tutorial/postprocess/tuto-postprocess01.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Postprocessing parameter in compile method\n",
    "\n",
    "Compile method is a method that creates the explainer you need for your model.<br /> This compile method has many parameters, and among those is `postprocessing` parameter, that will be explained in this tutorial. <br />\n",
    "This parameter allows to **modify** the dataset with several techniques, for a better visualization.\n",
    "<b>This tutorial </b>presents the different way you can modify data, and the right syntax to do it.\n",
    "\n",
    "Contents:\n",
    "- Loading dataset and fitting a model.\n",
    "\n",
    "- Creating our SmartExplainer and compiling it without postprocessing.\n",
    "\n",
    "- New SmartExplainer with postprocessing parameter.\n",
    "\n",
    "\n",
    "Data from Kaggle: [Titanic](https://www.kaggle.com/c/titanic/data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.ensemble import RandomForestClassifier"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Building Supervized Model "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### First step : Importing our dataset"
   ]
  },
  {
   "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",
    "y_df=titanic_df['Survived']\n",
    "X_df=titanic_df[titanic_df.columns.difference(['Survived'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\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>Name</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",
       "      <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>Braund Owen Harris</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>Cumings John Bradley (Florence Briggs Thayer)</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>Heikkinen Laina</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>Futrelle Jacques Heath (Lily May Peel)</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>Allen William Henry</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  \\\n",
       "PassengerId                          \n",
       "1                   0  Third class   \n",
       "2                   1  First class   \n",
       "3                   1  Third class   \n",
       "4                   1  First class   \n",
       "5                   0  Third class   \n",
       "\n",
       "                                                      Name     Sex   Age  \\\n",
       "PassengerId                                                                \n",
       "1                                       Braund Owen Harris    male  22.0   \n",
       "2            Cumings John Bradley (Florence Briggs Thayer)  female  38.0   \n",
       "3                                          Heikkinen Laina  female  26.0   \n",
       "4                   Futrelle Jacques Heath (Lily May Peel)  female  35.0   \n",
       "5                                      Allen William Henry    male  35.0   \n",
       "\n",
       "             SibSp  Parch   Fare     Embarked Title  \n",
       "PassengerId                                          \n",
       "1                1      0   7.25  Southampton    Mr  \n",
       "2                1      0  71.28    Cherbourg   Mrs  \n",
       "3                0      0   7.92  Southampton  Miss  \n",
       "4                1      0  53.10  Southampton   Mrs  \n",
       "5                0      0   8.05  Southampton    Mr  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Second step : Encode our categorical variables"
   ]
  },
  {
   "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": [
    "#### Third step : Train/test split and fitting our model"
   ]
  },
  {
   "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=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "classifier = RandomForestClassifier(n_estimators=200).fit(Xtrain, ytrain)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = pd.DataFrame(classifier.predict(Xtest), columns=['pred'], index=Xtest.index) # Predictions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Fourth step : Declaring our Explainer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from shapash import SmartExplainer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "xpl = SmartExplainer(\n",
    "    model=classifier,\n",
    "    preprocessing=encoder, # Optional: compile step can use inverse_transform method\n",
    "    features_dict=titanic_dict   # Optional parameter, dict specifies label for features name \n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Compiling without postprocessing parameter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After declaring our explainer, we need to compile it on our model and data in order to have information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Backend: Shap TreeExplainer\n"
     ]
    }
   ],
   "source": [
