AED postes vacants.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "9378a572",
   "metadata": {},
   "source": [
    "# Informations sur la base de données.\n",
    "\n",
    "#### Buts de l'analyse\n",
    "\n",
    "#### Étapes de traitement des données"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9041bf2f",
   "metadata": {},
   "source": [
    "#### Importation des librairies utilisées."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "95e142e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "import sklearn\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set(color_codes=True)\n",
    "\n",
    "import scipy.stats as stats\n",
    "\n",
    "%matplotlib inline\n",
    "os.environ['KMP_DUPLICATE_LIB_OK']='True'\n",
    "# Pour la reproductibilité des résultats\n",
    "np.random.seed(43)\n",
    "\n",
    "import warnings\n",
    "warnings.simplefilter(action='ignore', category=FutureWarning)\n",
    "warnings.filterwarnings('ignore', '.*do not.*', )\n",
    "warnings.warn('Do not show this message')\n",
    "\n",
    "# some nice colors from http://colorbrewer2.org/\n",
    "COLOR1 = '#7fc97f'\n",
    "COLOR2 = '#beaed4'\n",
    "COLOR3 = '#fdc086'\n",
    "COLOR4 = '#ffff99'\n",
    "COLOR5 = '#386cb0'\n",
    "\n",
    "sns.set(rc={'figure.figsize':(9, 4)})\n",
    "sns.set_theme(context=\"notebook\", style=\"white\", palette=\"Set2\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca7a8161",
   "metadata": {},
   "source": [
    "## Recommandations \n",
    "\n",
    "### Analyse des forme\n",
    "\n",
    "\n",
    "* **Ligne et colonne: (1608208, 5)**\n",
    "\n",
    "niveau de detail, une ligne par :\n",
    "                  Géographie, \n",
    "                  Classification nationale des professions(CNP4),\n",
    "                  Sexe,\n",
    "                  Durée de l'emploi,\t\n",
    "                  Période de référence, mensuelle\n",
    "\n",
    "* **Type de variables: 2 variables de type numérique et 5 variables qualitative.**\n",
    "\n",
    "    * Géographie : Canada, Province ou territoire, région économique\n",
    "    * Classification nationale des professions(CNP4)\n",
    "    * Moyenne du salaire horaire offert\t\n",
    "    * Postes vacants\n",
    "    * Période de référence : par trimestre\n",
    "\n",
    "Au moins 75% de la valeur pour la variable \"moyenne du salaire horaire offert\" est égale a zero.\t\n",
    "\n",
    "    \n",
    "* **Valeurs extremes **\n",
    "\n",
    "On va supposer, pour l'exemple, que la base de données contient 0,5% de valeurs aberrantes de toutes sortes. Ce n'est pas exagéré. Cela représente $0,005*27410 \\approx 137$ valeurs.\n",
    "\n",
    "On utilise la méthode de la [forêt d'isolation](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.IsolationForest.html) pour détecter et éliminer un maximum de 0,5% des valeurs possiblement aberrantes.  \n",
    "    \n",
    "### Analyse de structure\n",
    "\n",
    "\n",
    "### Nettoyage des donnees: Recommandations\n",
    "\n",
    "* Filtrer \"moyenne du salaire horaire offert\" est égale a zero.\n",
    "* Filtrer les donnée selon CNP:\n",
    "\n",
    "    *  10 grandes catégories professionnelles\n",
    "\n",
    "    Chaque grande catégorie professionnelle comporte un code unique à un chiffre et est constituée \n",
    "    d'un ou de plusieurs grands groupes.\n",
    "\n",
    "    *  40 grands groupes\n",
    "\n",
    "    Chaque grand groupe comporte un code unique à deux chiffresNote de bas de page1 et est constitué \n",
    "    d'un ou de plusieurs groupes intermédiaires. \n",
    "    Le premier chiffre de ce code indique la grande catégorie professionnelle à laquelle le grand groupe appartient.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ebb6f94",
   "metadata": {},
   "source": [
    "# Partie I: Prétraitement des données.\n",
    "\n",
    "## Lecture des bases de données en format CSV.\n",
    "\n",
    "Les données sont écrites dans un DataFrame de la librairie Pandas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "db4e15f3",
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_db():\n",
    "    postes_vacants_CNP=pd.read_csv(\"postes_vacants_CNP\",sep=\",\")\n",
    "    return postes_vacants_CNP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a9395687",
   "metadata": {},
   "outputs": [],
   "source": [
    "postes_vacants_CNP=load_db()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "788d0a01",
   "metadata": {},
   "source": [
    "## Explorer les données"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0c778a54",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Année/Trim</th>\n",
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       "      <th>CNP</th>\n",
       "      <th>Moyenne du salaire horaire offert</th>\n",
       "      <th>Postes vacants</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-01</td>\n",
       "      <td>Abitibi-Témiscamingue, Québec</td>\n",
       "      <td>Acheteurs/acheteuses des commerces de détail e...</td>\n",
       "      <td>0.0</td>\n",
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       "      <th>1</th>\n",
       "      <td>2015-01</td>\n",
       "      <td>Abitibi-Témiscamingue, Québec</td>\n",
       "      <td>Acteurs/actrices et comédiens/comédiennes [5135]</td>\n",
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       "      <th>2</th>\n",
       "      <td>2015-01</td>\n",
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       "      <th>3</th>\n",
       "      <td>2015-01</td>\n",
       "      <td>Abitibi-Témiscamingue, Québec</td>\n",
       "      <td>Adjoints administratifs médicaux/adjointes adm...</td>\n",
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       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-01</td>\n",
       "      <td>Abitibi-Témiscamingue, Québec</td>\n",
       "      <td>Adjoints administratifs/adjointes administrati...</td>\n",
       "      <td>0.0</td>\n",
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      ],
      "text/plain": [
       "  Année/Trim                        Régions  \\\n",
       "0    2015-01  Abitibi-Témiscamingue, Québec   \n",
       "1    2015-01  Abitibi-Témiscamingue, Québec   \n",
       "2    2015-01  Abitibi-Témiscamingue, Québec   \n",
       "3    2015-01  Abitibi-Témiscamingue, Québec   \n",
       "4    2015-01  Abitibi-Témiscamingue, Québec   \n",
       "\n",
       "                                                 CNP  \\\n",
       "0  Acheteurs/acheteuses des commerces de détail e...   \n",
       "1   Acteurs/actrices et comédiens/comédiennes [5135]   \n",
       "2  Adjoints administratifs juridiques/adjointes a...   \n",
       "3  Adjoints administratifs médicaux/adjointes adm...   \n",
       "4  Adjoints administratifs/adjointes administrati...   \n",
       "\n",
       "   Moyenne du salaire horaire offert  Postes vacants  \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  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postes_vacants_CNP.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e21b4e5d",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Année/Trim</th>\n",
       "      <th>Régions</th>\n",
       "      <th>CNP</th>\n",
       "      <th>Moyenne du salaire horaire offert</th>\n",
       "      <th>Postes vacants</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1608203</th>\n",
       "      <td>2022-04</td>\n",
       "      <td>Île-du-Prince-Édouard</td>\n",
       "      <td>Électriciens/électriciennes de réseaux électri...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>1608204</th>\n",
       "      <td>2022-04</td>\n",
       "      <td>Île-du-Prince-Édouard</td>\n",
       "      <td>Électriciens/électriciennes et monteurs/monteu...</td>\n",
       "      <td>41.3</td>\n",
       "      <td>40.0</td>\n",
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       "      <th>1608205</th>\n",
