Simple Healthcare Chatbot.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ------------------------- Simple Healthcare Chatbot --------------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importing the required libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "from sklearn import preprocessing\n",
    "from sklearn.tree import DecisionTreeClassifier,_tree\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn import model_selection\n",
    "from sklearn.tree import export_graphviz\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\", category=DeprecationWarning)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importing the datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "training = pd.read_csv('Chatbot_Training.csv')\n",
    "testing  = pd.read_csv('Chatbot_Testing.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analyzing the data and performing required operations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>itching</th>\n",
       "      <th>skin_rash</th>\n",
       "      <th>nodal_skin_eruptions</th>\n",
       "      <th>continuous_sneezing</th>\n",
       "      <th>shivering</th>\n",
       "      <th>chills</th>\n",
       "      <th>joint_pain</th>\n",
       "      <th>stomach_pain</th>\n",
       "      <th>acidity</th>\n",
       "      <th>ulcers_on_tongue</th>\n",
       "      <th>...</th>\n",
       "      <th>blackheads</th>\n",
       "      <th>scurring</th>\n",
       "      <th>skin_peeling</th>\n",
       "      <th>silver_like_dusting</th>\n",
       "      <th>small_dents_in_nails</th>\n",
       "      <th>inflammatory_nails</th>\n",
       "      <th>blister</th>\n",
       "      <th>red_sore_around_nose</th>\n",
       "      <th>yellow_crust_ooze</th>\n",
       "      <th>prognosis</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Fungal infection</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Fungal infection</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Fungal infection</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Fungal infection</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Fungal infection</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 133 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   itching  skin_rash  nodal_skin_eruptions  continuous_sneezing  shivering  \\\n",
       "0        1          1                     1                    0          0   \n",
       "1        0          1                     1                    0          0   \n",
       "2        1          0                     1                    0          0   \n",
       "3        1          1                     0                    0          0   \n",
       "4        1          1                     1                    0          0   \n",
       "\n",
       "   chills  joint_pain  stomach_pain  acidity  ulcers_on_tongue  ...  \\\n",
       "0       0           0             0        0                 0  ...   \n",
       "1       0           0             0        0                 0  ...   \n",
       "2       0           0             0        0                 0  ...   \n",
       "3       0           0             0        0                 0  ...   \n",
       "4       0           0             0        0                 0  ...   \n",
       "\n",
       "   blackheads  scurring  skin_peeling  silver_like_dusting  \\\n",
       "0           0         0             0                    0   \n",
       "1           0         0             0                    0   \n",
       "2           0         0             0                    0   \n",
       "3           0         0             0                    0   \n",
       "4           0         0             0                    0   \n",
       "\n",
       "   small_dents_in_nails  inflammatory_nails  blister  red_sore_around_nose  \\\n",
       "0                     0                   0        0                     0   \n",
       "1                     0                   0        0                     0   \n",
       "2                     0                   0        0                     0   \n",
       "3                     0                   0        0                     0   \n",
       "4                     0                   0        0                     0   \n",
       "\n",
       "   yellow_crust_ooze         prognosis  \n",
       "0                  0  Fungal infection  \n",
       "1                  0  Fungal infection  \n",
       "2                  0  Fungal infection  \n",
       "3                  0  Fungal infection  \n",
       "4                  0  Fungal infection  \n",
       "\n",
       "[5 rows x 133 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "training.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>itching</th>\n",
       "      <th>skin_rash</th>\n",
       "      <th>nodal_skin_eruptions</th>\n",
       "      <th>continuous_sneezing</th>\n",
       "      <th>shivering</th>\n",
       "      <th>chills</th>\n",
       "      <th>joint_pain</th>\n",
       "      <th>stomach_pain</th>\n",
       "      <th>acidity</th>\n",
       "      <th>ulcers_on_tongue</th>\n",
       "      <th>...</th>\n",
       "      <th>blackheads</th>\n",
       "      <th>scurring</th>\n",
       "      <th>skin_peeling</th>\n",
       "      <th>silver_like_dusting</th>\n",
       "      <th>small_dents_in_nails</th>\n",
       "      <th>inflammatory_nails</th>\n",
       "      <th>blister</th>\n",
       "      <th>red_sore_around_nose</th>\n",
       "      <th>yellow_crust_ooze</th>\n",
       "      <th>prognosis</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Fungal infection</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Allergy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>GERD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Chronic cholestasis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Drug Reaction</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 133 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   itching  skin_rash  nodal_skin_eruptions  continuous_sneezing  shivering  \\\n",
       "0        1          1                     1                    0          0   \n",
       "1        0          0                     0                    1          1   \n",
       "2        0          0                     0                    0          0   \n",
       "3        1          0                     0                    0          0   \n",
       "4        1          1                     0                    0          0   \n",
       "\n",
       "   chills  joint_pain  stomach_pain  acidity  ulcers_on_tongue  ...  \\\n",
       "0       0           0             0        0                 0  ...   \n",