    "xpl.compile(x=Xtest, y_pred=y_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now use our explainer to understand model predictions, through plots or data. We also can find our original dataset, before preprocessing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Name</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Sex</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Title</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerId</th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>863</th>\n",
       "      <td>48.0</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>25.93</td>\n",
       "      <td>Swift Frederick Joel (Margaret Welles Barron)</td>\n",
       "      <td>0</td>\n",
       "      <td>First class</td>\n",
       "      <td>female</td>\n",
       "      <td>0</td>\n",
       "      <td>Mrs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>29.5</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>7.90</td>\n",
       "      <td>Nenkoff Christo</td>\n",
       "      <td>0</td>\n",
       "      <td>Third class</td>\n",
       "      <td>male</td>\n",
       "      <td>0</td>\n",
       "      <td>Mr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>17.0</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>10.50</td>\n",
       "      <td>Ilett Bertha</td>\n",
       "      <td>0</td>\n",
       "      <td>Second class</td>\n",
       "      <td>female</td>\n",
       "      <td>0</td>\n",
       "      <td>Miss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>681</th>\n",
       "      <td>29.5</td>\n",
       "      <td>Queenstown</td>\n",
       "      <td>8.14</td>\n",
       "      <td>Peters Katie</td>\n",
       "      <td>0</td>\n",
       "      <td>Third class</td>\n",
       "      <td>female</td>\n",
       "      <td>0</td>\n",
       "      <td>Miss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>536</th>\n",
       "      <td>7.0</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>26.25</td>\n",
       "      <td>Hart Eva Miriam</td>\n",
       "      <td>2</td>\n",
       "      <td>Second class</td>\n",
       "      <td>female</td>\n",
       "      <td>0</td>\n",
       "      <td>Miss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>33.0</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>26.00</td>\n",
       "      <td>Quick Frederick Charles (Jane Richards)</td>\n",
       "      <td>2</td>\n",
       "      <td>Second class</td>\n",
       "      <td>female</td>\n",
       "      <td>0</td>\n",
       "      <td>Mrs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>468</th>\n",
       "      <td>56.0</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>26.55</td>\n",
       "      <td>Smart John Montgomery</td>\n",
       "      <td>0</td>\n",
       "      <td>First class</td>\n",
       "      <td>male</td>\n",
       "      <td>0</td>\n",
       "      <td>Mr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>741</th>\n",
       "      <td>29.5</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>30.00</td>\n",
       "      <td>Hawksford Walter James</td>\n",
       "      <td>0</td>\n",
       "      <td>First class</td>\n",
       "      <td>male</td>\n",
       "      <td>0</td>\n",
       "      <td>Mr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>355</th>\n",
       "      <td>29.5</td>\n",
       "      <td>Cherbourg</td>\n",
       "      <td>7.22</td>\n",
       "      <td>Yousif Wazli</td>\n",
       "      <td>0</td>\n",
       "      <td>Third class</td>\n",
       "      <td>male</td>\n",
       "      <td>0</td>\n",
       "      <td>Mr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>450</th>\n",
       "      <td>52.0</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>30.50</td>\n",
       "      <td>Peuchen Arthur Godfrey</td>\n",
       "      <td>0</td>\n",
       "      <td>First class</td>\n",
       "      <td>male</td>\n",
       "      <td>0</td>\n",
       "      <td>Major</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>223 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Age     Embarked   Fare  \\\n",
       "PassengerId                             \n",
       "863          48.0  Southampton  25.93   \n",
       "224          29.5  Southampton   7.90   \n",
       "85           17.0  Southampton  10.50   \n",
       "681          29.5   Queenstown   8.14   \n",
       "536           7.0  Southampton  26.25   \n",
       "...           ...          ...    ...   \n",
       "507          33.0  Southampton  26.00   \n",
       "468          56.0  Southampton  26.55   \n",
       "741          29.5  Southampton  30.00   \n",
       "355          29.5    Cherbourg   7.22   \n",
       "450          52.0  Southampton  30.50   \n",
       "\n",
       "                                                      Name  Parch  \\\n",
       "PassengerId                                                         \n",
       "863          Swift Frederick Joel (Margaret Welles Barron)      0   \n",
       "224                                        Nenkoff Christo      0   \n",
