update Pandas value_counts()

Author: BindiChen

data-analysis/046-pandas-value_counts/pandas-value_counts.ipynb

@@ -15,7 +15,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -25,7 +25,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -166,7 +166,7 @@
        "4      0            373450   8.0500   NaN        S  "
       ]
      },
-     "execution_count": 10,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -358,7 +358,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "pd.set_option('display.float_format', '{:.2f}%'.format)"
+    "pd.set_option('display.float_format', '{:.2%}'.format)\n",
+    "\n",
+    "# Note: By calling the statement, you will update Pandas default display settings \n",
+    "# and apply to all float values. To reset it, you can call\n",
+    "#      pd.reset_option('display.float_format')"
    ]
   },
   {
@@ -369,9 +373,9 @@
     {
      "data": {
       "text/plain": [
-       "S   0.72%\n",
-       "C   0.19%\n",
-       "Q   0.09%\n",
+       "S   72.44%\n",
+       "C   18.90%\n",
+       "Q    8.66%\n",
        "Name: Embarked, dtype: float64"
       ]
      },
@@ -384,6 +388,56 @@
     "df['Embarked'].value_counts(normalize = True)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pd.reset_option('display.float_format')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "</style><table id=\"T_de79ef6a_0f55_11ec_8a56_acde48001122\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Embarked</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_de79ef6a_0f55_11ec_8a56_acde48001122level0_row0\" class=\"row_heading level0 row0\" >S</th>\n",
+       "                        <td id=\"T_de79ef6a_0f55_11ec_8a56_acde48001122row0_col0\" class=\"data row0 col0\" >72.44%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_de79ef6a_0f55_11ec_8a56_acde48001122level0_row1\" class=\"row_heading level0 row1\" >C</th>\n",
+       "                        <td id=\"T_de79ef6a_0f55_11ec_8a56_acde48001122row1_col0\" class=\"data row1 col0\" >18.90%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_de79ef6a_0f55_11ec_8a56_acde48001122level0_row2\" class=\"row_heading level0 row2\" >Q</th>\n",
+       "                        <td id=\"T_de79ef6a_0f55_11ec_8a56_acde48001122row2_col0\" class=\"data row2 col0\" >8.66%</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fb2914f74d0>"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Thanks for David B Rosen's advice (https://dabruro.medium.com/)\n",
+    "#\n",
+    "# Instead of Pandas display option, which would change the display of all float values, \n",
+    "# you can can simply do this: \n",
+    "df['Embarked'].value_counts(normalize = True).to_frame().style.format('{:.2%}')"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -393,7 +447,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -405,7 +459,7 @@
        "Name: Fare, dtype: int64"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -416,7 +470,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -428,7 +482,7 @@
        "Name: Fare, dtype: int64"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -446,7 +500,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -462,7 +516,7 @@
        "Name: Sex, dtype: int64"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -480,7 +534,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -556,7 +610,7 @@
        "         female  203"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -574,7 +628,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -635,7 +689,7 @@
        "ant            6          0"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -651,7 +705,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -664,7 +718,7 @@
        "dtype: int64"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -675,7 +729,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -736,7 +790,7 @@
        "2        2          1"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }