{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Features importance\n",
    "\n",
    "The methode *features_importance* displays a bar chart representing the<br />\n",
    "sum of absolute contribution values of each feature.\n",
    "\n",
    "This method also makes it possible to represent this sum calculated <br />\n",
    "on a subset and to compare it with the total population\n",
    "\n",
    "<b>This short tutorial </b>presents the different parameters you can use.\n",
    "\n",
    "Content :\n",
    "- Classification case: Specify the target modality to display.\n",
    "- selection parameter to display a subset\n",
    "- max_features parameter limits the number of features \n",
    "\n",
    "We used Kaggle's [Titanic](https://www.kaggle.com/c/titanic/data) dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from category_encoders import OrdinalEncoder\n",
    "from sklearn.ensemble import ExtraTreesClassifier\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Building Supervized Model "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load Titanic data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from shapash.data.data_loader import data_loading\n",
    "titanic_df, titanic_dict = data_loading('titanic')\n",
    "del titanic_df['Name']\n",
    "y_df=titanic_df['Survived'].to_frame()\n",
    "X_df=titanic_df[titanic_df.columns.difference(['Survived'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>Title</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerId</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>Third class</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7.25</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>Mr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>First class</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>71.28</td>\n",
       "      <td>Cherbourg</td>\n",
       "      <td>Mrs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>Third class</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.92</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>Miss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>First class</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53.10</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>Mrs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>Third class</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.05</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>Mr</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Survived       Pclass     Sex   Age  SibSp  Parch   Fare  \\\n",
       "PassengerId                                                             \n",
       "1                   0  Third class    male  22.0      1      0   7.25   \n",
       "2                   1  First class  female  38.0      1      0  71.28   \n",
       "3                   1  Third class  female  26.0      0      0   7.92   \n",
       "4                   1  First class  female  35.0      1      0  53.10   \n",
       "5                   0  Third class    male  35.0      0      0   8.05   \n",
       "\n",
       "                Embarked Title  \n",
       "PassengerId                     \n",
       "1            Southampton    Mr  \n",
       "2              Cherbourg   Mrs  \n",
       "3            Southampton  Miss  \n",
       "4            Southampton   Mrs  \n",
       "5            Southampton    Mr  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load Titanic data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from category_encoders import OrdinalEncoder\n",
    "\n",
    "categorical_features = [col for col in X_df.columns if X_df[col].dtype == 'object']\n",
    "\n",
    "encoder = OrdinalEncoder(\n",
    "    cols=categorical_features,\n",
    "    handle_unknown='ignore',\n",
    "    return_df=True).fit(X_df)\n",
    "\n",
    "X_df=encoder.transform(X_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Train / Test Split + model fitting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "Xtrain, Xtest, ytrain, ytest = train_test_split(X_df, y_df, train_size=0.75, random_state=7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "clf = ExtraTreesClassifier(n_estimators=200).fit(Xtrain,ytrain)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### First step: You need to Declare and Compile SmartExplainer "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from shapash import SmartExplainer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "response_dict = {0: 'Death', 1:' Survival'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "xpl = SmartExplainer(\n",
    "    model=clf,\n",
    "    preprocessing=encoder,      # Optional: compile step can use inverse_transform method\n",
    "    features_dict=titanic_dict, # Optional parameters\n",
    "    label_dict=response_dict    # Optional parameters, dicts specify labels \n",
    ") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Backend: Shap TreeExplainer\n"
     ]
    }
   ],
   "source": [
    "xpl.compile(x=Xtest)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Display Feature Importance\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xpl.plot.features_importance()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Multiclass: Select the target modality\n",
    "\n",
    "Features importances sum and display the absolute contribution for one target modality.<br />\n",
    "you can change this modality, selecting with *label* parameter: <br />\n",
    "\n",
    "<b>xpl.plot.features_importance(label='Death')</b><br />\n",
    "\n",
    "with label parameter you can specify target value, label or number "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Focus and compare a subset\n",
    "\n",
    "selection parameter specify the subset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "sel = [581, 610, 524, 636, 298, 420, 568, 817, 363, 557,\n",
    "       486, 252, 390, 505, 16, 290, 611, 148, 438, 23, 810,\n",
    "       875, 206, 836, 143, 843, 436, 701, 681, 67, 10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xpl.plot.features_importance(selection=sel)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tune the number of features to display\n",
    "\n",
    "Use max_features parameter (default value: 20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xpl.plot.features_importance(max_features=3)"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Aucun(e)",
  "hide_input": false,
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}