       "85                                            Ilett Bertha      0   \n",
       "681                                           Peters Katie      0   \n",
       "536                                        Hart Eva Miriam      2   \n",
       "...                                                    ...    ...   \n",
       "507                Quick Frederick Charles (Jane Richards)      2   \n",
       "468                                  Smart John Montgomery      0   \n",
       "741                                 Hawksford Walter James      0   \n",
       "355                                           Yousif Wazli      0   \n",
       "450                                 Peuchen Arthur Godfrey      0   \n",
       "\n",
       "                   Pclass     Sex  SibSp  Title  \n",
       "PassengerId                                      \n",
       "863           First class  female      0    Mrs  \n",
       "224           Third class    male      0     Mr  \n",
       "85           Second class  female      0   Miss  \n",
       "681           Third class  female      0   Miss  \n",
       "536          Second class  female      0   Miss  \n",
       "...                   ...     ...    ...    ...  \n",
       "507          Second class  female      0    Mrs  \n",
       "468           First class    male      0     Mr  \n",
       "741           First class    male      0     Mr  \n",
       "355           Third class    male      0     Mr  \n",
       "450           First class    male      0  Major  \n",
       "\n",
       "[223 rows x 9 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xpl.x_init"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All the analysis you can do is in this tutorial : **[Tutorial](https://github.com/MAIF/shapash/blob/master/tutorial/tutorial02-Shapash-overview-in-Jupyter.ipynb)**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Compiling with postprocessing parameter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nevertheless, here we want to add postprocessing to our data to understand them better, and to have a better **explicability**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The syntax for the **postprocessing parameter** is as follow :"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```python\n",
    "postprocess = {\n",
    "    'name_of_the_feature': {'type': 'type_of_modification', 'rule': 'rule_to_apply'},\n",
    "    'second_name_of_features': {'type': 'type_of_modification', 'rule': 'rule_to_apply'},\n",
    "    ...\n",
    "}\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You have five different types of modifications : \n",
    "\n",
    "- 1) **prefix** : <br />\n",
    "If you want to modify the beginning of the data. The syntax is \n",
    "```python\n",
    "{'features_name': {'type': 'prefix',\n",
    "                     'rule': 'Example : '}\n",
    "}\n",
    "```\n",
    "\n",
    "- 2) **suffix** : <br />\n",
    "If you want to add something at the end of some features, the syntax is similar : \n",
    "```python\n",
    "{'features_name': {'type': 'suffix',\n",
    "                     'rule': ' is an example'}\n",
    "}\n",
    "```\n",
    "\n",
    "- 3) **transcoding** : <br />\n",
    "This is a mapping function which modifies categorical variables. The syntax is :\n",
    "```python\n",
    "{'features_name': {'type': 'transcoding',  \n",
    "                     'rule': {'old_name1': 'new_name1',\n",
    "                              'old_name2': 'new_name2',\n",
    "                              ...\n",
    "                             }\n",
    "                    }\n",
    "}\n",
    "```\n",
    "If you don't map all possible values, those values won't be modified.\n",
    "\n",
    "- 4) **regex** : <br />\n",
    "If you want to modify strings, you can do it by regular expressions like this:\n",
    "```python\n",
    "{'features_name': {'type': 'regex', \n",
    "                     'rule': {'in': '^M',\n",
    "                              'out': 'm'\n",
    "                             }\n",
    "                    }\n",
    "}\n",
    "```\n",
    "\n",
    "- 5) **case** : <br />\n",
    "If you want to change the case of a certain features, you can or change everything in lowercase with `'rule': 'lower'`, or change in uppercase with `'rule': 'upper'`. The syntax is :\n",
    "```python\n",
    "{'features_name': {'type': 'case', \n",
    "                     'rule': 'upper'}\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Of course, you don't have to modify all features. Let's give an example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "postprocess = {\n",
    "    'Age': {'type': 'suffix', \n",
    "            'rule': ' years old' # Adding 'years old' at the end\n",
    "           }, \n",
    "    'Sex': {'type': 'transcoding', \n",
    "            'rule': {'male': 'Man',\n",
    "                     'female': 'Woman'}\n",
