span class="p">,</span><span class="s1">&#39;55-64&#39;</span><span class="p">,</span><span class="s1">&#39;65-74&#39;</span><span class="p">,</span><span class="s1">&#39;75-84&#39;</span><span class="p">,</span><span class="s1">&#39;85+&#39;</span><span class="p">])</span>
</pre></div>

    </div>
</div>
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    <div class="prompt output_prompt">Out[48]:</div>


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<pre>&lt;seaborn.axisgrid.FacetGrid at 0x7fd266f8b7f0&gt;</pre>
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    <div class="prompt"></div>


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<div class="prompt input_prompt">In&nbsp;[49]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">catplot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="s1">&#39;avg_glucose_level&#39;</span><span class="p">,</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;count&#39;</span><span class="p">,</span><span class="n">col</span><span class="o">=</span><span class="s1">&#39;stroke&#39;</span><span class="p">,</span><span class="n">data</span><span class="o">=</span><span class="n">strokedatadfcur_train</span><span class="p">,</span>  <span class="n">order</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;healthy&#39;</span><span class="p">,</span><span class="s1">&#39;pre-diabetes&#39;</span><span class="p">,</span> <span class="s1">&#39;diabetes&#39;</span><span class="p">])</span>
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    <div class="prompt output_prompt">Out[49]:</div>


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<div class="prompt input_prompt">In&nbsp;[50]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">catplot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="s1">&#39;bmi&#39;</span><span class="p">,</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;count&#39;</span><span class="p">,</span><span class="n">col</span><span class="o">=</span><span class="s1">&#39;stroke&#39;</span><span class="p">,</span><span class="n">data</span><span class="o">=</span><span class="n">strokedatadfcur_train</span><span class="p">,</span>  <span class="n">order</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;&lt;20&#39;</span><span class="p">,</span><span class="s1">&#39;20-22&#39;</span><span class="p">,</span> <span class="s1">&#39;23-24&#39;</span><span class="p">,</span><span class="s1">&#39;25-26&#39;</span><span class="p">,</span><span class="s1">&#39;27-29&#39;</span><span class="p">,</span><span class="s1">&#39;30-34&#39;</span><span class="p">,</span><span class="s1">&#39;35+&#39;</span><span class="p">])</span>
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<pre>&lt;seaborn.axisgrid.FacetGrid at 0x7fd266da1128&gt;</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Encoding data</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;ever_married&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;ever_married&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;work_type&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;work_type&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;Residence_type&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;Residence_type&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;smoking_status&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;smoking_status&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;avg_glucose_level&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;avg_glucose_level&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedf_test</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;ever_married&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;ever_married&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;work_type&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;work_type&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;Residence_type&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;Residence_type&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;smoking_status&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;smoking_status&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;avg_glucose_level&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;avg_glucose_level&#39;</span><span class="p">])</span>

<span class="c1">#Resampling data (as described earlier)</span>
<span class="n">X_resampcur</span><span class="p">,</span> <span class="n">y_resampcur</span><span class="o">=</span><span class="n">smote</span><span class="o">.</span><span class="n">fit_resample</span><span class="p">(</span><span class="n">strokedatadfcur_train</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span><span class="n">strokedatadfcur_train</span><span class="o">.</span><span class="n">columns</span><span class="o">!=</span><span class="s1">&#39;stroke&#39;</span><span class="p">],</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;stroke&#39;</span><span class="p">])</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">format</span><span class="p">(</span><span class="n">X_resampcur</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">format</span><span class="p">(</span><span class="n">y_resampcur</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
<span class="n">y_resamp</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
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<pre>(71088, 10)
(71088,)
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<pre>1    35544
0    35544
Name: stroke, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">X_traincur</span><span class="p">,</span> <span class="n">X_testcur</span><span class="p">,</span> <span class="n">y_traincur</span><span class="p">,</span> <span class="n">y_testcur</span> <span class="o">=</span> <span class="n">train_test_split</span><span class="p">(</span><span class="n">X_resampcur</span><span class="p">,</span> <span class="n">y_resampcur</span><span class="p">,</span> <span class="n">test_size</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">77</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">RFmod</span><span class="o">=</span><span class="n">RandomForestClassifier</span><span class="p">(</span><span class="n">n_estimators</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span><span class="n">random_state</span><span class="o">=</span><span class="mi">77</span><span class="p">)</span>
<span class="n">RFmod</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_traincur</span><span class="p">,</span><span class="n">y_traincur</span><span class="p">)</span>
<span class="n">RFmod</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="n">X_traincur</span><span class="p">,</span><span class="n">y_traincur</span><span class="p">)</span>
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<pre>0.9173553719008265</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">RFpred</span> <span class="o">=</span> <span class="n">RFmod</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_testcur</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Accuracy score:&#39;</span><span class="p">,</span> <span class="n">accuracy_score</span><span class="p">(</span><span class="n">y_testcur</span><span class="p">,</span><span class="n">RFpred</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;F1 score:&#39;</span><span class="p">,</span> <span class="n">f1_score</span><span class="p">(</span><span class="n">y_testcur</span><span class="p">,</span> <span class="n">RFpred</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Recall score:&#39;</span><span class="p">,</span> <span class="n">recall_score</span><span class="p">(</span><span class="n">y_testcur</span><span class="p">,</span> <span class="n">RFpred</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Precision score:&#39;</span><span class="p">,</span> <span class="n">precision_score</span><span class="p">(</span><span class="n">y_testcur</span><span class="p">,</span> <span class="n">RFpred</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Confusion matrix:&#39;</span><span class="p">,</span> <span class="n">confusion_matrix</span><span class="p">(</span><span class="n">y_testcur</span><span class="p">,</span> <span class="n">RFpred</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Classification report:&#39;</span><span class="p">,</span> <span class="n">classification_report</span><span class="p">(</span><span class="n">y_testcur</span><span class="p">,</span> <span class="n">RFpred</span><span class="p">))</span>
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<pre>Accuracy score: 90.60346040230694
F1 score: 90.9912339851652
Recall score: 95.13536379018612
Precision score: 87.19307314551563
Confusion matrix: [[6135  991]
 [ 345 6747]]
Classification report:               precision    recall  f1-score   support