       "1       1           0             0        0                 0  ...   \n",
       "2       0           0             1        1                 1  ...   \n",
       "3       0           0             0        0                 0  ...   \n",
       "4       0           0             1        0                 0  ...   \n",
       "\n",
       "   blackheads  scurring  skin_peeling  silver_like_dusting  \\\n",
       "0           0         0             0                    0   \n",
       "1           0         0             0                    0   \n",
       "2           0         0             0                    0   \n",
       "3           0         0             0                    0   \n",
       "4           0         0             0                    0   \n",
       "\n",
       "   small_dents_in_nails  inflammatory_nails  blister  red_sore_around_nose  \\\n",
       "0                     0                   0        0                     0   \n",
       "1                     0                   0        0                     0   \n",
       "2                     0                   0        0                     0   \n",
       "3                     0                   0        0                     0   \n",
       "4                     0                   0        0                     0   \n",
       "\n",
       "   yellow_crust_ooze            prognosis  \n",
       "0                  0     Fungal infection  \n",
       "1                  0              Allergy  \n",
       "2                  0                 GERD  \n",
       "3                  0  Chronic cholestasis  \n",
       "4                  0        Drug Reaction  \n",
       "\n",
       "[5 rows x 133 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testing.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4920 entries, 0 to 4919\n",
      "Columns: 133 entries, itching to prognosis\n",
      "dtypes: int64(132), object(1)\n",
      "memory usage: 5.0+ MB\n"
     ]
    }
   ],
   "source": [
    "training.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 41 entries, 0 to 40\n",
      "Columns: 133 entries, itching to prognosis\n",
      "dtypes: int64(132), object(1)\n",
      "memory usage: 42.7+ KB\n"
     ]
    }
   ],
   "source": [
    "testing.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4920, 133)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "training.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(41, 133)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testing.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols = training.columns\n",
    "cols = cols[:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = training[cols]\n",
    "y = training['prognosis']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "y1 = y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "reduced_data = training.groupby(training['prognosis']).max()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### We need to map strings to numbers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "le = preprocessing.LabelEncoder()\n",
    "le.fit(y)\n",
    "y = le.transform(y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Performing the train_test_split operation on the training dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.33, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "testx = testing[cols]\n",
    "testy = testing['prognosis']  \n",
    "testy = le.transform(testy)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Building"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "clf1  = DecisionTreeClassifier()\n",
    "clf = clf1.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "importances = clf.feature_importances_\n",
    "indices = np.argsort(importances)[::-1]\n",
    "features = cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Please reply Yes or No for the following symptoms\n",
      "loss_of_smell ?\n",
      "no\n",
      "internal_itching ?\n",
      "no\n",
      "hip_joint_pain ?\n",
      "no\n",
      "polyuria ?\n",
      "no\n",
      "silver_like_dusting ?\n",
      "no\n",
      "swollen_extremeties ?\n",
      "no\n",
      "blood_in_sputum ?\n",
      "no\n",
      "yellow_crust_ooze ?\n",
      "no\n",
      "nodal_skin_eruptions ?\n",
      "no\n",
      "unsteadiness ?\n",
      "no\n",
      "weight_loss ?\n",
      "no\n",
      "prominent_veins_on_calf ?\n",
      "no\n",
      "fluid_overload.1 ?\n",
      "no\n",
      "depression ?\n",
      "yes\n",
      "['You may have Migraine']\n",
      "symptoms present  ['depression']\n",
      "symptoms given ['acidity', 'indigestion', 'headache', 'blurred_and_distorted_vision', 'excessive_hunger', 'stiff_neck', 'depression', 'irritability', 'visual_disturbances']\n"
     ]
    }
   ],
   "source": [
    "print(\"Please reply Yes or No for the following symptoms\") \n",
    "def print_disease(node):\n",
    "    node = node[0]\n",
    "    val  = node.nonzero() \n",
    "    disease = le.inverse_transform(val[0])\n",
    "    return disease\n",
    "def tree_to_code(tree, feature_names):\n",
    "    tree_ = tree.tree_\n",
    "    feature_name = [\n",
    "        feature_names[i] if i != _tree.TREE_UNDEFINED else \"undefined!\"\n",
    "        for i in tree_.feature\n",
    "    ]\n",
    "    symptoms_present = []\n",
    "    def recurse(node, depth):\n",
    "        indent = \"  \" * depth\n",
    "        if tree_.feature[node] != _tree.TREE_UNDEFINED:\n",
    "            name = feature_name[node]\n",
    "            threshold = tree_.threshold[node]\n",
    "            print(name + \" ?\")\n",
    "            ans = input()\n",
    "            ans = ans.lower()\n",
    "            if ans == 'yes':\n",
    "                val = 1\n",
    "            else:\n",
    "                val = 0\n",
    "            if  val <= threshold:\n",
    "                recurse(tree_.children_left[node], depth + 1)\n",
    "            else:\n",
    "                symptoms_present.append(name)\n",
    "                recurse(tree_.children_right[node], depth + 1)\n",
    "        else:\n",
    "            present_disease = print_disease(tree_.value[node])\n",
    "            print( \"You may have \" +  present_disease )\n",
    "            red_cols = reduced_data.columns \n",
    "            symptoms_given = red_cols[reduced_data.loc[present_disease].values[0].nonzero()]\n",
    "            print(\"symptoms present  \" + str(list(symptoms_present)))\n",
    "            print(\"symptoms given \"  +  str(list(symptoms_given)) )  \n",
    "            confidence_level = (1.0*len(symptoms_present))/len(symptoms_given)\n",
    "\n",
    "    recurse(0, 1)\n",
    "\n",
    "tree_to_code(clf,cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}