    "           },\n",
    "    'Pclass': {'type': 'regex', \n",
    "               'rule': {'in': ' class$', \n",
    "                        'out': ''} # Deleting 'class' word at the end\n",
    "              },\n",
    "    'Fare': {'type': 'prefix', \n",
    "             'rule': '$' # Adding $ at the beginning\n",
    "            }, \n",
    "    'Embarked': {'type': 'case', \n",
    "                 'rule': 'upper'\n",
    "                }\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can now add this postprocess dict in parameter :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "xpl_postprocess = SmartExplainer(\n",
    "    model=classifier,\n",
    "    postprocessing=postprocess,\n",
    "    preprocessing=encoder,       # Optional: compile step can use inverse_transform method\n",
    "    features_dict=titanic_dict\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Backend: Shap TreeExplainer\n"
     ]
    }
   ],
   "source": [
    "xpl_postprocess.compile(\n",
    "    x=Xtest,\n",
    "    y_pred=y_pred, # Optional\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can now visualize your dataset, which is modified."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>Age</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Name</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Sex</th>\n",
       "      <th>SibSp</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>863</th>\n",
       "      <td>48.0 years old</td>\n",
       "      <td>SOUTHAMPTON</td>\n",
       "      <td>$25.93</td>\n",
       "      <td>Swift Frederick Joel (Margaret Welles Barron)</td>\n",
       "      <td>0</td>\n",
       "      <td>First</td>\n",
       "      <td>Woman</td>\n",
       "      <td>0</td>\n",
       "      <td>Mrs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>29.5 years old</td>\n",
       "      <td>SOUTHAMPTON</td>\n",
       "      <td>$7.9</td>\n",
       "      <td>Nenkoff Christo</td>\n",
       "      <td>0</td>\n",
       "      <td>Third</td>\n",
       "      <td>Man</td>\n",
       "      <td>0</td>\n",
       "      <td>Mr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>17.0 years old</td>\n",
       "      <td>SOUTHAMPTON</td>\n",
       "      <td>$10.5</td>\n",
       "      <td>Ilett Bertha</td>\n",
       "      <td>0</td>\n",
       "      <td>Second</td>\n",
       "      <td>Woman</td>\n",
       "      <td>0</td>\n",
       "      <td>Miss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>681</th>\n",
       "      <td>29.5 years old</td>\n",
       "      <td>QUEENSTOWN</td>\n",
       "      <td>$8.14</td>\n",
       "      <td>Peters Katie</td>\n",
       "      <td>0</td>\n",
       "      <td>Third</td>\n",
       "      <td>Woman</td>\n",
       "      <td>0</td>\n",
       "      <td>Miss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>536</th>\n",
       "      <td>7.0 years old</td>\n",
       "      <td>SOUTHAMPTON</td>\n",
       "      <td>$26.25</td>\n",
       "      <td>Hart Eva Miriam</td>\n",
       "      <td>2</td>\n",
       "      <td>Second</td>\n",
       "      <td>Woman</td>\n",
       "      <td>0</td>\n",
       "      <td>Miss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>33.0 years old</td>\n",
       "      <td>SOUTHAMPTON</td>\n",
       "      <td>$26.0</td>\n",
       "      <td>Quick Frederick Charles (Jane Richards)</td>\n",
       "      <td>2</td>\n",
       "      <td>Second</td>\n",
       "      <td>Woman</td>\n",
       "      <td>0</td>\n",
       "      <td>Mrs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>468</th>\n",
       "      <td>56.0 years old</td>\n",
       "      <td>SOUTHAMPTON</td>\n",
       "      <td>$26.55</td>\n",
       "      <td>Smart John Montgomery</td>\n",
       "      <td>0</td>\n",
       "      <td>First</td>\n",
       "      <td>Man</td>\n",
       "      <td>0</td>\n",
       "      <td>Mr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>741</th>\n",
       "      <td>29.5 years old</td>\n",
       "      <td>SOUTHAMPTON</td>\n",
       "      <td>$30.0</td>\n",
       "      <td>Hawksford Walter James</td>\n",
       "      <td>0</td>\n",
       "      <td>First</td>\n",
       "      <td>Man</td>\n",
       "      <td>0</td>\n",
       "      <td>Mr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>355</th>\n",
       "      <td>29.5 years old</td>\n",
       "      <td>CHERBOURG</td>\n",
       "      <td>$7.22</td>\n",
       "      <td>Yousif Wazli</td>\n",
       "      <td>0</td>\n",
       "      <td>Third</td>\n",
       "      <td>Man</td>\n",
       "      <td>0</td>\n",
       "      <td>Mr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>450</th>\n",
       "      <td>52.0 years old</td>\n",
       "      <td>SOUTHAMPTON</td>\n",
       "      <td>$30.5</td>\n",
       "      <td>Peuchen Arthur Godfrey</td>\n",
       "      <td>0</td>\n",
       "      <td>First</td>\n",
       "      <td>Man</td>\n",