           0       0.95      0.86      0.90      7126
           1       0.87      0.95      0.91      7092

    accuracy                           0.91     14218
   macro avg       0.91      0.91      0.91     14218
weighted avg       0.91      0.91      0.91     14218

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">featurelist</span><span class="o">=</span><span class="nb">list</span><span class="p">(</span><span class="n">strokedatadfcur_train</span><span class="o">.</span><span class="n">columns</span><span class="p">[:])</span>
<span class="n">plt</span><span class="o">.</span><span class="n">bar</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">RFmod</span><span class="o">.</span><span class="n">feature_importances_</span><span class="p">)),</span> <span class="n">RFmod</span><span class="o">.</span><span class="n">feature_importances_</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">&quot;feature&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;importance&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;feature importance&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xticks</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">RFmod</span><span class="o">.</span><span class="n">feature_importances_</span><span class="p">)),</span> <span class="n">featurelist</span><span class="p">,</span><span class="n">rotation</span><span class="o">=</span><span class="s1">&#39;vertical&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
<span class="nb">print</span><span class="p">(</span><span class="n">featurelist</span><span class="p">)</span>
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<pre>[&#39;gender&#39;, &#39;age&#39;, &#39;hypertension&#39;, &#39;heart_disease&#39;, &#39;ever_married&#39;, &#39;work_type&#39;, &#39;Residence_type&#39;, &#39;avg_glucose_level&#39;, &#39;bmi&#39;, &#39;smoking_status&#39;, &#39;stroke&#39;]
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">RFprestest</span> <span class="o">=</span> <span class="n">RFmod</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">strokedatadfcur_test</span><span class="p">)</span>
<span class="n">RFpredf</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">RFprestest</span><span class="p">,</span><span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;prediction&#39;</span><span class="p">])</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">strokedatadfcur_test</span><span class="p">))</span>
<span class="n">RFpredf</span><span class="p">[</span><span class="s1">&#39;prediction&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
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<pre>15568
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<pre>0    13409
1     2159
Name: prediction, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">###Curated approach v2, repeating cleaning from curatved v1 with exceptions</span>
<span class="n">strokedatacur_train</span><span class="o">=</span><span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;train_2v.csv&#39;</span><span class="p">)</span>
<span class="n">strokedatacur_test</span><span class="o">=</span><span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;test_2v.csv&#39;</span><span class="p">)</span>
<span class="n">strokedatadfcur_train</span><span class="o">=</span><span class="n">strokedatacur_train</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;id&#39;</span><span class="p">,</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">strokedatadfcur_test</span><span class="o">=</span><span class="n">strokedatacur_test</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;id&#39;</span><span class="p">,</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">strokedatadfcur_train</span> <span class="o">=</span> <span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">]</span> <span class="o">!=</span> <span class="s2">&quot;Other&quot;</span><span class="p">]</span>
<span class="n">strokedatadfcur_test</span> <span class="o">=</span> <span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">]</span> <span class="o">!=</span> <span class="s2">&quot;Other&quot;</span><span class="p">]</span>
<span class="n">strokedatadfcur_train</span> <span class="o">=</span> <span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">16</span><span class="p">]</span>
<span class="n">strokedatadfcur_test</span> <span class="o">=</span> <span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">16</span><span class="p">]</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">median</span><span class="p">(),</span> <span class="n">inplace</span><span class="o">=</span> <span class="kc">True</span><span class="p">)</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;bmi&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">median</span><span class="p">(),</span> <span class="n">inplace</span><span class="o">=</span> <span class="kc">True</span><span class="p">)</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;smoking_status&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="n">value</span><span class="o">=</span><span class="s1">&#39;unknown&#39;</span><span class="p">,</span><span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;smoking_status&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="n">value</span><span class="o">=</span><span class="s1">&#39;unknown&#39;</span><span class="p">,</span><span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span><span class="o">=</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span><span class="s2">&quot;16-24&quot;</span> <span class="k">if</span> <span class="mi">16</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">25</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;25-34&quot;</span> <span class="k">if</span> <span class="mi">25</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">35</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;35-44&quot;</span> <span class="k">if</span> <span class="mi">35</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">44</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;45-54&quot;</span> <span class="k">if</span> <span class="mi">45</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">54</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;55-64&quot;</span> <span class="k">if</span> <span class="mi">55</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">64</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;65-74&quot;</span> <span class="k">if</span> <span class="mi">65</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">74</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;75-84&quot;</span> <span class="k">if</span> <span class="mi">75</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">84</span> <span class="k">else</span> <span class="s2">&quot;85+&quot;</span><span class="p">)))))))</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span><span class="o">=</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span><span class="s2">&quot;16-24&quot;</span> <span class="k">if</span> <span class="mi">16</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">25</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;25-34&quot;</span> <span class="k">if</span> <span class="mi">25</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">35</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;35-44&quot;</span> <span class="k">if</span> <span class="mi">35</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">44</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;45-54&quot;</span> <span class="k">if</span> <span class="mi">45</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">54</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;55-64&quot;</span> <span class="k">if</span> <span class="mi">55</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">64</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;65-74&quot;</span> <span class="k">if</span> <span class="mi">65</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">74</span> <span class="k">else</span> <span class="p">(</span><span class="s2">&quot;75-84&quot;</span> <span class="k">if</span> <span class="mi">75</span><span class="o">&lt;=</span><span class="n">x</span><span class="o">&lt;</span><span class="mi">84</span> <span class="k">else</span> <span class="s2">&quot;85+&quot;</span><span class="p">)))))))</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;ever_married&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;ever_married&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;work_type&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;work_type&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;Residence_type&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;Residence_type&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;smoking_status&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;smoking_status&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedf_test</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;ever_married&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;ever_married&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;work_type&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;work_type&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;Residence_type&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;Residence_type&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;smoking_status&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;smoking_status&#39;</span><span class="p">])</span>
<span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">enc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">strokedatadfcur_test</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">])</span>