       "      <td>2022-04</td>\n",
       "      <td>Île-du-Prince-Édouard</td>\n",
       "      <td>Électromécaniciens/électromécaniciennes [7333]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1608206</th>\n",
       "      <td>2022-04</td>\n",
       "      <td>Île-du-Prince-Édouard</td>\n",
       "      <td>Électroniciens/électroniciennes d'entretien (b...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>1608207</th>\n",
       "      <td>2022-04</td>\n",
       "      <td>Île-du-Prince-Édouard</td>\n",
       "      <td>Évaluateurs/évaluatrices de systèmes informati...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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      ],
      "text/plain": [
       "        Année/Trim                Régions  \\\n",
       "1608203    2022-04  Île-du-Prince-Édouard   \n",
       "1608204    2022-04  Île-du-Prince-Édouard   \n",
       "1608205    2022-04  Île-du-Prince-Édouard   \n",
       "1608206    2022-04  Île-du-Prince-Édouard   \n",
       "1608207    2022-04  Île-du-Prince-Édouard   \n",
       "\n",
       "                                                       CNP  \\\n",
       "1608203  Électriciens/électriciennes de réseaux électri...   \n",
       "1608204  Électriciens/électriciennes et monteurs/monteu...   \n",
       "1608205     Électromécaniciens/électromécaniciennes [7333]   \n",
       "1608206  Électroniciens/électroniciennes d'entretien (b...   \n",
       "1608207  Évaluateurs/évaluatrices de systèmes informati...   \n",
       "\n",
       "         Moyenne du salaire horaire offert  Postes vacants  \n",
       "1608203                                0.0             0.0  \n",
       "1608204                               41.3            40.0  \n",
       "1608205                                0.0             0.0  \n",
       "1608206                                0.0             0.0  \n",
       "1608207                                0.0             0.0  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postes_vacants_CNP.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0941eb5",
   "metadata": {},
   "source": [
    "### Dimensions du dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e5487147",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Les dimensions du jeux des donnees:  (1608208, 5)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(\"Les dimensions du jeux des donnees: \", postes_vacants_CNP.shape)\n",
    "print() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "66af9abb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nombre d’éléments: 8041040\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Size of our data set\n",
    "## le nombre de lignes multiplié par le nombre de colonnes si DataFrame.\n",
    "print(\"Nombre d’éléments:\", postes_vacants_CNP.size)\n",
    "print()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d841b22",
   "metadata": {},
   "source": [
    "Le nombre d'individus est égale à 1608208 et le nombre de descripteurs est égale à 5"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67f90838",
   "metadata": {},
   "source": [
    "### Type des donnees"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6974a10d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Année/Trim                            object\n",
       "Régions                               object\n",
       "CNP                                   object\n",
       "Moyenne du salaire horaire offert    float64\n",
       "Postes vacants                       float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postes_vacants_CNP.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ec9d8287",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "object     3\n",
       "float64    2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postes_vacants_CNP.dtypes.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c62b6977",
   "metadata": {},
   "source": [
    " Le jeu des données a 2 variables de type numérique et 3 variables qualitative."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a4ab7d2b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Moyenne du salaire horaire offert</th>\n",
       "      <th>Postes vacants</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1.608208e+06</td>\n",
       "      <td>1.608208e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>4.307979e+00</td>\n",
       "      <td>1.279677e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.033259e+01</td>\n",
       "      <td>3.085177e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.776000e+02</td>\n",
       "      <td>1.031955e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "       Moyenne du salaire horaire offert  Postes vacants\n",
       "count                       1.608208e+06    1.608208e+06\n",
       "mean                        4.307979e+00    1.279677e+02\n",
       "std                         1.033259e+01    3.085177e+03\n",
       "min                         0.000000e+00    0.000000e+00\n",
       "25%                         0.000000e+00    0.000000e+00\n",
       "50%                         0.000000e+00    0.000000e+00\n",
       "75%                         0.000000e+00    0.000000e+00\n",
       "max                         1.776000e+02    1.031955e+06"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postes_vacants_CNP.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed80d0d4",
   "metadata": {},
   "source": [
    "Au moins 75% des postes ont la valeur 0 pour la moyenne du salaire offert"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9380200c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1608208 entries, 0 to 1608207\n",
      "Data columns (total 5 columns):\n",
      " #   Column                             Non-Null Count    Dtype  \n",
      "---  ------                             --------------    -----  \n",
      " 0   Année/Trim                         1608208 non-null  object \n",
      " 1   Régions                            1608208 non-null  object \n",
      " 2   CNP                                1608208 non-null  object \n",
      " 3   Moyenne du salaire horaire offert  1608208 non-null  float64\n",
      " 4   Postes vacants                     1608208 non-null  float64\n",
      "dtypes: float64(2), object(3)\n",
      "memory usage: 61.3+ MB\n"
     ]
    }
   ],
   "source": [
    "postes_vacants_CNP.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0c84396",
   "metadata": {},
   "source": [
    "### Affichage du nombre de valeurs manquantes Nans dans le DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "becf99d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Année/Trim                           0\n",
       "Régions                              0\n",
       "CNP                                  0\n",
       "Moyenne du salaire horaire offert    0\n",
       "Postes vacants                       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postes_vacants_CNP.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "02abc5c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1323479, 5)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postes_vacants_CNP[postes_vacants_CNP[\"Moyenne du salaire horaire offert\"]==0.0].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ffb0b14f",
   "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>Année/Trim</th>\n",
       "      <th>Régions</th>\n",
       "      <th>CNP</th>\n",
       "      <th>Moyenne du salaire horaire offert</th>\n",
       "      <th>Postes vacants</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2015-01</td>\n",
       "      <td>Abitibi-Témiscamingue, Québec</td>\n",
       "      <td>Affaires, finance et administration [1]</td>\n",
       "      <td>16.80</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>244</th>\n",
       "      <td>2015-01</td>\n",
       "      <td>Abitibi-Témiscamingue, Québec</td>\n",
       "      <td>Enseignement, droit et services sociaux, commu...</td>\n",
       "      <td>20.70</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>267</th>\n",
       "      <td>2015-01</td>\n",
       "      <td>Abitibi-Témiscamingue, Québec</td>\n",
       "      <td>Fabrication et services d'utilité publique [9]</td>\n",
       "      <td>21.40</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>384</th>\n",
       "      <td>2015-01</td>\n",
       "      <td>Abitibi-Témiscamingue, Québec</td>\n",
       "      <td>Métiers, transport, machinerie et domaines app...</td>\n",
       "      <td>16.15</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>457</th>\n",
       "      <td>2015-01</td>\n",
       "      <td>Abitibi-Témiscamingue, Québec</td>\n",
       "      <td>Personnel de coordination de la distribution, ...</td>\n",
       "      <td>15.90</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1608186</th>\n",
       "      <td>2022-04</td>\n",
       "      <td>Île-du-Prince-Édouard</td>\n",
       "      <td>Travailleurs/travailleuses des services sociau...</td>\n",
       "      <td>32.70</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1608190</th>\n",
       "      <td>2022-04</td>\n",
       "      <td>Île-du-Prince-Édouard</td>\n",
       "      <td>Vendeurs/vendeuses - commerce de détail [6421]</td>\n",
       "      <td>32.40</td>\n",
       "      <td>740.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1608191</th>\n",
       "      <td>2022-04</td>\n",
       "      <td>Île-du-Prince-Édouard</td>\n",
       "      <td>Vendeurs/vendeuses - commerce de détail [642]</td>\n",
       "      <td>32.40</td>\n",
       "      <td>740.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1608192</th>\n",
       "      <td>2022-04</td>\n",
       "      <td>Île-du-Prince-Édouard</td>\n",
       "      <td>Vente et services [6]</td>\n",
       "      <td>30.90</td>\n",
       "      <td>3060.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1608204</th>\n",
       "      <td>2022-04</td>\n",
       "      <td>Île-du-Prince-Édouard</td>\n",
       "      <td>Électriciens/électriciennes et monteurs/monteu...</td>\n",
       "      <td>41.30</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>284729 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Année/Trim                        Régions  \\\n",
       "9          2015-01  Abitibi-Témiscamingue, Québec   \n",
       "244        2015-01  Abitibi-Témiscamingue, Québec   \n",
       "267        2015-01  Abitibi-Témiscamingue, Québec   \n",
       "384        2015-01  Abitibi-Témiscamingue, Québec   \n",
       "457        2015-01  Abitibi-Témiscamingue, Québec   \n",
       "...            ...                            ...   \n",
       "1608186    2022-04          Île-du-Prince-Édouard   \n",
       "1608190    2022-04          Île-du-Prince-Édouard   \n",
       "1608191    2022-04          Île-du-Prince-Édouard   \n",
       "1608192    2022-04          Île-du-Prince-Édouard   \n",
       "1608204    2022-04          Île-du-Prince-Édouard   \n",
       "\n",
       "                                                       CNP  \\\n",
       "9                  Affaires, finance et administration [1]   \n",
       "244      Enseignement, droit et services sociaux, commu...   \n",
       "267         Fabrication et services d'utilité publique [9]   \n",
       "384      Métiers, transport, machinerie et domaines app...   \n",
       "457      Personnel de coordination de la distribution, ...   \n",
       "...                                                    ...   \n",
       "1608186  Travailleurs/travailleuses des services sociau...   \n",
       "1608190     Vendeurs/vendeuses - commerce de détail [6421]   \n",
       "1608191      Vendeurs/vendeuses - commerce de détail [642]   \n",
       "1608192                              Vente et services [6]   \n",
       "1608204  Électriciens/électriciennes et monteurs/monteu...   \n",
       "\n",
       "         Moyenne du salaire horaire offert  Postes vacants  \n",
       "9                                    16.80             0.0  \n",
       "244                                  20.70             0.0  \n",
       "267                                  21.40             0.0  \n",
       "384                                  16.15             0.0  \n",
       "457                                  15.90             0.0  \n",
       "...                                    ...             ...  \n",
       "1608186                              32.70             0.0  \n",
       "1608190                              32.40           740.0  \n",
       "1608191                              32.40           740.0  \n",
       "1608192                              30.90          3060.0  \n",
       "1608204                              41.30            40.0  \n",
       "\n",
       "[284729 rows x 5 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postes_vacants_CNP[postes_vacants_CNP[\"Moyenne du salaire horaire offert\"]!=0.0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8abba53e",
   "metadata": {},
   "source": [
    "### Filtrer les postes vacants dont Moyenne du salaire horaire offert est different de 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "593b68b4",
   "metadata": {},
   "outputs": [],
   "source": [
    "postes_vacants_CNP_0=postes_vacants_CNP[postes_vacants_CNP[\"Moyenne du salaire horaire offert\"]!=0.0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "4a7ce716",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(284729, 5)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postes_vacants_CNP_0.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "07d0200c",
   "metadata": {},
   "source": [
    "Le jeux de données contient 284.729 occurences"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5052ce64",
   "metadata": {},
   "source": [
    "### Analyse caractéristiques catégorielles"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20b730fe",
   "metadata": {},
   "source": [
    "#### Séparer les données en colonnes numériques et catégorielle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "a896538d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variable catégorielle: ['Année/Trim', 'Régions', 'CNP']\n",
      "Variable numériques: ['Moyenne du salaire horaire offert', 'Postes vacants']\n"
     ]
    }
   ],
   "source": [
    "cat_col=[]\n",
    "num_col=[]\n",
    "\n",
    "for col in postes_vacants_CNP_0.columns:\n",
    "    if postes_vacants_CNP_0[col].dtypes==\"object\":\n",
    "        cat_col.append(col)\n",
    "    else:\n",
    "        num_col.append(col)\n",
    "print (\"Variable catégorielle:\",cat_col)\n",
    "print(\"Variable numériques:\",num_col)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c924f5e",
   "metadata": {},
   "source": [
    "#### Nombre valeurs uniques"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "386e6519",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Année/Trim (28) :\n",
      "2022-04    14249\n",
      "2021-10    13469\n",
      "2022-01    13407\n",
      "2021-07    13167\n",
      "2021-04    12266\n",
      "2021-01    11231\n",
      "2019-04    11079\n",
      "2018-04    10699\n",
      "2019-07    10673\n",
      "2018-07    10643\n",
      "2020-01    10537\n",
      "2018-10    10350\n",
      "2019-01    10105\n",
      "2020-10    10093\n",
      "2019-10    10009\n",
      "2017-04     9842\n",
      "2017-07     9790\n",
      "2017-10     9581\n",
      "2018-01     9573\n",
      "2015-04     9456\n",
      "2016-04     9430\n",
      "2016-07     9292\n",
      "2015-07     9174\n",
      "2016-10     9045\n",
      "2015-10     8703\n",
      "2017-01     8541\n",
      "2016-01     8503\n",
      "2015-01     1822\n",
      "Name: Année/Trim, dtype: int64\n",
      "\n",
      "\n",
      "Régions (93) :\n",
      "Canada                                                       16182\n",
      "Ontario                                                      13320\n",
      "Québec                                                       12330\n",
      "Colombie-Britannique                                         10631\n",
      "Toronto, Ontario                                             10008\n",
      "                                                             ...  \n",
      "Nechako, Colombie-Britannique                                  114\n",
      "Parklands, Manitoba                                             97\n",
      "Notre Dame-Central Bonavista Bay, Terre-Neuve-et-Labrador       93\n",
      "Nord, Saskatchewan                                              53\n",
      "Côte-sud-Burin Peninsula, Terre-Neuve-et-Labrador               29\n",
      "Name: Régions, Length: 93, dtype: int64\n",
      "\n",
      "\n",
      "CNP (679) :\n",
      "Total, toutes les professions                                                                                                         2316\n",
      "Vente et services [6]                                                                                                                 2305\n",
      "Métiers, transport, machinerie et domaines apparentés [7]                                                                             2263\n",
      "Affaires, finance et administration [1]                                                                                               2254\n",
      "Personnel de soutien en service et autre personnel de service, non classé ailleurs (n.c.a.) [67]                                      2219\n",
      "                                                                                                                                      ... \n",
      "Autre personnel de services personnalisés [6564]                                                                                         1\n",
      "Contrôleurs/contrôleuses de la circulation ferroviaire et régulateurs/régulatrices de la circulation maritime [2275]                     1\n",
      "Opérateurs/opératrices au contrôle de la réduction en pâte des pâtes et papiers, de la fabrication du papier et du couchage [9235]       1\n",
      "Matelots de pont sur les bateaux de pêche [8441]                                                                                         1\n",
      "Chiropraticiens/chiropraticiennes [3122]                                                                                                 1\n",
      "Name: CNP, Length: 679, dtype: int64\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for col in cat_col:\n",
    "    print(col,'({})'.format(postes_vacants_CNP_0[col].nunique()),\":\")\n",
    "    print(postes_vacants_CNP_0[col].value_counts())\n",
    "    print()\n",
    "    print()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca52ab19",
   "metadata": {},
   "source": [
    "* La variable Regions contient 93 modalites\n",
    "* La variable CNP contient 679 modalites\n",
    "* La variable Année/Trim contient 28 modalites"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c8afaa9",
   "metadata": {},
   "source": [
    "#### Filtrer les Régions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "e91f1362",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Régions                                          \n",
       "Abitibi-Témiscamingue, Québec                        2596\n",
       "Alberta                                              9759\n",
       "Annapolis Valley, Nouvelle-Écosse                    1153\n",
       "Athabasca-Grande Prairie-Peace River, Alberta         489\n",
       "Avalon Peninsula, Terre-Neuve-et-Labrador            1651\n",
       "                                                     ... \n",
       "Wood Buffalo-Cold Lake, Alberta                      2076\n",
       "Yorkton-Melville, Saskatchewan                       1082\n",
       "Yukon                                                 897\n",
       "Île de Vancouver et la côte, Colombie-Britannique    4443\n",
       "Île-du-Prince-Édouard                                1243\n",
       "Length: 93, dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postes_vacants_CNP_0[['Régions']].value_counts().sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "da360d55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Régions\n",
       "Alberta    9759\n",
       "dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postes_vacants_CNP_0[['Régions']][postes_vacants_CNP_0[\"Régions\"]=='Alberta'].value_counts().sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "661fdb9a",
   "metadata": {},
   "outputs": [],
   "source": [
    "postes_vacants_CNP_regions=postes_vacants_CNP_0[postes_vacants_CNP_0.Régions.isin(['Alberta', 'Colombie-Britannique', 'Manitoba',\n",
    "       'Nouveau-Brunswick', 'Nouvelle-Écosse', 'Ontario', 'Québec',\n",
    "       'Saskatchewan', 'Terre-Neuve-et-Labrador', 'Île-du-Prince-Édouard'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "567a47d0",
   "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>Année/Trim</th>\n",
       "      <th>Régions</th>\n",
       "      <th>CNP</th>\n",
       "      <th>Moyenne du salaire horaire offert</th>\n",
       "      <th>Postes vacants</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>701</th>\n",
       "      <td>2015-01</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Affaires, finance et administration [1]</td>\n",
       "      <td>24.00</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>801</th>\n",
       "      <td>2015-01</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Cadres intermédiaires dans le commerce de déta...</td>\n",
       "      <td>20.65</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>802</th>\n",
       "      <td>2015-01</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Cadres intermédiaires des métiers, des transpo...</td>\n",
       "      <td>41.10</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>924</th>\n",
       "      <td>2015-01</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Dispensateurs/dispensatrices de soins et perso...</td>\n",
       "      <td>16.25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>936</th>\n",
       "      <td>2015-01</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Enseignement, droit et services sociaux, commu...</td>\n",
       "      <td>22.85</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1608186</th>\n",
       "      <td>2022-04</td>\n",
       "      <td>Île-du-Prince-Édouard</td>\n",
       "      <td>Travailleurs/travailleuses des services sociau...</td>\n",
       "      <td>32.70</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1608190</th>\n",
       "      <td>2022-04</td>\n",
       "      <td>Île-du-Prince-Édouard</td>\n",
       "      <td>Vendeurs/vendeuses - commerce de détail [6421]</td>\n",
       "      <td>32.40</td>\n",
       "      <td>740.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1608191</th>\n",
       "      <td>2022-04</td>\n",
       "      <td>Île-du-Prince-Édouard</td>\n",
       "      <td>Vendeurs/vendeuses - commerce de détail [642]</td>\n",
       "      <td>32.40</td>\n",
       "      <td>740.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1608192</th>\n",
       "      <td>2022-04</td>\n",
       "      <td>Île-du-Prince-Édouard</td>\n",
       "      <td>Vente et services [6]</td>\n",
       "      <td>30.90</td>\n",
       "      <td>3060.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1608204</th>\n",
       "      <td>2022-04</td>\n",
       "      <td>Île-du-Prince-Édouard</td>\n",
       "      <td>Électriciens/électriciennes et monteurs/monteu...</td>\n",
       "      <td>41.30</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>71432 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Année/Trim                Régions  \\\n",
       "701        2015-01                Alberta   \n",
       "801        2015-01                Alberta   \n",
       "802        2015-01                Alberta   \n",
       "924        2015-01                Alberta   \n",
       "936        2015-01                Alberta   \n",
       "...            ...                    ...   \n",
       "1608186    2022-04  Île-du-Prince-Édouard   \n",
       "1608190    2022-04  Île-du-Prince-Édouard   \n",
       "1608191    2022-04  Île-du-Prince-Édouard   \n",
       "1608192    2022-04  Île-du-Prince-Édouard   \n",
       "1608204    2022-04  Île-du-Prince-Édouard   \n",
       "\n",
       "                                                       CNP  \\\n",
       "701                Affaires, finance et administration [1]   \n",
       "801      Cadres intermédiaires dans le commerce de déta...   \n",
       "802      Cadres intermédiaires des métiers, des transpo...   \n",
       "924      Dispensateurs/dispensatrices de soins et perso...   \n",
       "936      Enseignement, droit et services sociaux, commu...   \n",
       "...                                                    ...   \n",
       "1608186  Travailleurs/travailleuses des services sociau...   \n",
       "1608190     Vendeurs/vendeuses - commerce de détail [6421]   \n",
       "1608191      Vendeurs/vendeuses - commerce de détail [642]   \n",
       "1608192                              Vente et services [6]   \n",
       "1608204  Électriciens/électriciennes et monteurs/monteu...   \n",
       "\n",
       "         Moyenne du salaire horaire offert  Postes vacants  \n",
       "701                                  24.00             0.0  \n",
       "801                                  20.65             0.0  \n",
       "802                                  41.10             0.0  \n",
       "924                                  16.25             0.0  \n",
       "936                                  22.85             0.0  \n",
       "...                                    ...             ...  \n",
       "1608186                              32.70             0.0  \n",
       "1608190                              32.40           740.0  \n",
       "1608191                              32.40           740.0  \n",
       "1608192                              30.90          3060.0  \n",
       "1608204                              41.30            40.0  \n",
       "\n",
       "[71432 rows x 5 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postes_vacants_CNP_regions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "149a1622",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Régions                \n",
       "Alberta                     9759\n",
       "Colombie-Britannique       10631\n",
       "Manitoba                    6234\n",
       "Nouveau-Brunswick           4257\n",
       "Nouvelle-Écosse             5076\n",
       "Ontario                    13320\n",
       "Québec                     12330\n",
       "Saskatchewan                5705\n",
       "Terre-Neuve-et-Labrador     2877\n",
       "Île-du-Prince-Édouard       1243\n",
       "dtype: int64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postes_vacants_CNP_regions[['Régions']].value_counts().sort_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6313b252",
   "metadata": {},
   "source": [
    "### Analyse caractéristiques numériques"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "83196e27",
   "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>Moyenne du salaire horaire offert</th>\n",
       "      <th>Postes vacants</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>284729.000000</td>\n",
       "      <td>2.847290e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>24.332350</td>\n",
       "      <td>7.200326e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>10.759934</td>\n",
       "      <td>7.301819e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>8.950000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>16.600000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>21.750000</td>\n",
       "      <td>5.500000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>29.550000</td>\n",
       "      <td>2.900000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>177.600000</td>\n",
       "      <td>1.031955e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Moyenne du salaire horaire offert  Postes vacants\n",
       "count                      284729.000000    2.847290e+05\n",
       "mean                           24.332350    7.200326e+02\n",
       "std                            10.759934    7.301819e+03\n",
       "min                             8.950000    0.000000e+00\n",
       "25%                            16.600000    0.000000e+00\n",
       "50%                            21.750000    5.500000e+01\n",
       "75%                            29.550000    2.900000e+02\n",
       "max                           177.600000    1.031955e+06"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postes_vacants_CNP_0.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be93b93e",
   "metadata": {},
   "source": [
    "75% des postes vacants ont la moyenne du salaire horaire offert au moins de 30.\n",
    "Le résultat tient compte de la répartition géographique: Canada, régions, Région économique.\n",
    "\n",
    "**La règle empirique**\n",
    "\n",
    "L’écart-type et la moyenne ensemble peuvent vous indiquer où se trouvent la plupart des valeurs de votre distribution si elles suivent une distribution normale.\n",
    "\n",
    "La règle empirique, ou la règle 68-95-99.7, vous indique où se situent vos valeurs :\n",
    "\n",
    "* Environ 68% des scores se situent à moins de 1 écart-type de la moyenne,\n",
    "* Environ 95% des scores se situent à moins de 2 écarts-types de la moyenne,\n",
    "* Environ 99,7% des scores se situent à moins de 3 écarts-types de la moyenne.\n",
    "\n",
    "La valeur de l'écart type est 11, indique que les valeurs sont très variés, réparties sur une plage plus large.\n",
    "Cela signifie que la plus part(68%) des postes vacants ont la moyenne du salaire horraire offert à moins de 11 de la moyenne(13-33)- un écart type - et presque toutes les postes (95 %) ont la moyenne du salaire horraire offert à moin de 22 de la moyenne (2-46)-deux-écart type, en supposant que la distribution est normale."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "138a2b6c",
   "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>Moyenne du salaire horaire offert</th>\n",
       "      <th>Postes vacants</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>71432.000000</td>\n",
       "      <td>71432.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>25.344301</td>\n",
       "      <td>989.197839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>10.897026</td>\n",
       "      <td>6249.509672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>9.400000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>17.200000</td>\n",
       "      <td>15.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>23.100000</td>\n",
       "      <td>135.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>31.050000</td>\n",
       "      <td>535.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>130.800000</td>\n",
       "      <td>387235.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Moyenne du salaire horaire offert  Postes vacants\n",
       "count                       71432.000000    71432.000000\n",
       "mean                           25.344301      989.197839\n",
       "std                            10.897026     6249.509672\n",
       "min                             9.400000        0.000000\n",
       "25%                            17.200000       15.000000\n",
       "50%                            23.100000      135.000000\n",
       "75%                            31.050000      535.000000\n",
       "max                           130.800000   387235.000000"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postes_vacants_CNP_regions.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36058df8",
   "metadata": {},
   "source": [
    "Si on considère seulement la répartition géographique Canada et régions, on observe un changement au niveau des valeurs\n",
    "min, et max, mais l'écart type reste le même.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81b00053",
   "metadata": {},
   "source": [
    "### Agregation des données par année"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "9395cbec",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\daian\\AppData\\Local\\Temp\\ipykernel_19488\\4266169036.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  postes_vacants_CNP_regions['Annee'] = postes_vacants_CNP_regions['Année/Trim'].str[:4]\n"
     ]
    }
   ],
   "source": [
    "postes_vacants_CNP_regions['Annee'] = postes_vacants_CNP_regions['Année/Trim'].str[:4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "79d9bfe7",
   "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>Année/Trim</th>\n",
       "      <th>Régions</th>\n",
       "      <th>CNP</th>\n",
       "      <th>Moyenne du salaire horaire offert</th>\n",
       "      <th>Postes vacants</th>\n",
       "      <th>Annee</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>701</th>\n",
       "      <td>2015-01</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Affaires, finance et administration [1]</td>\n",
       "      <td>24.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>801</th>\n",
       "      <td>2015-01</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Cadres intermédiaires dans le commerce de déta...</td>\n",
       "      <td>20.65</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>802</th>\n",
       "      <td>2015-01</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Cadres intermédiaires des métiers, des transpo...</td>\n",
       "      <td>41.10</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>924</th>\n",
       "      <td>2015-01</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Dispensateurs/dispensatrices de soins et perso...</td>\n",
       "      <td>16.25</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>936</th>\n",
       "      <td>2015-01</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Enseignement, droit et services sociaux, commu...</td>\n",
       "      <td>22.85</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Année/Trim  Régions                                                CNP  \\\n",
       "701    2015-01  Alberta            Affaires, finance et administration [1]   \n",
       "801    2015-01  Alberta  Cadres intermédiaires dans le commerce de déta...   \n",
       "802    2015-01  Alberta  Cadres intermédiaires des métiers, des transpo...   \n",
       "924    2015-01  Alberta  Dispensateurs/dispensatrices de soins et perso...   \n",
       "936    2015-01  Alberta  Enseignement, droit et services sociaux, commu...   \n",
       "\n",
       "     Moyenne du salaire horaire offert  Postes vacants Annee  \n",
       "701                              24.00             0.0  2015  \n",
       "801                              20.65             0.0  2015  \n",
       "802                              41.10             0.0  2015  \n",
       "924                              16.25             0.0  2015  \n",
       "936                              22.85             0.0  2015  "
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postes_vacants_CNP_regions.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "bee57329",
   "metadata": {},
   "outputs": [],
   "source": [
    "def process_date(dg):\n",
    "    return pd.DataFrame([[\n",
    "                        dg[\"Postes vacants\"].sum(),\n",
    "                        dg[\"Moyenne du salaire horaire offert\"].mean(),\n",
    "                        ]], columns=[\"Postes vacants\", \"Moyenne du salaire horaire offert\"])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "8ba25a8e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_postes_vacants=postes_vacants_CNP_regions.groupby([\"Régions\",\"CNP\",\"Annee\"]).apply(process_date).reset_index(3, drop=True).reset_index(drop=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "cd30576a",
   "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>Postes vacants</th>\n",
       "      <th>Moyenne du salaire horaire offert</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2.741000e+04</td>\n",
       "      <td>27410.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.577905e+03</td>\n",
       "      <td>25.845663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.867961e+04</td>\n",
       "      <td>10.937729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>9.533333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.000000e+01</td>\n",
       "      <td>17.637500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.950000e+02</td>\n",
       "      <td>23.700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.168750e+03</td>\n",
       "      <td>31.546875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.148010e+06</td>\n",
       "      <td>126.325000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Postes vacants  Moyenne du salaire horaire offert\n",
       "count    2.741000e+04                       27410.000000\n",
       "mean     2.577905e+03                          25.845663\n",
       "std      1.867961e+04                          10.937729\n",
       "min      0.000000e+00                           9.533333\n",
       "25%      2.000000e+01                          17.637500\n",
       "50%      1.950000e+02                          23.700000\n",
       "75%      1.168750e+03                          31.546875\n",
       "max      1.148010e+06                         126.325000"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_postes_vacants.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1d511ee",
   "metadata": {},
   "source": [
    "## Visualisation des données"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "b47cb40c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(27410, 5)"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_postes_vacants.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "e29922c3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Categorical Variables:\n",
      "Index(['Régions', 'CNP', 'Annee'], dtype='object')\n",
      "Numerical Variables:\n",
      "['Postes vacants', 'Moyenne du salaire horaire offert']\n"
     ]
    }
   ],
   "source": [
    "# séparer les variables numériques et catégorielles\n",
    "cat_cols=df_postes_vacants.select_dtypes(include=['object']).columns\n",
    "num_cols = df_postes_vacants.select_dtypes(include=np.number).columns.tolist()\n",
    "print(\"Categorical Variables:\")\n",
    "print(cat_cols)\n",
    "print(\"Numerical Variables:\")\n",
    "print(num_cols)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d36395de",
   "metadata": {},
   "source": [
    "### Analyse de la moyenne du salaire horaire offert"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22c6036c",
   "metadata": {},
   "source": [
    "#### Distribution "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "1233351b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Moyenne du salaire horaire offert\n",
      "Skew : 1.56\n"
     ]
    },
    {
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      "text/plain": [
       "<Figure size 1500x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "col = 'Moyenne du salaire horaire offert'\n",
    "print(col)\n",
    "print('Skew :', round(df_postes_vacants[col].skew(), 2))\n",
    "plt.figure(figsize = (15, 4))\n",
    "plt.subplot(1, 2, 1)\n",
    "df_postes_vacants[col].hist(grid=False)\n",
    "plt.ylabel('count')\n",
    "plt.subplot(1, 2, 2)\n",
    "sns.boxplot(x=df_postes_vacants[col])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2974c8cc",
   "metadata": {},
   "source": [
    "La distribution de la moyenne du salaire horaire offert est modale asymétrique positive. \n",
    "Elle est inclinée avec une queue vers la droite. \n",
    "Selon le boxplot, il y a quelques valeurs aberrantes à l’extrémité droite de la distribution de la variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "a6e47641",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lineplot(data=df_postes_vacants.sort_values(by=\"Annee\"), \n",
    "             x=\"Annee\", \n",
    "             y='Moyenne du salaire horaire offert',\n",
    "            markers=True,\n",
    "            dashes=False)\n",
    "plt.title(label=\"Evolution de la moyenne du salaire horaire offert, 2015-2022 (Source: Donnees StatCanada)\",\n",
    "          fontdict={'fontsize':10}, loc='center')\n",
    "plt.xticks(rotation=75)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "84678445",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "filtre_Ont_Qc=(df_postes_vacants['Régions'].isin(['Ontario','Québec']))\n",
    "sns.relplot(data=df_postes_vacants[filtre_Ont_Qc],\n",
    "             x=\"Annee\", \n",
    "             y='Moyenne du salaire horaire offert',\n",
    "             col='Régions',\n",
    "             kind='line',\n",
    "             #markers=True, \n",
    "            dashes=True\n",
    "            \n",
    "            )\n",
    "plt.title(label='Evolution de la moyenne du salaire horaire offert, 2015-2022 (Source: Donnees StatCanada)',\n",
    "          fontdict={'fontsize':10}, loc='left',y=1.1)\n",
    "plt.xticks(rotation=75)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "c249303e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x1200 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,12))\n",
    "sns.catplot(data=df_postes_vacants, \n",
    "            x=\"Régions\", \n",
    "            y=\"Moyenne du salaire horaire offert\", \n",
    "            kind=\"box\",\n",
    "            #palette=\"pastel\",\n",
    "           dodge=True)\n",
    "plt.title(label=\"Distribution de la moyenne du salaire horaire offert selon regions ,donnees 2015-2022(source Statistique Canada)\",\n",
    "          fontdict={'fontsize':10}, loc='center')\n",
    "plt.xticks(rotation=75)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ce72792",
   "metadata": {},
   "source": [
    "#### Valeurs aberantes "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b200b278",
   "metadata": {},
   "source": [
    " Dans ce qui suit, on va supposer, pour l'exemple, que la base de données contient 0,5% de valeurs aberrantes de toutes sortes. Ce n'est pas exagéré. Cela représente $0,005*27410 \\approx 137$ valeurs.\n",
    "\n",
    "On utilise la méthode de la [forêt d'isolation](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.IsolationForest.html) pour détecter et éliminer un maximum de 0,5% des valeurs possiblement aberrantes. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "da7de493",
   "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>Régions</th>\n",
       "      <th>CNP</th>\n",
       "      <th>Annee</th>\n",
       "      <th>Postes vacants</th>\n",
       "      <th>Moyenne du salaire horaire offert</th>\n",
       "      <th>outliers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>602</th>\n",
       "      <td>Alberta</td>\n",
       "      <td>Cadres supérieurs/cadres supérieures - adminis...</td>\n",
       "      <td>2020</td>\n",
       "      <td>15.0</td>\n",
       "      <td>80.500000</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>606</th>\n",
       "      <td>Alberta</td>\n",
       "      <td>Cadres supérieurs/cadres supérieures - commerc...</td>\n",
       "      <td>2018</td>\n",
       "      <td>0.0</td>\n",
       "      <td>86.450000</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>607</th>\n",
       "      <td>Alberta</td>\n",
       "      <td>Cadres supérieurs/cadres supérieures - commerc...</td>\n",
       "      <td>2019</td>\n",
       "      <td>0.0</td>\n",
       "      <td>71.625000</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>608</th>\n",
       "      <td>Alberta</td>\n",
       "      <td>Cadres supérieurs/cadres supérieures - commerc...</td>\n",
       "      <td>2021</td>\n",
       "      <td>5.0</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>610</th>\n",
       "      <td>Alberta</td>\n",
       "      <td>Cadres supérieurs/cadres supérieures - constru...</td>\n",
       "      <td>2016</td>\n",
       "      <td>30.0</td>\n",
       "      <td>83.812500</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>611</th>\n",
       "      <td>Alberta</td>\n",
       "      <td>Cadres supérieurs/cadres supérieures - constru...</td>\n",
       "      <td>2017</td>\n",
       "      <td>20.0</td>\n",
       "      <td>86.583333</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>613</th>\n",
       "      <td>Alberta</td>\n",
       "      <td>Cadres supérieurs/cadres supérieures - constru...</td>\n",
       "      <td>2019</td>\n",
       "      <td>80.0</td>\n",
       "      <td>106.975000</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>614</th>\n",
       "      <td>Alberta</td>\n",
       "      <td>Cadres supérieurs/cadres supérieures - constru...</td>\n",
       "      <td>2020</td>\n",
       "      <td>0.0</td>\n",
       "      <td>103.700000</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>615</th>\n",
       "      <td>Alberta</td>\n",
       "      <td>Cadres supérieurs/cadres supérieures - constru...</td>\n",
       "      <td>2022</td>\n",
       "      <td>5.0</td>\n",
       "      <td>75.425000</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>619</th>\n",
       "      <td>Alberta</td>\n",
       "      <td>Cadres supérieurs/cadres supérieures - santé, ...</td>\n",
       "      <td>2018</td>\n",
       "      <td>35.0</td>\n",
       "      <td>74.833333</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>621</th>\n",
       "      <td>Alberta</td>\n",
       "      <td>Cadres supérieurs/cadres supérieures - santé, ...</td>\n",
       "      <td>2020</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85.750000</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>623</th>\n",
       "      <td>Alberta</td>\n",
       "      <td>Cadres supérieurs/cadres supérieures - santé, ...</td>\n",
       "      <td>2022</td>\n",
       "      <td>30.0</td>\n",
       "      <td>90.075000</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>624</th>\n",
       "      <td>Alberta</td>\n",
       "      <td>Cadres supérieurs/cadres supérieures - service...</td>\n",
       "      <td>2015</td>\n",
       "      <td>10.0</td>\n",
       "      <td>95.550000</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>625</th>\n",
       "      <td>Alberta</td>\n",
       "      <td>Cadres supérieurs/cadres supérieures - service...</td>\n",
       "      <td>2016</td>\n",
       "      <td>0.0</td>\n",
       "      <td>75.150000</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>629</th>\n",
       "      <td>Alberta</td>\n",
       "      <td>Cadres supérieurs/cadres supérieures - service...</td>\n",
       "      <td>2020</td>\n",
       "      <td>30.0</td>\n",
       "      <td>90.100000</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Régions                                                CNP Annee  \\\n",
       "602  Alberta  Cadres supérieurs/cadres supérieures - adminis...  2020   \n",
       "606  Alberta  Cadres supérieurs/cadres supérieures - commerc...  2018   \n",
       "607  Alberta  Cadres supérieurs/cadres supérieures - commerc...  2019   \n",
       "608  Alberta  Cadres supérieurs/cadres supérieures - commerc...  2021   \n",
       "610  Alberta  Cadres supérieurs/cadres supérieures - constru...  2016   \n",
       "611  Alberta  Cadres supérieurs/cadres supérieures - constru...  2017   \n",
       "613  Alberta  Cadres supérieurs/cadres supérieures - constru...  2019   \n",
       "614  Alberta  Cadres supérieurs/cadres supérieures - constru...  2020   \n",
       "615  Alberta  Cadres supérieurs/cadres supérieures - constru...  2022   \n",
       "619  Alberta  Cadres supérieurs/cadres supérieures - santé, ...  2018   \n",
       "621  Alberta  Cadres supérieurs/cadres supérieures - santé, ...  2020   \n",
       "623  Alberta  Cadres supérieurs/cadres supérieures - santé, ...  2022   \n",
       "624  Alberta  Cadres supérieurs/cadres supérieures - service...  2015   \n",
       "625  Alberta  Cadres supérieurs/cadres supérieures - service...  2016   \n",
       "629  Alberta  Cadres supérieurs/cadres supérieures - service...  2020   \n",
       "\n",
       "     Postes vacants  Moyenne du salaire horaire offert  outliers  \n",
       "602            15.0                          80.500000        -1  \n",
       "606             0.0                          86.450000        -1  \n",
       "607             0.0                          71.625000        -1  \n",
       "608             5.0                          81.000000        -1  \n",
       "610            30.0                          83.812500        -1  \n",
       "611            20.0                          86.583333        -1  \n",
       "613            80.0                         106.975000        -1  \n",
       "614             0.0                         103.700000        -1  \n",
       "615             5.0                          75.425000        -1  \n",
       "619            35.0                          74.833333        -1  \n",
       "621             0.0                          85.750000        -1  \n",
       "623            30.0                          90.075000        -1  \n",
       "624            10.0                          95.550000        -1  \n",
       "625             0.0                          75.150000        -1  \n",
       "629            30.0                          90.100000        -1  "
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import IsolationForest\n",
    "# Trouvons les valeurs aberrantes; la variable 'outlier' vaut -1 \n",
    "# pour les valeurs aberrantes et +1 pour les autres.\n",
    "i_forest = IsolationForest(contamination= 0.005, random_state=42)\n",
    "df_postes_vacants_=df_postes_vacants\n",
    "df_postes_vacants_['outliers'] = i_forest.fit(np.array(df_postes_vacants_['Moyenne du salaire horaire offert']).reshape(-1, 1)).predict(np.array(df_postes_vacants_['Moyenne du salaire horaire offert']).reshape(-1, 1))\n",
    "\n",
    "# Affichons les 15 premières données de la base de données\n",
    "df_postes_vacants_[df_postes_vacants_['outliers']==-1].head(15)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af3f7eaf",
   "metadata": {},
   "source": [
    "### Analyse des postes vacants"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25fcfdd6",
   "metadata": {},
   "source": [
    "#### Distribution des postes par année"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "beb067b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(data=df_postes_vacants, \n",
    "             x=\"Annee\", \n",
    "             y='Postes vacants'\n",
    "            )\n",
    "plt.title(label=\"Distribution des postes vacants, 2015-2020 (Source: Donnees StatCanada)\",\n",
    "          fontdict={'fontsize':10}, loc='center')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dac02bf3",
   "metadata": {},
   "source": [
    "#### Distribution des postes par régions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "16215281",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(data=df_postes_vacants, \n",
    "             x=\"Régions\", \n",
    "             y='Postes vacants'\n",
    "            )\n",
    "plt.title(label=\"Distribution des postes vacants, 2015-2020 (Source: Donnees StatCanada)\",\n",
    "          fontdict={'fontsize':10}, loc='center')\n",
    "plt.xticks(rotation=75)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d117e4e",
   "metadata": {},
   "source": [
    "* Ontario a le plus grand nombre des postes vacants , suivi de Québec\n",
    "* Le plus grand nombre des postes vacants a été en 2021, suivi de 2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "8ddc4e4e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(27410, 5)"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_postes_vacants.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e988be1e",
   "metadata": {},
   "source": [
    "#### Distribution des postes par CNP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "01492bba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Adjoints administratifs juridiques/adjointes administratives juridiques [1242]                        8\n",
       "Adjoints administratifs médicaux/adjointes administratives médicales [1243]                           8\n",
       "Adjoints administratifs/adjointes administratives [1241]                                              8\n",
       "Adjoints administratifs/adjointes administratives de bureau - général, juridique et médical [124]     8\n",
       "Adjoints/adjointes de direction [1222]                                                                8\n",
       "Administrateurs/administratrices - enseignement postsecondaire et formation professionnelle [0421]    8\n",
       "Administrateurs/administratrices de la paye [1432]                                                    8\n",
       "Affaires, finance et administration [1]                                                               8\n",
       "Acheteurs/acheteuses des commerces de détail et de gros [6222]                                        7\n",
       "Agents/agentes aux achats [1225]                                                                      4\n",
       "Name: CNP, dtype: int64"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_postes_vacants['CNP'].head(75).value_counts()\n",
    "data=df.sort_values('Global_Sales').tail(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "32d31eb3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title(\"Top 10 postes vacants selon leur CNP4, 2015-2020 (Source: Donnees Statistique Canada)' \")\n",
    "sns.countplot(data=df_postes_vacants.nlargest(85,'Postes vacants'),\n",
    "              y='CNP',\n",
    "              #order = df_postes_vacants['CNP'].head(75).value_counts().index,\n",
    "              palette='pastel')\n",
    "plt.xticks(rotation=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8aa2ad08",
   "metadata": {},
   "source": [
    "## Exporter to csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "7ef2515b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_postes_vacants.to_csv(\"df_postes_vacants\", index = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9a0f567",
   "metadata": {},
   "source": [
    "### Annexe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f585acc0",
   "metadata": {},
   "outputs": [],
   "source": [
    "for col in num_cols:\n",
    "    print(col)\n",
    "    print('Skew :', round(df_postes_vacants[col].skew(), 2))\n",
    "    plt.figure(figsize = (15, 4))\n",
    "    plt.subplot(1, 2, 1)\n",
    "    df_postes_vacants[col].hist(grid=False)\n",
    "    plt.ylabel('count')\n",
    "    plt.subplot(1, 2, 2)\n",
    "    sns.boxplot(x=df_postes_vacants[col])\n",
    "    plt.show()"
   ]
  }
 ],
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  "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": "3.8.11"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
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   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "349.091px"
   },
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
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