       "      <td>0</td>\n",
       "      <td>Major</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>223 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Age     Embarked    Fare  \\\n",
       "PassengerId                                        \n",
       "863          48.0 years old  SOUTHAMPTON  $25.93   \n",
       "224          29.5 years old  SOUTHAMPTON    $7.9   \n",
       "85           17.0 years old  SOUTHAMPTON   $10.5   \n",
       "681          29.5 years old   QUEENSTOWN   $8.14   \n",
       "536           7.0 years old  SOUTHAMPTON  $26.25   \n",
       "...                     ...          ...     ...   \n",
       "507          33.0 years old  SOUTHAMPTON   $26.0   \n",
       "468          56.0 years old  SOUTHAMPTON  $26.55   \n",
       "741          29.5 years old  SOUTHAMPTON   $30.0   \n",
       "355          29.5 years old    CHERBOURG   $7.22   \n",
       "450          52.0 years old  SOUTHAMPTON   $30.5   \n",
       "\n",
       "                                                      Name  Parch  Pclass  \\\n",
       "PassengerId                                                                 \n",
       "863          Swift Frederick Joel (Margaret Welles Barron)      0   First   \n",
       "224                                        Nenkoff Christo      0   Third   \n",
       "85                                            Ilett Bertha      0  Second   \n",
       "681                                           Peters Katie      0   Third   \n",
       "536                                        Hart Eva Miriam      2  Second   \n",
       "...                                                    ...    ...     ...   \n",
       "507                Quick Frederick Charles (Jane Richards)      2  Second   \n",
       "468                                  Smart John Montgomery      0   First   \n",
       "741                                 Hawksford Walter James      0   First   \n",
       "355                                           Yousif Wazli      0   Third   \n",
       "450                                 Peuchen Arthur Godfrey      0   First   \n",
       "\n",
       "               Sex  SibSp  Title  \n",
       "PassengerId                       \n",
       "863          Woman      0    Mrs  \n",
       "224            Man      0     Mr  \n",
       "85           Woman      0   Miss  \n",
       "681          Woman      0   Miss  \n",
       "536          Woman      0   Miss  \n",
       "...            ...    ...    ...  \n",
       "507          Woman      0    Mrs  \n",
       "468            Man      0     Mr  \n",
       "741            Man      0     Mr  \n",
       "355            Man      0     Mr  \n",
       "450            Man      0  Major  \n",
       "\n",
       "[223 rows x 9 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xpl_postprocess.x_init"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All the plots are also modified with the postprocessing modifications."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Application with to_pandas method"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The main purpose of postprocessing modifications is a better understanding of the data, especially when the features names are not specified, such as in to_pandas() method, which orders the features depending on their importance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "to_pandas params: {'features_to_hide': None, 'threshold': None, 'positive': None, 'max_contrib': 20}\n"
     ]
    },
    {
     "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>pred</th>\n",
       "      <th>feature_1</th>\n",
       "      <th>value_1</th>\n",
       "      <th>contribution_1</th>\n",
       "      <th>feature_2</th>\n",
       "      <th>value_2</th>\n",
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       "      <th>feature_3</th>\n",
       "      <th>value_3</th>\n",
       "      <th>contribution_3</th>\n",
       "      <th>...</th>\n",
       "      <th>contribution_6</th>\n",
       "      <th>feature_7</th>\n",
       "      <th>value_7</th>\n",
       "      <th>contribution_7</th>\n",
       "      <th>feature_8</th>\n",
       "      <th>value_8</th>\n",
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       "      <th>feature_9</th>\n",
       "      <th>value_9</th>\n",
       "      <th>contribution_9</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>863</th>\n",
       "      <td>1</td>\n",
       "      <td>Title of passenger</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>0.163479</td>\n",
       "      <td>Sex</td>\n",
       "      <td>Woman</td>\n",
       "      <td>0.154309</td>\n",
       "      <td>Ticket class</td>\n",
       "      <td>First</td>\n",
       "      <td>0.130221</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0406219</td>\n",
       "      <td>Name, First name</td>\n",
       "      <td>Swift Frederick Joel (Margaret Welles Barron)</td>\n",
       "      <td>-0.0381955</td>\n",
       "      <td>Port of embarkation</td>\n",
       "      <td>SOUTHAMPTON</td>\n",
       "      <td>-0.0147327</td>\n",
       "      <td>Relatives like children or parents</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.00538103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>0</td>\n",
       "      <td>Title of passenger</td>\n",
       "      <td>Mr</td>\n",
       "      <td>0.094038</td>\n",
       "      <td>Sex</td>\n",
       "      <td>Man</td>\n",
       "      <td>0.0696282</td>\n",
       "      <td>Age</td>\n",
       "      <td>29.5 years old</td>\n",
       "      <td>0.0658556</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0151605</td>\n",
       "      <td>Relatives such as brother or wife</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.00855039</td>\n",
       "      <td>Relatives like children or parents</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00124433</td>\n",
       "      <td>Name, First name</td>\n",
       "      <td>Nenkoff Christo</td>\n",
       "      <td>-0.000577095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>1</td>\n",
       "      <td>Title of passenger</td>\n",
       "      <td>Miss</td>\n",
       "      <td>0.190529</td>\n",
       "      <td>Sex</td>\n",
       "      <td>Woman</td>\n",
       "      <td>0.135507</td>\n",
       "      <td>Ticket class</td>\n",
       "      <td>Second</td>\n",
       "      <td>0.0809714</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.025286</td>\n",
       "      <td>Relatives like children or parents</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.0238222</td>\n",
       "      <td>Relatives such as brother or wife</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0209045</td>\n",
       "      <td>Age</td>\n",
       "      <td>17.0 years old</td>\n",
       "      <td>-0.00702283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>681</th>\n",
       "      <td>1</td>\n",
       "      <td>Title of passenger</td>\n",
       "      <td>Miss</td>\n",
       "      <td>0.237477</td>\n",
       "      <td>Port of embarkation</td>\n",
       "      <td>QUEENSTOWN</td>\n",
       "      <td>0.143451</td>\n",
       "      <td>Sex</td>\n",
       "      <td>Woman</td>\n",
       "      <td>0.127931</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0243567</td>\n",
       "      <td>Relatives like children or parents</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0165205</td>\n",
       "      <td>Passenger fare</td>\n",
       "      <td>$8.14</td>\n",
       "      <td>-0.0109633</td>\n",
       "      <td>Age</td>\n",
       "      <td>29.5 years old</td>\n",
       "      <td>0.00327866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>536</th>\n",
       "      <td>1</td>\n",
       "      <td>Title of passenger</td>\n",
       "      <td>Miss</td>\n",
       "      <td>0.210166</td>\n",
       "      <td>Ticket class</td>\n",
       "      <td>Second</td>\n",
       "      <td>0.168247</td>\n",
       "      <td>Sex</td>\n",
       "      <td>Woman</td>\n",
       "      <td>0.0876445</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0147503</td>\n",
       "      <td>Relatives like children or parents</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0125069</td>\n",
       "      <td>Port of embarkation</td>\n",
       "      <td>SOUTHAMPTON</td>\n",
       "      <td>-0.0119119</td>\n",
       "      <td>Name, First name</td>\n",
       "      <td>Hart Eva Miriam</td>\n",
       "      <td>0.00654165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>1</td>\n",
       "      <td>Title of passenger</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>0.215332</td>\n",
       "      <td>Sex</td>\n",
       "      <td>Woman</td>\n",
       "      <td>0.194419</td>\n",
       "      <td>Ticket class</td>\n",
       "      <td>Second</td>\n",
       "      <td>0.166437</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0079185</td>\n",
       "      <td>Relatives like children or parents</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00407485</td>\n",
       "      <td>Age</td>\n",
       "      <td>33.0 years old</td>\n",
       "      <td>-0.00263589</td>\n",
       "      <td>Name, First name</td>\n",
       "      <td>Quick Frederick Charles (Jane Richards)</td>\n",
       "      <td>0.00162901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>468</th>\n",
       "      <td>0</td>\n",
       "      <td>Sex</td>\n",
       "      <td>Man</td>\n",
       "      <td>0.100602</td>\n",
       "      <td>Passenger fare</td>\n",
       "      <td>$26.55</td>\n",
       "      <td>-0.099794</td>\n",
       "      <td>Title of passenger</td>\n",
       "      <td>Mr</td>\n",
       "      <td>0.0967768</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0243706</td>\n",
       "      <td>Port of embarkation</td>\n",
       "      <td>SOUTHAMPTON</td>\n",