<span class="n">X_resampcur</span><span class="p">,</span> <span class="n">y_resampcur</span><span class="o">=</span><span class="n">smote</span><span class="o">.</span><span class="n">fit_resample</span><span class="p">(</span><span class="n">strokedatadfcur_train</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span><span class="n">strokedatadfcur_train</span><span class="o">.</span><span class="n">columns</span><span class="o">!=</span><span class="s1">&#39;stroke&#39;</span><span class="p">],</span><span class="n">strokedatadfcur_train</span><span class="p">[</span><span class="s1">&#39;stroke&#39;</span><span class="p">])</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">format</span><span class="p">(</span><span class="n">X_resampcur</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">format</span><span class="p">(</span><span class="n">y_resampcur</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
<span class="n">y_resamp</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
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<pre>(71088, 10)
(71088,)
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<pre>1    35544
0    35544
Name: stroke, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">strokedatadfcur_test</span><span class="o">.</span><span class="n">info</span><span class="p">()</span>
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<pre>&lt;class &#39;pandas.core.frame.DataFrame&#39;&gt;
Int64Index: 15568 entries, 0 to 18600
Data columns (total 10 columns):
 #   Column             Non-Null Count  Dtype  
---  ------             --------------  -----  
 0   gender             15568 non-null  int64  
 1   age                15568 non-null  int64  
 2   hypertension       15568 non-null  int64  
 3   heart_disease      15568 non-null  int64  
 4   ever_married       15568 non-null  int64  
 5   work_type          15568 non-null  int64  
 6   Residence_type     15568 non-null  int64  
 7   avg_glucose_level  15568 non-null  float64
 8   bmi                15568 non-null  float64
 9   smoking_status     15568 non-null  int64  
dtypes: float64(2), int64(8)
memory usage: 1.3 MB
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">X_traincur</span><span class="p">,</span> <span class="n">X_testcur</span><span class="p">,</span> <span class="n">y_traincur</span><span class="p">,</span> <span class="n">y_testcur</span> <span class="o">=</span> <span class="n">train_test_split</span><span class="p">(</span><span class="n">X_resampcur</span><span class="p">,</span> <span class="n">y_resampcur</span><span class="p">,</span> <span class="n">test_size</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">77</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">RFmod</span><span class="o">=</span><span class="n">RandomForestClassifier</span><span class="p">(</span><span class="n">n_estimators</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span><span class="n">random_state</span><span class="o">=</span><span class="mi">77</span><span class="p">)</span>
<span class="n">RFmod</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_traincur</span><span class="p">,</span><span class="n">y_traincur</span><span class="p">)</span>
<span class="n">RFmod</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="n">X_traincur</span><span class="p">,</span><span class="n">y_traincur</span><span class="p">)</span>
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<pre>0.9999648320731492</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">RFpred</span> <span class="o">=</span> <span class="n">RFmod</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_testcur</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Accuracy score:&#39;</span><span class="p">,</span> <span class="n">accuracy_score</span><span class="p">(</span><span class="n">y_testcur</span><span class="p">,</span><span class="n">RFpred</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;F1 score:&#39;</span><span class="p">,</span> <span class="n">f1_score</span><span class="p">(</span><span class="n">y_testcur</span><span class="p">,</span> <span class="n">RFpred</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Recall score:&#39;</span><span class="p">,</span> <span class="n">recall_score</span><span class="p">(</span><span class="n">y_testcur</span><span class="p">,</span> <span class="n">RFpred</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Precision score:&#39;</span><span class="p">,</span> <span class="n">precision_score</span><span class="p">(</span><span class="n">y_testcur</span><span class="p">,</span> <span class="n">RFpred</span><span class="p">)</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Confusion matrix:&#39;</span><span class="p">,</span> <span class="n">confusion_matrix</span><span class="p">(</span><span class="n">y_testcur</span><span class="p">,</span> <span class="n">RFpred</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Classification report:&#39;</span><span class="p">,</span> <span class="n">classification_report</span><span class="p">(</span><span class="n">y_testcur</span><span class="p">,</span> <span class="n">RFpred</span><span class="p">))</span>
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<pre>Accuracy score: 96.01209734139823
F1 score: 96.07259125857172
Recall score: 97.7862380146644
Precision score: 94.41797140912185
Confusion matrix: [[6716  410]
 [ 157 6935]]
Classification report:               precision    recall  f1-score   support

