{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Création des données pour le chapitre"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'fr_FR.UTF-8'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Markdown as md\n",
    "from IPython.display import display, HTML\n",
    "import pandas as pd\n",
    "import ipywidgets as widgets\n",
    "from pathlib import Path\n",
    "from datetime import datetime\n",
    "import locale\n",
    "locale.setlocale(locale.LC_ALL, 'fr_FR.UTF-8')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Les données viennent de https://github.com/chris1610/pbpython/blob/master/data/2018_Sales_Total.xlsx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_excel('2018_Sales_Total.xlsx')\n",
    "df = df.rename(columns={\"Nom\": \"Vendeur\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Numero de compte</th>\n",
       "      <th>Vendeur</th>\n",
       "      <th>Code</th>\n",
       "      <th>Prix</th>\n",
       "      <th>date</th>\n",
       "      <th>Produit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>740150</td>\n",
       "      <td>Barton LLC</td>\n",
       "      <td>B1-20000</td>\n",
       "      <td>86.69</td>\n",
       "      <td>2018-01-01 07:21:51</td>\n",
       "      <td>Logiciel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>714466</td>\n",
       "      <td>Trantow-Barrows</td>\n",
       "      <td>S2-77896</td>\n",
       "      <td>63.16</td>\n",
       "      <td>2018-01-01 10:00:47</td>\n",
       "      <td>Ordinateur</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>218895</td>\n",
       "      <td>Kulas Inc</td>\n",
       "      <td>B1-69924</td>\n",
       "      <td>90.70</td>\n",
       "      <td>2018-01-01 13:24:58</td>\n",
       "      <td>Logiciel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>307599</td>\n",
       "      <td>Kassulke, Ondricka and Metz</td>\n",
       "      <td>S1-65481</td>\n",
       "      <td>21.05</td>\n",
       "      <td>2018-01-01 15:05:22</td>\n",
       "      <td>Impression</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>412290</td>\n",
       "      <td>Jerde-Hilpert</td>\n",
       "      <td>S2-34077</td>\n",
       "      <td>83.21</td>\n",
       "      <td>2018-01-01 23:26:55</td>\n",
       "      <td>Ordinateur</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Numero de compte                      Vendeur      Code   Prix  \\\n",
       "0            740150                   Barton LLC  B1-20000  86.69   \n",
       "1            714466              Trantow-Barrows  S2-77896  63.16   \n",
       "2            218895                    Kulas Inc  B1-69924  90.70   \n",
       "3            307599  Kassulke, Ondricka and Metz  S1-65481  21.05   \n",
       "4            412290                Jerde-Hilpert  S2-34077  83.21   \n",
       "\n",
       "                 date     Produit  \n",
       "0 2018-01-01 07:21:51    Logiciel  \n",
       "1 2018-01-01 10:00:47  Ordinateur  \n",
       "2 2018-01-01 13:24:58    Logiciel  \n",
       "3 2018-01-01 15:05:22  Impression  \n",
       "4 2018-01-01 23:26:55  Ordinateur  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Réduction des codes produits avec un type de produit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['B1-20000', 'S2-77896', 'B1-69924', 'S1-65481', 'S2-34077',\n",
       "       'B1-65551', 'S1-30248', 'S1-50961', 'S2-82423', 'S2-00301',\n",
       "       'S2-23246', 'S2-10342', 'B1-53102', 'S1-06532', 'B1-50809',\n",
       "       'S1-82801', 'B1-04202', 'S2-83881', 'S2-78676', 'B1-53636',\n",
       "       'B1-38851', 'B1-86481', 'S1-93683', 'B1-33087', 'S1-27722',\n",
       "       'B1-05914', 'B1-33364', 'S2-16558', 'S1-47412', 'S2-11481'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Code.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['B1', 'S2', 'S1'], dtype=object)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.apply(lambda x: x.Code[:2], axis=1).unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>Numero de compte</th>\n",
       "      <th>Vendeur</th>\n",
       "      <th>Code</th>\n",
       "      <th>Prix</th>\n",
       "      <th>date</th>\n",
       "      <th>Produit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>740150</td>\n",
       "      <td>Barton LLC</td>\n",
       "      <td>B1-20000</td>\n",
       "      <td>86.69</td>\n",
       "      <td>2018-01-01 07:21:51</td>\n",
       "      <td>Logiciel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>714466</td>\n",
       "      <td>Trantow-Barrows</td>\n",
       "      <td>S2-77896</td>\n",
       "      <td>63.16</td>\n",
       "      <td>2018-01-01 10:00:47</td>\n",
       "      <td>Ordinateur</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>218895</td>\n",
       "      <td>Kulas Inc</td>\n",
       "      <td>B1-69924</td>\n",
       "      <td>90.70</td>\n",
       "      <td>2018-01-01 13:24:58</td>\n",
       "      <td>Logiciel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>307599</td>\n",
       "      <td>Kassulke, Ondricka and Metz</td>\n",
       "      <td>S1-65481</td>\n",
       "      <td>21.05</td>\n",
       "      <td>2018-01-01 15:05:22</td>\n",
       "      <td>Impression</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>412290</td>\n",
       "      <td>Jerde-Hilpert</td>\n",
       "      <td>S2-34077</td>\n",
       "      <td>83.21</td>\n",
       "      <td>2018-01-01 23:26:55</td>\n",
       "      <td>Ordinateur</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Numero de compte                      Vendeur      Code   Prix  \\\n",
       "0            740150                   Barton LLC  B1-20000  86.69   \n",
       "1            714466              Trantow-Barrows  S2-77896  63.16   \n",
       "2            218895                    Kulas Inc  B1-69924  90.70   \n",
       "3            307599  Kassulke, Ondricka and Metz  S1-65481  21.05   \n",
       "4            412290                Jerde-Hilpert  S2-34077  83.21   \n",
       "\n",
       "                 date     Produit  \n",
       "0 2018-01-01 07:21:51    Logiciel  \n",
       "1 2018-01-01 10:00:47  Ordinateur  \n",
       "2 2018-01-01 13:24:58    Logiciel  \n",
       "3 2018-01-01 15:05:22  Impression  \n",
       "4 2018-01-01 23:26:55  Ordinateur  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "code_prod = {\n",
    "    \"B1\": \"Logiciel\",\n",
    "    \"S1\": \"Impression\",\n",
    "    \"S2\": \"Ordinateur\"\n",
    "}\n",
    "df[\"Produit\"] = df.apply(lambda x: code_prod[x.Code[:2]], axis=1)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Réduction du nombre de noms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Barton LLC', 'Trantow-Barrows', 'Kulas Inc',\n",
       "       'Kassulke, Ondricka and Metz', 'Jerde-Hilpert'], dtype=object)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uniq_names = df.Vendeur.unique()\n",
    "uniq_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Numero de compte</th>\n",
       "      <th>Vendeur</th>\n",
       "      <th>Code</th>\n",
       "      <th>Prix</th>\n",
       "      <th>date</th>\n",
       "      <th>Produit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>740150</td>\n",
       "      <td>Barton LLC</td>\n",
       "      <td>B1-20000</td>\n",
       "      <td>86.69</td>\n",
       "      <td>2018-01-01 07:21:51</td>\n",
       "      <td>Logiciel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>714466</td>\n",
       "      <td>Trantow-Barrows</td>\n",
       "      <td>S2-77896</td>\n",
       "      <td>63.16</td>\n",
       "      <td>2018-01-01 10:00:47</td>\n",
       "      <td>Ordinateur</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>218895</td>\n",
       "      <td>Kulas Inc</td>\n",
       "      <td>B1-69924</td>\n",
       "      <td>90.70</td>\n",
       "      <td>2018-01-01 13:24:58</td>\n",
       "      <td>Logiciel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>307599</td>\n",
       "      <td>Kassulke, Ondricka and Metz</td>\n",
       "      <td>S1-65481</td>\n",
       "      <td>21.05</td>\n",
       "      <td>2018-01-01 15:05:22</td>\n",
       "      <td>Impression</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>412290</td>\n",
       "      <td>Jerde-Hilpert</td>\n",
       "      <td>S2-34077</td>\n",
       "      <td>83.21</td>\n",
       "      <td>2018-01-01 23:26:55</td>\n",
       "      <td>Ordinateur</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Numero de compte                      Vendeur      Code   Prix  \\\n",
       "0            740150                   Barton LLC  B1-20000  86.69   \n",
       "1            714466              Trantow-Barrows  S2-77896  63.16   \n",
       "2            218895                    Kulas Inc  B1-69924  90.70   \n",
       "3            307599  Kassulke, Ondricka and Metz  S1-65481  21.05   \n",
       "4            412290                Jerde-Hilpert  S2-34077  83.21   \n",
       "\n",
       "                 date     Produit  \n",
       "0 2018-01-01 07:21:51    Logiciel  \n",
       "1 2018-01-01 10:00:47  Ordinateur  \n",
       "2 2018-01-01 13:24:58    Logiciel  \n",
       "3 2018-01-01 15:05:22  Impression  \n",
       "4 2018-01-01 23:26:55  Ordinateur  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nbr_names = 5\n",
    "names = {orig: uniq_names[i%nbr_names] for (i, orig) in enumerate(uniq_names)}\n",
    "names\n",
    "df[\"Vendeur\"] = df.apply(lambda x: names[x.Vendeur], axis=1)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1500 entries, 0 to 1499\n",
      "Data columns (total 6 columns):\n",
      "Numero de compte    1500 non-null int64\n",
      "Vendeur             1500 non-null object\n",
      "Code                1500 non-null object\n",
      "Prix                1500 non-null float64\n",
      "date                1500 non-null datetime64[ns]\n",
      "Produit             1500 non-null object\n",
      "dtypes: datetime64[ns](1), float64(1), int64(1), object(3)\n",
      "memory usage: 70.4+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_excel(\"2018_Sales_Total.xlsx\", index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Données à traiter à la main - 10 premiers jours de janvier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>Numero de compte</th>\n",
       "      <th>Vendeur</th>\n",
       "      <th>Code</th>\n",
       "      <th>Prix</th>\n",
       "      <th>date</th>\n",
       "      <th>Produit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>740150</td>\n",
       "      <td>Barton LLC</td>\n",
       "      <td>B1-20000</td>\n",
       "      <td>86.69</td>\n",
       "      <td>2018-01-01 07:21:51</td>\n",
       "      <td>Logiciel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>714466</td>\n",
       "      <td>Trantow-Barrows</td>\n",
       "      <td>S2-77896</td>\n",
       "      <td>63.16</td>\n",
       "      <td>2018-01-01 10:00:47</td>\n",
       "      <td>Ordinateur</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>218895</td>\n",
       "      <td>Kulas Inc</td>\n",
       "      <td>B1-69924</td>\n",
       "      <td>90.70</td>\n",
       "      <td>2018-01-01 13:24:58</td>\n",
       "      <td>Logiciel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>307599</td>\n",
       "      <td>Kassulke, Ondricka and Metz</td>\n",
       "      <td>S1-65481</td>\n",
       "      <td>21.05</td>\n",
       "      <td>2018-01-01 15:05:22</td>\n",
       "      <td>Impression</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>412290</td>\n",
       "      <td>Jerde-Hilpert</td>\n",
       "      <td>S2-34077</td>\n",
       "      <td>83.21</td>\n",
       "      <td>2018-01-01 23:26:55</td>\n",
       "      <td>Ordinateur</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Numero de compte                      Vendeur      Code   Prix  \\\n",
       "0            740150                   Barton LLC  B1-20000  86.69   \n",
       "1            714466              Trantow-Barrows  S2-77896  63.16   \n",
       "2            218895                    Kulas Inc  B1-69924  90.70   \n",
       "3            307599  Kassulke, Ondricka and Metz  S1-65481  21.05   \n",
       "4            412290                Jerde-Hilpert  S2-34077  83.21   \n",
       "\n",
       "                 date     Produit  \n",
       "0 2018-01-01 07:21:51    Logiciel  \n",
       "1 2018-01-01 10:00:47  Ordinateur  \n",
       "2 2018-01-01 13:24:58    Logiciel  \n",
       "3 2018-01-01 15:05:22  Impression  \n",
       "4 2018-01-01 23:26:55  Ordinateur  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hand_df = df.loc[df.date < \"2018-01-11\"]\n",
    "hand_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "hand_df.to_excel(\"201801_sales.xlsx\", index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Quelques tableau d'effectifs et de fréquences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [],
   "source": [
    "count = lambda x: x.count()\n",
    "count.__name__ = \"Effectif\"\n",
    "\n",
    "#freq = lambda x: f\"{x.count()/hand_df['Prix'].count():.2%}\"\n",
    "#freq.__name__ = \"Fréquence marginale\"\n",
    "\n",
    "def freq(total):\n",
    "    func = lambda x: f\"{x.count()/total:.2%}\"\n",
    "    func.__name__ = \"Fréquence marginale\"\n",
    "    return func"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Par rapport aux vendeurs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "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>Effectif</th>\n",
       "      <th>Fréquence marginale</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vendeur</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Barton LLC</th>\n",
       "      <td>8</td>\n",
       "      <td>19.51%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jerde-Hilpert</th>\n",
       "      <td>7</td>\n",
       "      <td>17.07%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kassulke, Ondricka and Metz</th>\n",
       "      <td>5</td>\n",
       "      <td>12.20%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kulas Inc</th>\n",
       "      <td>6</td>\n",
       "      <td>14.63%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trantow-Barrows</th>\n",
       "      <td>15</td>\n",
       "      <td>36.59%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>41</td>\n",
       "      <td>100.00%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             Effectif Fréquence marginale\n",
       "Vendeur                                                  \n",
       "Barton LLC                          8              19.51%\n",
       "Jerde-Hilpert                       7              17.07%\n",
       "Kassulke, Ondricka and Metz         5              12.20%\n",
       "Kulas Inc                           6              14.63%\n",
       "Trantow-Barrows                    15              36.59%\n",
       "Total                              41             100.00%"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pt_sellers = pd.pivot_table(hand_df,\n",
    "              index=\"Vendeur\",\n",
    "              values=\"Code\",\n",
    "              aggfunc=[count, freq(hand_df[\"Prix\"].count())],\n",
    "              margins=True,\n",
    "              margins_name=\"Total\")\n",
    "pt_sellers.columns = pt_sellers.columns.droplevel(1)\n",
    "pt_sellers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Par rapport aux Produits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "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>Effectif</th>\n",
       "      <th>Fréquence marginale</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Produit</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Impression</th>\n",
       "      <td>12</td>\n",
       "      <td>29.27%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Logiciel</th>\n",
       "      <td>13</td>\n",
       "      <td>31.71%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ordinateur</th>\n",
       "      <td>16</td>\n",
       "      <td>39.02%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>41</td>\n",
       "      <td>100.00%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Effectif Fréquence marginale\n",
       "Produit                                 \n",
       "Impression        12              29.27%\n",
       "Logiciel          13              31.71%\n",
       "Ordinateur        16              39.02%\n",
       "Total             41             100.00%"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pt_sellers = pd.pivot_table(hand_df,\n",
    "              index=\"Produit\",\n",
    "              values=\"Code\",\n",
    "              aggfunc=[count, freq(hand_df[\"Prix\"].count())],\n",
    "              margins=True,\n",
    "              margins_name=\"Total\"\n",
    "                           )\n",
    "pt_sellers.columns = pt_sellers.columns.droplevel(1)\n",
    "pt_sellers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Croisement de ventes entre vendeurs et produits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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>Produit</th>\n",
       "      <th>Impression</th>\n",
       "      <th>Logiciel</th>\n",
       "      <th>Ordinateur</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vendeur</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Barton LLC</th>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jerde-Hilpert</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kassulke, Ondricka and Metz</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kulas Inc</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trantow-Barrows</th>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>12.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Produit                      Impression  Logiciel  Ordinateur  Total\n",
       "Vendeur                                                             \n",
       "Barton LLC                          3.0       4.0         1.0      8\n",
       "Jerde-Hilpert                       2.0       1.0         4.0      7\n",
       "Kassulke, Ondricka and Metz         1.0       NaN         4.0      5\n",
       "Kulas Inc                           2.0       2.0         2.0      6\n",
       "Trantow-Barrows                     4.0       6.0         5.0     15\n",
       "Total                              12.0      13.0        16.0     41"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(hand_df,\n",
    "               index=\"Vendeur\",\n",
    "               columns = \"Produit\",\n",
    "               values=\"Code\",\n",
    "               aggfunc=\"count\",\n",
    "               margins=True,\n",
    "              margins_name=\"Total\"\n",
    "              )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{tabular}{lrrrr}\n",
      "\\toprule\n",
      "\\textbf{Produit} &  Impression &  Logiciel &  Ordinateur &  Total \\\\\n",
      "\\textbf{Vendeur                    } &             &           &             &        \\\\\n",
      "\\midrule\n",
      "\\textbf{Barton LLC                 } &           3 &         4 &           1 &      8 \\\\\n",
      "\\textbf{Jerde-Hilpert              } &           2 &         1 &           4 &      7 \\\\\n",
      "\\textbf{Kassulke, Ondricka and Metz} &           1 &       nan &           4 &      5 \\\\\n",
      "\\textbf{Kulas Inc                  } &           2 &         2 &           2 &      6 \\\\\n",
      "\\textbf{Trantow-Barrows            } &           4 &         6 &           5 &     15 \\\\\n",
      "\\textbf{Total                      } &          12 &        13 &          16 &     41 \\\\\n",
      "\\bottomrule\n",
      "\\end{tabular}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(pd.pivot_table(hand_df,\n",
    "               index=\"Vendeur\",\n",
    "               columns = \"Produit\",\n",
    "               values=\"Code\",\n",
    "               aggfunc=\"count\",\n",
    "               margins=True,\n",
    "              margins_name=\"Total\"\n",
    "              )\\\n",
    "      .to_latex(\n",
    "    float_format=\"{:0.0f}\".format,\n",
    "    bold_rows=True\n",
    ")\n",
    "     )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Fréquences marginales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "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>Produit</th>\n",
       "      <th>Impression</th>\n",
       "      <th>Logiciel</th>\n",
       "      <th>Ordinateur</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vendeur</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Barton LLC</th>\n",
       "      <td>7.32%</td>\n",
       "      <td>9.76%</td>\n",
       "      <td>2.44%</td>\n",
       "      <td>19.51%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jerde-Hilpert</th>\n",
       "      <td>4.88%</td>\n",
       "      <td>2.44%</td>\n",
       "      <td>9.76%</td>\n",
       "      <td>17.07%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kassulke, Ondricka and Metz</th>\n",
       "      <td>2.44%</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.76%</td>\n",
       "      <td>12.20%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kulas Inc</th>\n",
       "      <td>4.88%</td>\n",
       "      <td>4.88%</td>\n",
       "      <td>4.88%</td>\n",
       "      <td>14.63%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trantow-Barrows</th>\n",
       "      <td>9.76%</td>\n",
       "      <td>14.63%</td>\n",
       "      <td>12.20%</td>\n",
       "      <td>36.59%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>29.27%</td>\n",
       "      <td>31.71%</td>\n",
       "      <td>39.02%</td>\n",
       "      <td>100.00%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Produit                     Impression Logiciel Ordinateur    Total\n",
       "Vendeur                                                            \n",
       "Barton LLC                       7.32%    9.76%      2.44%   19.51%\n",
       "Jerde-Hilpert                    4.88%    2.44%      9.76%   17.07%\n",
       "Kassulke, Ondricka and Metz      2.44%      NaN      9.76%   12.20%\n",
       "Kulas Inc                        4.88%    4.88%      4.88%   14.63%\n",
       "Trantow-Barrows                  9.76%   14.63%     12.20%   36.59%\n",
       "Total                           29.27%   31.71%     39.02%  100.00%"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(hand_df,\n",
    "               index=\"Vendeur\",\n",
    "               columns = \"Produit\",\n",
    "               values=\"Code\",\n",
    "               aggfunc=freq(hand_df[\"Prix\"].count()),\n",
    "               margins=True,\n",
    "              margins_name=\"Total\"\n",
    "              )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ventes sur le mois de Février"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>Numero de compte</th>\n",
       "      <th>Vendeur</th>\n",
       "      <th>Code</th>\n",
       "      <th>Prix</th>\n",
       "      <th>date</th>\n",
       "      <th>Produit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>383080</td>\n",
       "      <td>Trantow-Barrows</td>\n",
       "      <td>B1-20000</td>\n",
       "      <td>33.69</td>\n",
       "      <td>2018-02-01 09:04:59</td>\n",
       "      <td>Logiciel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>412290</td>\n",
       "      <td>Jerde-Hilpert</td>\n",
       "      <td>S1-27722</td>\n",
       "      <td>21.12</td>\n",
       "      <td>2018-02-01 11:51:46</td>\n",
       "      <td>Impression</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>412290</td>\n",
       "      <td>Jerde-Hilpert</td>\n",
       "      <td>B1-86481</td>\n",
       "      <td>35.99</td>\n",
       "      <td>2018-02-01 17:24:32</td>\n",
       "      <td>Logiciel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>412290</td>\n",
       "      <td>Jerde-Hilpert</td>\n",
       "      <td>B1-20000</td>\n",
       "      <td>78.90</td>\n",
       "      <td>2018-02-01 19:56:48</td>\n",
       "      <td>Logiciel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>672390</td>\n",
       "      <td>Trantow-Barrows</td>\n",
       "      <td>S1-06532</td>\n",
       "      <td>55.82</td>\n",
       "      <td>2018-02-02 03:45:20</td>\n",
       "      <td>Impression</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Numero de compte          Vendeur      Code   Prix                date  \\\n",
       "134            383080  Trantow-Barrows  B1-20000  33.69 2018-02-01 09:04:59   \n",
       "135            412290    Jerde-Hilpert  S1-27722  21.12 2018-02-01 11:51:46   \n",
       "136            412290    Jerde-Hilpert  B1-86481  35.99 2018-02-01 17:24:32   \n",
       "137            412290    Jerde-Hilpert  B1-20000  78.90 2018-02-01 19:56:48   \n",
       "138            672390  Trantow-Barrows  S1-06532  55.82 2018-02-02 03:45:20   \n",
       "\n",
       "        Produit  \n",
       "134    Logiciel  \n",
       "135  Impression  \n",
       "136    Logiciel  \n",
       "137    Logiciel  \n",
       "138  Impression  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feb_df = df.loc[(df.date < \"2018-03-01\") & (df.date >= \"2018-02-01\")]\n",
    "feb_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Produit</th>\n",
       "      <th>Impression</th>\n",
       "      <th>Logiciel</th>\n",
       "      <th>Ordinateur</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vendeur</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Barton LLC</th>\n",
       "      <td>5</td>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jerde-Hilpert</th>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kassulke, Ondricka and Metz</th>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kulas Inc</th>\n",
       "      <td>6</td>\n",
       "      <td>15</td>\n",
       "      <td>3</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trantow-Barrows</th>\n",
       "      <td>13</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>36</td>\n",
       "      <td>49</td>\n",
       "      <td>23</td>\n",
       "      <td>108</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Produit                      Impression  Logiciel  Ordinateur  Total\n",
       "Vendeur                                                             \n",
       "Barton LLC                            5        12           2     19\n",
       "Jerde-Hilpert                         6         5           6     17\n",
       "Kassulke, Ondricka and Metz           6         9           5     20\n",
       "Kulas Inc                             6        15           3     24\n",
       "Trantow-Barrows                      13         8           7     28\n",
       "Total                                36        49          23    108"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(feb_df,\n",
    "               index=\"Vendeur\",\n",
    "               columns = \"Produit\",\n",
    "               values=\"Code\",\n",
    "               aggfunc=\"count\",\n",
    "               margins=True,\n",
    "              margins_name=\"Total\"\n",
    "              )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{tabular}{lrrrr}\n",
      "\\toprule\n",
      "\\textbf{Produit} &  Impression &  Logiciel &  Ordinateur &  Total \\\\\n",
      "\\textbf{Vendeur                    } &             &           &             &        \\\\\n",
      "\\midrule\n",
      "\\textbf{Barton LLC                 } &           5 &        12 &           2 &     19 \\\\\n",
      "\\textbf{Jerde-Hilpert              } &           6 &         5 &           6 &     17 \\\\\n",
      "\\textbf{Kassulke, Ondricka and Metz} &           6 &         9 &           5 &     20 \\\\\n",
      "\\textbf{Kulas Inc                  } &           6 &        15 &           3 &     24 \\\\\n",
      "\\textbf{Trantow-Barrows            } &          13 &         8 &           7 &     28 \\\\\n",
      "\\textbf{Total                      } &          36 &        49 &          23 &    108 \\\\\n",
      "\\bottomrule\n",
      "\\end{tabular}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(pd.pivot_table(feb_df,\n",
    "               index=\"Vendeur\",\n",
    "               columns = \"Produit\",\n",
    "               values=\"Code\",\n",
    "               aggfunc=\"count\",\n",
    "               margins=True,\n",
    "              margins_name=\"Total\"\n",
    "              )\\\n",
    "      .to_latex(\n",
    "    float_format=\"{:0.0f}\".format,\n",
    "    bold_rows=True\n",
    ")\n",
    "     )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Tableau des fréquences marginales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "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>Produit</th>\n",
       "      <th>Impression</th>\n",
       "      <th>Logiciel</th>\n",
       "      <th>Ordinateur</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vendeur</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Barton LLC</th>\n",
       "      <td>4.63%</td>\n",
       "      <td>11.11%</td>\n",
       "      <td>1.85%</td>\n",
       "      <td>17.59%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jerde-Hilpert</th>\n",
       "      <td>5.56%</td>\n",
       "      <td>4.63%</td>\n",
       "      <td>5.56%</td>\n",
       "      <td>15.74%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kassulke, Ondricka and Metz</th>\n",
       "      <td>5.56%</td>\n",
       "      <td>8.33%</td>\n",
       "      <td>4.63%</td>\n",
       "      <td>18.52%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kulas Inc</th>\n",
       "      <td>5.56%</td>\n",
       "      <td>13.89%</td>\n",
       "      <td>2.78%</td>\n",
       "      <td>22.22%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trantow-Barrows</th>\n",
       "      <td>12.04%</td>\n",
       "      <td>7.41%</td>\n",
       "      <td>6.48%</td>\n",
       "      <td>25.93%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>33.33%</td>\n",
       "      <td>45.37%</td>\n",
       "      <td>21.30%</td>\n",
       "      <td>100.00%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Produit                     Impression Logiciel Ordinateur    Total\n",
       "Vendeur                                                            \n",
       "Barton LLC                       4.63%   11.11%      1.85%   17.59%\n",
       "Jerde-Hilpert                    5.56%    4.63%      5.56%   15.74%\n",
       "Kassulke, Ondricka and Metz      5.56%    8.33%      4.63%   18.52%\n",
       "Kulas Inc                        5.56%   13.89%      2.78%   22.22%\n",
       "Trantow-Barrows                 12.04%    7.41%      6.48%   25.93%\n",
       "Total                           33.33%   45.37%     21.30%  100.00%"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(feb_df,\n",
    "               index=\"Vendeur\",\n",
    "               columns = \"Produit\",\n",
    "               values=\"Code\",\n",
    "               aggfunc=freq(feb_df[\"Prix\"].count()),\n",
    "               margins=True,\n",
    "              margins_name=\"Total\"\n",
    "              )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{tabular}{lllll}\n",
      "\\toprule\n",
      "\\textbf{Produit} & Impression & Logiciel & Ordinateur &    Total \\\\\n",
      "\\textbf{Vendeur                    } &            &          &            &          \\\\\n",
      "\\midrule\n",
      "\\textbf{Barton LLC                 } &      4.63\\% &   11.11\\% &      1.85\\% &   17.59\\% \\\\\n",
      "\\textbf{Jerde-Hilpert              } &      5.56\\% &    4.63\\% &      5.56\\% &   15.74\\% \\\\\n",
      "\\textbf{Kassulke, Ondricka and Metz} &      5.56\\% &    8.33\\% &      4.63\\% &   18.52\\% \\\\\n",
      "\\textbf{Kulas Inc                  } &      5.56\\% &   13.89\\% &      2.78\\% &   22.22\\% \\\\\n",
      "\\textbf{Trantow-Barrows            } &     12.04\\% &    7.41\\% &      6.48\\% &   25.93\\% \\\\\n",
      "\\textbf{Total                      } &     33.33\\% &   45.37\\% &     21.30\\% &  100.00\\% \\\\\n",
      "\\bottomrule\n",
      "\\end{tabular}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(pd.pivot_table(feb_df,\n",
    "               index=\"Vendeur\",\n",
    "               columns = \"Produit\",\n",
    "               values=\"Code\",\n",
    "               aggfunc=freq(feb_df[\"Prix\"].count()),\n",
    "               margins=True,\n",
    "              margins_name=\"Total\"\n",
    "              )\\\n",
    "      .to_latex(\n",
    "    float_format=\"{:0.0f}\".format,\n",
    "    bold_rows=True\n",
    ")\n",
    "     )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Tableau des fréquences conditionnelles au vendeur"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11d\" ><thead>    <tr>        <th class=\"index_name level0\" >Produit</th>        <th class=\"col_heading level0 col0\" >Impression</th>        <th class=\"col_heading level0 col1\" >Logiciel</th>        <th class=\"col_heading level0 col2\" >Ordinateur</th>        <th class=\"col_heading level0 col3\" >Total</th>    </tr>    <tr>        <th class=\"index_name level0\" >Vendeur</th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11dlevel0_row0\" class=\"row_heading level0 row0\" >Barton LLC</th>\n",
       "                        <td id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11drow0_col0\" class=\"data row0 col0\" >26.32%</td>\n",
       "                        <td id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11drow0_col1\" class=\"data row0 col1\" >63.16%</td>\n",
       "                        <td id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11drow0_col2\" class=\"data row0 col2\" >10.53%</td>\n",
       "                        <td id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11drow0_col3\" class=\"data row0 col3\" >100.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11dlevel0_row1\" class=\"row_heading level0 row1\" >Jerde-Hilpert</th>\n",
       "                        <td id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11drow1_col0\" class=\"data row1 col0\" >35.29%</td>\n",
       "                        <td id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11drow1_col1\" class=\"data row1 col1\" >29.41%</td>\n",
       "                        <td id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11drow1_col2\" class=\"data row1 col2\" >35.29%</td>\n",
       "                        <td id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11drow1_col3\" class=\"data row1 col3\" >100.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11dlevel0_row2\" class=\"row_heading level0 row2\" >Kassulke, Ondricka and Metz</th>\n",
       "                        <td id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11drow2_col0\" class=\"data row2 col0\" >30.00%</td>\n",
       "                        <td id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11drow2_col1\" class=\"data row2 col1\" >45.00%</td>\n",
       "                        <td id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11drow2_col2\" class=\"data row2 col2\" >25.00%</td>\n",
       "                        <td id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11drow2_col3\" class=\"data row2 col3\" >100.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11dlevel0_row3\" class=\"row_heading level0 row3\" >Kulas Inc</th>\n",
       "                        <td id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11drow3_col0\" class=\"data row3 col0\" >25.00%</td>\n",
       "                        <td id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11drow3_col1\" class=\"data row3 col1\" >62.50%</td>\n",
       "                        <td id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11drow3_col2\" class=\"data row3 col2\" >12.50%</td>\n",
       "                        <td id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11drow3_col3\" class=\"data row3 col3\" >100.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11dlevel0_row4\" class=\"row_heading level0 row4\" >Trantow-Barrows</th>\n",
       "                        <td id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11drow4_col0\" class=\"data row4 col0\" >46.43%</td>\n",
       "                        <td id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11drow4_col1\" class=\"data row4 col1\" >28.57%</td>\n",
       "                        <td id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11drow4_col2\" class=\"data row4 col2\" >25.00%</td>\n",
       "                        <td id=\"T_83340c58_c4ac_11e9_a18a_902b34d9e11drow4_col3\" class=\"data row4 col3\" >100.00%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f0b80feb4d0>"
      ]
     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vp_df = feb_df.groupby([\"Vendeur\", \"Produit\"])[\"Code\"]\\\n",
    "            .agg(len)\\\n",
    "            .unstack()\\\n",
    "            .assign(\n",
    "                Total=lambda x: x.T.sum()\n",
    "            )\\\n",
    "            .apply(\n",
    "                lambda x: x / x.T.Total,\n",
    "                axis=1\n",
    "            )\n",
    "vp_df.style.format(\"{:.2%}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{tabular}{lrrrr}\n",
      "\\toprule\n",
      "\\textbf{Produit} &  Impression &  Logiciel &  Ordinateur &   Total \\\\\n",
      "\\textbf{Vendeur                    } &             &           &             &         \\\\\n",
      "\\midrule\n",
      "\\textbf{Barton LLC                 } &      26.32\\% &    63.16\\% &      10.53\\% & 100.00\\% \\\\\n",
      "\\textbf{Jerde-Hilpert              } &      35.29\\% &    29.41\\% &      35.29\\% & 100.00\\% \\\\\n",
      "\\textbf{Kassulke, Ondricka and Metz} &      30.00\\% &    45.00\\% &      25.00\\% & 100.00\\% \\\\\n",
      "\\textbf{Kulas Inc                  } &      25.00\\% &    62.50\\% &      12.50\\% & 100.00\\% \\\\\n",
      "\\textbf{Trantow-Barrows            } &      46.43\\% &    28.57\\% &      25.00\\% & 100.00\\% \\\\\n",
      "\\bottomrule\n",
      "\\end{tabular}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(vp_df.to_latex(\n",
    "    float_format=\"{:.2%}\".format,\n",
    "    bold_rows=True\n",
    "))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Tableau des fréquences conditionnelles au produit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11d\" ><thead>    <tr>        <th class=\"index_name level0\" >Produit</th>        <th class=\"col_heading level0 col0\" >Impression</th>        <th class=\"col_heading level0 col1\" >Logiciel</th>        <th class=\"col_heading level0 col2\" >Ordinateur</th>    </tr>    <tr>        <th class=\"index_name level0\" >Vendeur</th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11dlevel0_row0\" class=\"row_heading level0 row0\" >Barton LLC</th>\n",
       "                        <td id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11drow0_col0\" class=\"data row0 col0\" >13.89%</td>\n",
       "                        <td id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11drow0_col1\" class=\"data row0 col1\" >24.49%</td>\n",
       "                        <td id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11drow0_col2\" class=\"data row0 col2\" >8.70%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11dlevel0_row1\" class=\"row_heading level0 row1\" >Jerde-Hilpert</th>\n",
       "                        <td id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11drow1_col0\" class=\"data row1 col0\" >16.67%</td>\n",
       "                        <td id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11drow1_col1\" class=\"data row1 col1\" >10.20%</td>\n",
       "                        <td id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11drow1_col2\" class=\"data row1 col2\" >26.09%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11dlevel0_row2\" class=\"row_heading level0 row2\" >Kassulke, Ondricka and Metz</th>\n",
       "                        <td id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11drow2_col0\" class=\"data row2 col0\" >16.67%</td>\n",
       "                        <td id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11drow2_col1\" class=\"data row2 col1\" >18.37%</td>\n",
       "                        <td id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11drow2_col2\" class=\"data row2 col2\" >21.74%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11dlevel0_row3\" class=\"row_heading level0 row3\" >Kulas Inc</th>\n",
       "                        <td id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11drow3_col0\" class=\"data row3 col0\" >16.67%</td>\n",
       "                        <td id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11drow3_col1\" class=\"data row3 col1\" >30.61%</td>\n",
       "                        <td id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11drow3_col2\" class=\"data row3 col2\" >13.04%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11dlevel0_row4\" class=\"row_heading level0 row4\" >Trantow-Barrows</th>\n",
       "                        <td id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11drow4_col0\" class=\"data row4 col0\" >36.11%</td>\n",
       "                        <td id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11drow4_col1\" class=\"data row4 col1\" >16.33%</td>\n",
       "                        <td id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11drow4_col2\" class=\"data row4 col2\" >30.43%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11dlevel0_row5\" class=\"row_heading level0 row5\" >Total</th>\n",
       "                        <td id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11drow5_col0\" class=\"data row5 col0\" >100.00%</td>\n",
       "                        <td id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11drow5_col1\" class=\"data row5 col1\" >100.00%</td>\n",
       "                        <td id=\"T_8a002ec2_c4ac_11e9_a18a_902b34d9e11drow5_col2\" class=\"data row5 col2\" >100.00%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f0b80ff8bd0>"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vp_df = feb_df.groupby([\"Produit\", \"Vendeur\"])[\"Code\"]\\\n",
    "            .agg(len)\\\n",
    "            .unstack()\\\n",
    "            .assign(\n",
    "                Total=lambda x: x.T.sum()\n",
    "            )\\\n",
    "            .apply(\n",
    "                lambda x: x / x.T.Total,\n",
    "                axis=1\n",
    "            )\n",
    "vp_df.T.style.format(\"{:.2%}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{tabular}{lrrr}\n",
      "\\toprule\n",
      "\\textbf{Produit} &  Impression &  Logiciel &  Ordinateur \\\\\n",
      "\\textbf{Vendeur                    } &             &           &             \\\\\n",
      "\\midrule\n",
      "\\textbf{Barton LLC                 } &      13.89\\% &    24.49\\% &       8.70\\% \\\\\n",
      "\\textbf{Jerde-Hilpert              } &      16.67\\% &    10.20\\% &      26.09\\% \\\\\n",
      "\\textbf{Kassulke, Ondricka and Metz} &      16.67\\% &    18.37\\% &      21.74\\% \\\\\n",
      "\\textbf{Kulas Inc                  } &      16.67\\% &    30.61\\% &      13.04\\% \\\\\n",
      "\\textbf{Trantow-Barrows            } &      36.11\\% &    16.33\\% &      30.43\\% \\\\\n",
      "\\textbf{Total                      } &     100.00\\% &   100.00\\% &     100.00\\% \\\\\n",
      "\\bottomrule\n",
      "\\end{tabular}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(vp_df.T.to_latex(\n",
    "    float_format=\"{:.2%}\".format,\n",
    "    bold_rows=True\n",
    "))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ventes sur le mois de Mars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>Numero de compte</th>\n",
       "      <th>Vendeur</th>\n",
       "      <th>Code</th>\n",
       "      <th>Prix</th>\n",
       "      <th>date</th>\n",
       "      <th>Produit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>163416</td>\n",
       "      <td>Jerde-Hilpert</td>\n",
       "      <td>S1-30248</td>\n",
       "      <td>65.03</td>\n",
       "      <td>2018-03-01 16:07:40</td>\n",
       "      <td>Impression</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>527099</td>\n",
       "      <td>Jerde-Hilpert</td>\n",
       "      <td>S2-82423</td>\n",
       "      <td>76.21</td>\n",
       "      <td>2018-03-01 17:18:01</td>\n",
       "      <td>Ordinateur</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>244</th>\n",
       "      <td>527099</td>\n",
       "      <td>Jerde-Hilpert</td>\n",
       "      <td>B1-50809</td>\n",
       "      <td>70.78</td>\n",
       "      <td>2018-03-01 18:53:09</td>\n",
       "      <td>Logiciel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>737550</td>\n",
       "      <td>Trantow-Barrows</td>\n",
       "      <td>B1-50809</td>\n",
       "      <td>50.11</td>\n",
       "      <td>2018-03-01 23:47:17</td>\n",
       "      <td>Logiciel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>688981</td>\n",
       "      <td>Kassulke, Ondricka and Metz</td>\n",
       "      <td>B1-86481</td>\n",
       "      <td>97.16</td>\n",
       "      <td>2018-03-02 01:46:44</td>\n",
       "      <td>Logiciel</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Numero de compte                      Vendeur      Code   Prix  \\\n",
       "242            163416                Jerde-Hilpert  S1-30248  65.03   \n",
       "243            527099                Jerde-Hilpert  S2-82423  76.21   \n",
       "244            527099                Jerde-Hilpert  B1-50809  70.78   \n",
       "245            737550              Trantow-Barrows  B1-50809  50.11   \n",
       "246            688981  Kassulke, Ondricka and Metz  B1-86481  97.16   \n",
       "\n",
       "                   date     Produit  \n",
       "242 2018-03-01 16:07:40  Impression  \n",
       "243 2018-03-01 17:18:01  Ordinateur  \n",
       "244 2018-03-01 18:53:09    Logiciel  \n",
       "245 2018-03-01 23:47:17    Logiciel  \n",
       "246 2018-03-02 01:46:44    Logiciel  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "march_df = df.loc[(df.date < \"2018-04-01\") & (df.date >= \"2018-03-01\")]\n",
    "march_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Croisement de ventes entre vendeurs et produits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>Produit</th>\n",
       "      <th>Impression</th>\n",
       "      <th>Logiciel</th>\n",
       "      <th>Ordinateur</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vendeur</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Barton LLC</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jerde-Hilpert</th>\n",
       "      <td>9</td>\n",
       "      <td>13</td>\n",
       "      <td>9</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kassulke, Ondricka and Metz</th>\n",
       "      <td>6</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kulas Inc</th>\n",
       "      <td>13</td>\n",
       "      <td>5</td>\n",
       "      <td>13</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trantow-Barrows</th>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>6</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>46</td>\n",
       "      <td>48</td>\n",
       "      <td>48</td>\n",
       "      <td>142</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Produit                      Impression  Logiciel  Ordinateur  Total\n",
       "Vendeur                                                             \n",
       "Barton LLC                            7         7           8     22\n",
       "Jerde-Hilpert                         9        13           9     31\n",
       "Kassulke, Ondricka and Metz           6        12          12     30\n",
       "Kulas Inc                            13         5          13     31\n",
       "Trantow-Barrows                      11        11           6     28\n",
       "Total                                46        48          48    142"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(march_df,\n",
    "               index=\"Vendeur\",\n",
    "               columns = \"Produit\",\n",
    "               values=\"Code\",\n",
    "               aggfunc=\"count\",\n",
    "               margins=True,\n",
    "              margins_name=\"Total\"\n",
    "              )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{tabular}{lrrrr}\n",
      "\\toprule\n",
      "\\textbf{Produit} &  Impression &  Logiciel &  Ordinateur &  Total \\\\\n",
      "\\textbf{Vendeur                    } &             &           &             &        \\\\\n",
      "\\midrule\n",
      "\\textbf{Barton LLC                 } &           7 &         7 &           8 &     22 \\\\\n",
      "\\textbf{Jerde-Hilpert              } &           9 &        13 &           9 &     31 \\\\\n",
      "\\textbf{Kassulke, Ondricka and Metz} &           6 &        12 &          12 &     30 \\\\\n",
      "\\textbf{Kulas Inc                  } &          13 &         5 &          13 &     31 \\\\\n",
      "\\textbf{Trantow-Barrows            } &          11 &        11 &           6 &     28 \\\\\n",
      "\\textbf{Total                      } &          46 &        48 &          48 &    142 \\\\\n",
      "\\bottomrule\n",
      "\\end{tabular}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(pd.pivot_table(march_df,\n",
    "               index=\"Vendeur\",\n",
    "               columns = \"Produit\",\n",
    "               values=\"Code\",\n",
    "               aggfunc=\"count\",\n",
    "               margins=True,\n",
    "              margins_name=\"Total\"\n",
    "              )\\\n",
    "      .to_latex(\n",
    "    float_format=\"{:0.0f}\".format,\n",
    "    bold_rows=True\n",
    ")\n",
    "     )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Fréquences marginales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
   },
   "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>Produit</th>\n",
       "      <th>Impression</th>\n",
       "      <th>Logiciel</th>\n",
       "      <th>Ordinateur</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vendeur</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Barton LLC</th>\n",
       "      <td>17.07%</td>\n",
       "      <td>17.07%</td>\n",
       "      <td>19.51%</td>\n",
       "      <td>53.66%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jerde-Hilpert</th>\n",
       "      <td>21.95%</td>\n",
       "      <td>31.71%</td>\n",
       "      <td>21.95%</td>\n",
       "      <td>75.61%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kassulke, Ondricka and Metz</th>\n",
       "      <td>14.63%</td>\n",
       "      <td>29.27%</td>\n",
       "      <td>29.27%</td>\n",
       "      <td>73.17%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kulas Inc</th>\n",
       "      <td>31.71%</td>\n",
       "      <td>12.20%</td>\n",
       "      <td>31.71%</td>\n",
       "      <td>75.61%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trantow-Barrows</th>\n",
       "      <td>26.83%</td>\n",
       "      <td>26.83%</td>\n",
       "      <td>14.63%</td>\n",
       "      <td>68.29%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>112.20%</td>\n",
       "      <td>117.07%</td>\n",
       "      <td>117.07%</td>\n",
       "      <td>346.34%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Produit                     Impression Logiciel Ordinateur    Total\n",
       "Vendeur                                                            \n",
       "Barton LLC                      17.07%   17.07%     19.51%   53.66%\n",
       "Jerde-Hilpert                   21.95%   31.71%     21.95%   75.61%\n",
       "Kassulke, Ondricka and Metz     14.63%   29.27%     29.27%   73.17%\n",
       "Kulas Inc                       31.71%   12.20%     31.71%   75.61%\n",
       "Trantow-Barrows                 26.83%   26.83%     14.63%   68.29%\n",
       "Total                          112.20%  117.07%    117.07%  346.34%"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(march_df,\n",
    "               index=\"Vendeur\",\n",
    "               columns = \"Produit\",\n",
    "               values=\"Code\",\n",
    "               aggfunc=freq,\n",
    "               margins=True,\n",
    "              margins_name=\"Total\"\n",
    "              )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  Et les 2 en même temps?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>Numero de compte</th>\n",
       "      <th>Vendeur</th>\n",
       "      <th>Code</th>\n",
       "      <th>Prix</th>\n",
       "      <th>date</th>\n",
       "      <th>Produit</th>\n",
       "      <th>Mois</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>383080</td>\n",
       "      <td>Trantow-Barrows</td>\n",
       "      <td>B1-20000</td>\n",
       "      <td>33.69</td>\n",
       "      <td>2018-02-01 09:04:59</td>\n",
       "      <td>Logiciel</td>\n",
       "      <td>février</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>412290</td>\n",
       "      <td>Jerde-Hilpert</td>\n",
       "      <td>S1-27722</td>\n",
       "      <td>21.12</td>\n",
       "      <td>2018-02-01 11:51:46</td>\n",
       "      <td>Impression</td>\n",
       "      <td>février</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>412290</td>\n",
       "      <td>Jerde-Hilpert</td>\n",
       "      <td>B1-86481</td>\n",
       "      <td>35.99</td>\n",
       "      <td>2018-02-01 17:24:32</td>\n",
       "      <td>Logiciel</td>\n",
       "      <td>février</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>412290</td>\n",
       "      <td>Jerde-Hilpert</td>\n",
       "      <td>B1-20000</td>\n",
       "      <td>78.90</td>\n",
       "      <td>2018-02-01 19:56:48</td>\n",
       "      <td>Logiciel</td>\n",
       "      <td>février</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>672390</td>\n",
       "      <td>Trantow-Barrows</td>\n",
       "      <td>S1-06532</td>\n",
       "      <td>55.82</td>\n",
       "      <td>2018-02-02 03:45:20</td>\n",
       "      <td>Impression</td>\n",
       "      <td>février</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Numero de compte          Vendeur      Code   Prix                date  \\\n",
       "134            383080  Trantow-Barrows  B1-20000  33.69 2018-02-01 09:04:59   \n",
       "135            412290    Jerde-Hilpert  S1-27722  21.12 2018-02-01 11:51:46   \n",
       "136            412290    Jerde-Hilpert  B1-86481  35.99 2018-02-01 17:24:32   \n",
       "137            412290    Jerde-Hilpert  B1-20000  78.90 2018-02-01 19:56:48   \n",
       "138            672390  Trantow-Barrows  S1-06532  55.82 2018-02-02 03:45:20   \n",
       "\n",
       "        Produit     Mois  \n",
       "134    Logiciel  février  \n",
       "135  Impression  février  \n",
       "136    Logiciel  février  \n",
       "137    Logiciel  février  \n",
       "138  Impression  février  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "both_df = df.loc[(df.date < \"2018-04-01\") & (df.date >= \"2018-02-01\")].assign(\n",
    "    Mois=lambda x: x.date.dt.strftime(\"%B\")\n",
    ")\n",
    "both_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>Mois</th>\n",
       "      <th colspan=\"3\" halign=\"left\">février</th>\n",
       "      <th colspan=\"3\" halign=\"left\">mars</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Produit</th>\n",
       "      <th>Impression</th>\n",
       "      <th>Logiciel</th>\n",
       "      <th>Ordinateur</th>\n",
       "      <th>Impression</th>\n",
       "      <th>Logiciel</th>\n",
       "      <th>Ordinateur</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vendeur</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>Barton LLC</th>\n",
       "      <td>5</td>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jerde-Hilpert</th>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>13</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kassulke, Ondricka and Metz</th>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kulas Inc</th>\n",
       "      <td>6</td>\n",
       "      <td>15</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>5</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trantow-Barrows</th>\n",
       "      <td>13</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Mois                           février                           mars  \\\n",
       "Produit                     Impression Logiciel Ordinateur Impression   \n",
       "Vendeur                                                                 \n",
       "Barton LLC                           5       12          2          7   \n",
       "Jerde-Hilpert                        6        5          6          9   \n",
       "Kassulke, Ondricka and Metz          6        9          5          6   \n",
       "Kulas Inc                            6       15          3         13   \n",
       "Trantow-Barrows                     13        8          7         11   \n",
       "\n",
       "Mois                                             \n",
       "Produit                     Logiciel Ordinateur  \n",
       "Vendeur                                          \n",
       "Barton LLC                         7          8  \n",
       "Jerde-Hilpert                     13          9  \n",
       "Kassulke, Ondricka and Metz       12         12  \n",
       "Kulas Inc                          5         13  \n",
       "Trantow-Barrows                   11          6  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(both_df,\n",
    "               index=\"Vendeur\",\n",
    "               columns = [\"Mois\",\"Produit\"],\n",
    "               values=\"Code\",\n",
    "               aggfunc=\"count\",\n",
    "               #margins=True,\n",
    "               #margins_name=\"Total\"\n",
    "              )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{tabular}{lrrrrrr}\n",
      "\\toprule\n",
      "\\textbf{Mois} & \\multicolumn{3}{l}{février} & \\multicolumn{3}{l}{mars} \\\\\n",
      "\\textbf{Produit} & Impression & Logiciel & Ordinateur & Impression & Logiciel & Ordinateur \\\\\n",
      "\\textbf{Vendeur                    } &            &          &            &            &          &            \\\\\n",
      "\\midrule\n",
      "\\textbf{Barton LLC                 } &          5 &       12 &          2 &          7 &        7 &          8 \\\\\n",
      "\\textbf{Jerde-Hilpert              } &          6 &        5 &          6 &          9 &       13 &          9 \\\\\n",
      "\\textbf{Kassulke, Ondricka and Metz} &          6 &        9 &          5 &          6 &       12 &         12 \\\\\n",
      "\\textbf{Kulas Inc                  } &          6 &       15 &          3 &         13 &        5 &         13 \\\\\n",
      "\\textbf{Trantow-Barrows            } &         13 &        8 &          7 &         11 &       11 &          6 \\\\\n",
      "\\bottomrule\n",
      "\\end{tabular}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(pd.pivot_table(both_df,\n",
    "               index=\"Vendeur\",\n",
    "               columns = [\"Mois\",\"Produit\"],\n",
    "               values=\"Code\",\n",
    "               aggfunc=\"count\",\n",
    "               #margins=True,\n",
    "               #margins_name=\"Total\"\n",
    "              )\\\n",
    ".to_latex(\n",
    "    float_format=\"{:0.0f}\".format,\n",
    "    bold_rows=True\n",
    ")\n",
    "     )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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