       "      <td>0.0124424</td>\n",
       "      <td>Relatives such as brother or wife</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.0108301</td>\n",
       "      <td>Relatives like children or parents</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.00332632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>741</th>\n",
       "      <td>0</td>\n",
       "      <td>Title of passenger</td>\n",
       "      <td>Mr</td>\n",
       "      <td>0.131861</td>\n",
       "      <td>Sex</td>\n",
       "      <td>Man</td>\n",
       "      <td>0.110845</td>\n",
       "      <td>Age</td>\n",
       "      <td>29.5 years old</td>\n",
       "      <td>0.104878</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0339308</td>\n",
       "      <td>Relatives such as brother or wife</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.00715564</td>\n",
       "      <td>Name, First name</td>\n",
       "      <td>Hawksford Walter James</td>\n",
       "      <td>0.00165882</td>\n",
       "      <td>Relatives like children or parents</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.00137946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>355</th>\n",
       "      <td>0</td>\n",
       "      <td>Title of passenger</td>\n",
       "      <td>Mr</td>\n",
       "      <td>0.12679</td>\n",
       "      <td>Sex</td>\n",
       "      <td>Man</td>\n",
       "      <td>0.0933251</td>\n",
       "      <td>Age</td>\n",
       "      <td>29.5 years old</td>\n",
       "      <td>0.0717939</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0271103</td>\n",
       "      <td>Name, First name</td>\n",
       "      <td>Yousif Wazli</td>\n",
       "      <td>0.0163174</td>\n",
       "      <td>Relatives such as brother or wife</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.0108501</td>\n",
       "      <td>Relatives like children or parents</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.000543508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>450</th>\n",
       "      <td>0</td>\n",
       "      <td>Sex</td>\n",
       "      <td>Man</td>\n",
       "      <td>0.13572</td>\n",
       "      <td>Title of passenger</td>\n",
       "      <td>Major</td>\n",
       "      <td>-0.0723023</td>\n",
       "      <td>Age</td>\n",
       "      <td>52.0 years old</td>\n",
       "      <td>0.0690373</td>\n",
       "      <td>...</td>\n",
       "      <td>0.027384</td>\n",
       "      <td>Relatives such as brother or wife</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.0134144</td>\n",
       "      <td>Relatives like children or parents</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00256623</td>\n",
       "      <td>Name, First name</td>\n",
       "      <td>Peuchen Arthur Godfrey</td>\n",
       "      <td>0.00229483</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>223 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     pred           feature_1 value_1 contribution_1            feature_2  \\\n",
       "863     1  Title of passenger     Mrs       0.163479                  Sex   \n",
       "224     0  Title of passenger      Mr       0.094038                  Sex   \n",
       "85      1  Title of passenger    Miss       0.190529                  Sex   \n",
       "681     1  Title of passenger    Miss       0.237477  Port of embarkation   \n",
       "536     1  Title of passenger    Miss       0.210166         Ticket class   \n",
       "..    ...                 ...     ...            ...                  ...   \n",
       "507     1  Title of passenger     Mrs       0.215332                  Sex   \n",
       "468     0                 Sex     Man       0.100602       Passenger fare   \n",
       "741     0  Title of passenger      Mr       0.131861                  Sex   \n",
       "355     0  Title of passenger      Mr        0.12679                  Sex   \n",
       "450     0                 Sex     Man        0.13572   Title of passenger   \n",
       "\n",
       "        value_2 contribution_2           feature_3         value_3  \\\n",
       "863       Woman       0.154309        Ticket class           First   \n",
       "224         Man      0.0696282                 Age  29.5 years old   \n",
       "85        Woman       0.135507        Ticket class          Second   \n",
       "681  QUEENSTOWN       0.143451                 Sex           Woman   \n",
       "536      Second       0.168247                 Sex           Woman   \n",
       "..          ...            ...                 ...             ...   \n",
       "507       Woman       0.194419        Ticket class          Second   \n",
       "468      $26.55      -0.099794  Title of passenger              Mr   \n",
       "741         Man       0.110845                 Age  29.5 years old   \n",
       "355         Man      0.0933251                 Age  29.5 years old   \n",
       "450       Major     -0.0723023                 Age  52.0 years old   \n",
       "\n",
       "    contribution_3  ... contribution_6                           feature_7  \\\n",
       "863       0.130221  ...      0.0406219                    Name, First name   \n",
       "224      0.0658556  ...      0.0151605   Relatives such as brother or wife   \n",
       "85       0.0809714  ...      -0.025286  Relatives like children or parents   \n",
       "681       0.127931  ...      0.0243567  Relatives like children or parents   \n",
       "536      0.0876445  ...      0.0147503  Relatives like children or parents   \n",
       "..             ...  ...            ...                                 ...   \n",
       "507       0.166437  ...     -0.0079185  Relatives like children or parents   \n",
       "468      0.0967768  ...      0.0243706                 Port of embarkation   \n",
       "741       0.104878  ...      0.0339308   Relatives such as brother or wife   \n",
       "355      0.0717939  ...     -0.0271103                    Name, First name   \n",
       "450      0.0690373  ...       0.027384   Relatives such as brother or wife   \n",
       "\n",
       "                                           value_7 contribution_7  \\\n",
       "863  Swift Frederick Joel (Margaret Welles Barron)     -0.0381955   \n",
       "224                                              0    -0.00855039   \n",
       "85                                               0     -0.0238222   \n",
       "681                                              0      0.0165205   \n",
       "536                                              2      0.0125069   \n",
       "..                                             ...            ...   \n",
       "507                                              2     0.00407485   \n",
       "468                                    SOUTHAMPTON      0.0124424   \n",
       "741                                              0    -0.00715564   \n",
       "355                                   Yousif Wazli      0.0163174   \n",
       "450                                              0     -0.0134144   \n",
       "\n",
       "                              feature_8                 value_8  \\\n",
       "863                 Port of embarkation             SOUTHAMPTON   \n",
       "224  Relatives like children or parents                       0   \n",
       "85    Relatives such as brother or wife                       0   \n",
       "681                      Passenger fare                   $8.14   \n",
       "536                 Port of embarkation             SOUTHAMPTON   \n",
       "..                                  ...                     ...   \n",
       "507                                 Age          33.0 years old   \n",
       "468   Relatives such as brother or wife                       0   \n",
       "741                    Name, First name  Hawksford Walter James   \n",
       "355   Relatives such as brother or wife                       0   \n",
       "450  Relatives like children or parents                       0   \n",
       "\n",
       "    contribution_8                           feature_9  \\\n",
       "863     -0.0147327  Relatives like children or parents   \n",
       "224     0.00124433                    Name, First name   \n",
       "85       0.0209045                                 Age   \n",
       "681     -0.0109633                                 Age   \n",
       "536     -0.0119119                    Name, First name   \n",
       "..             ...                                 ...   \n",
       "507    -0.00263589                    Name, First name   \n",
       "468     -0.0108301  Relatives like children or parents   \n",
       "741     0.00165882  Relatives like children or parents   \n",
       "355     -0.0108501  Relatives like children or parents   \n",
       "450     0.00256623                    Name, First name   \n",
       "\n",
       "                                     value_9 contribution_9  \n",
       "863                                        0    -0.00538103  \n",
       "224                          Nenkoff Christo   -0.000577095  \n",
       "85                            17.0 years old    -0.00702283  \n",
       "681                           29.5 years old     0.00327866  \n",
       "536                          Hart Eva Miriam     0.00654165  \n",
       "..                                       ...            ...  \n",
       "507  Quick Frederick Charles (Jane Richards)     0.00162901  \n",
       "468                                        0    -0.00332632  \n",
       "741                                        0    -0.00137946  \n",
       "355                                        0   -0.000543508  \n",
       "450                   Peuchen Arthur Godfrey     0.00229483  \n",
       "\n",
       "[223 rows x 28 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xpl_postprocess.to_pandas()"
   ]
  }
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