           0       0.98      0.94      0.96      7126
           1       0.94      0.98      0.96      7092

    accuracy                           0.96     14218
   macro avg       0.96      0.96      0.96     14218
weighted avg       0.96      0.96      0.96     14218

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<div class="prompt input_prompt">In&nbsp;[62]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">featurelist</span><span class="o">=</span><span class="nb">list</span><span class="p">(</span><span class="n">strokedatadfcur_train</span><span class="o">.</span><span class="n">columns</span><span class="p">[:])</span>
<span class="n">plt</span><span class="o">.</span><span class="n">bar</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">RFmod</span><span class="o">.</span><span class="n">feature_importances_</span><span class="p">)),</span> <span class="n">RFmod</span><span class="o">.</span><span class="n">feature_importances_</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">&quot;feature&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;importance&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;feature importance&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xticks</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">RFmod</span><span class="o">.</span><span class="n">feature_importances_</span><span class="p">)),</span> <span class="n">featurelist</span><span class="p">,</span><span class="n">rotation</span><span class="o">=</span><span class="s1">&#39;vertical&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
<span class="nb">print</span><span class="p">(</span><span class="n">featurelist</span><span class="p">)</span>
</pre></div>

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<pre>[&#39;gender&#39;, &#39;age&#39;, &#39;hypertension&#39;, &#39;heart_disease&#39;, &#39;ever_married&#39;, &#39;work_type&#39;, &#39;Residence_type&#39;, &#39;avg_glucose_level&#39;, &#39;bmi&#39;, &#39;smoking_status&#39;, &#39;stroke&#39;]
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<div class="prompt input_prompt">In&nbsp;[63]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">RFprestest</span> <span class="o">=</span> <span class="n">RFmod</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">strokedatadfcur_test</span><span class="p">)</span>
<span class="n">RFpredf</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">RFprestest</span><span class="p">,</span><span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;prediction&#39;</span><span class="p">])</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">strokedatadfcur_test</span><span class="p">))</span>
<span class="n">RFpredf</span><span class="p">[</span><span class="s1">&#39;prediction&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
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<pre>15568
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<pre>0    14660
1      908
Name: prediction, dtype: int64</pre>
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