NANA_NEMGNE_Michèle_1_Notebook_122023.ipynb

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      "source": [
        "\n",
        "# PROJET 5 : Optimisez la gestion des données d'une boutique avec R ou Python"
      ],
      "metadata": {
        "id": "rzT14f4XjbTM"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 1.Importation des librairies et des fichiers de données\n",
        "\n"
      ],
      "metadata": {
        "id": "sot-OHLRkbT7"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 1.1 Importation des librairies"
      ],
      "metadata": {
        "id": "ifGt_6himAeC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sb"
      ],
      "metadata": {
        "id": "Ki3R7afonOAy"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 1.2 Importation des fichiers de données"
      ],
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        "id": "D-VFFxgwltaD"
      }
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              "   product_id  onsale_web  price  stock_quantity stock_status\n",
              "0        3847           1   24.2               0   outofstock\n",
              "1        3849           1   34.3               0   outofstock\n",
              "2        3850           1   20.8               0   outofstock\n",
              "3        4032           1   14.1               0   outofstock\n",
              "4        4039           1   46.0               0   outofstock"
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      ],
      "source": [
        "# df erp\n",
        "\n",
        "erp = pd.read_excel('Fichier_erp.xlsx')\n",
        "erp.head()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# df web\n",
        "\n",
        "web = pd.read_excel('Fichier_web.xlsx')\n",
        "web.head()"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 516
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        "id": "DsrHBVxSkTvl",
        "outputId": "ddc12af8-2c85-459f-c1d1-033808a7e23f"
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            "text/plain": [
              "     sku  virtual  downloadable  rating_count  average_rating  total_sales  \\\n",
              "0  16004        0             0             0             0.0          5.0   \n",
              "1    NaN        0             0             0             NaN          NaN   \n",
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              "\n",
              "  tax_status  tax_class  post_author           post_date  ...  \\\n",
              "0        NaN        NaN          2.0 2018-06-07 16:27:25  ...   \n",
              "1        NaN        NaN          NaN                 NaT  ...   \n",
              "2    taxable        NaN          2.0 2018-02-14 15:39:43  ...   \n",
              "3    taxable        NaN          2.0 2018-02-14 17:15:31  ...   \n",
              "4        NaN        NaN          2.0 2020-01-25 14:08:16  ...   \n",
              "\n",
              "                                           post_name       post_modified  \\\n",
              "0                    chateau-du-couvent-pomerol-2017 2020-08-25 18:35:02   \n",
              "1                                                NaN                 NaT   \n",
              "2                  pares-balta-penedes-indigena-2017 2020-08-20 15:35:02   \n",
              "3                     maurel-cabardes-tradition-2017 2020-08-05 18:05:03   \n",
              "4  domaine-de-la-monardiere-vacqueyras-les-vieill... 2020-08-21 11:35:02   \n",
              "\n",
              "    post_modified_gmt post_content_filtered post_parent  \\\n",
              "0 2020-08-25 16:35:02                   NaN         0.0   \n",
              "1                 NaT                   NaN         NaN   \n",
              "2 2020-08-20 13:35:02                   NaN         0.0   \n",
              "3 2020-08-05 16:05:03                   NaN         0.0   \n",
              "4 2020-08-21 09:35:02                   NaN         0.0   \n",
              "\n",
              "                                                guid menu_order   post_type  \\\n",
              "0  https://www.bottle-neck.fr/wp-content/uploads/...        0.0  attachment   \n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>taxable</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2018-02-14 15:39:43</td>\n",
              "      <td>...</td>\n",
              "      <td>pares-balta-penedes-indigena-2017</td>\n",
              "      <td>2020-08-20 15:35:02</td>\n",
              "      <td>2020-08-20 13:35:02</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/?post_type=product&amp;...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>product</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>16209</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>taxable</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2018-02-14 17:15:31</td>\n",
              "      <td>...</td>\n",
              "      <td>maurel-cabardes-tradition-2017</td>\n",
              "      <td>2020-08-05 18:05:03</td>\n",
              "      <td>2020-08-05 16:05:03</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/?post_type=product&amp;...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>product</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>15763</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2020-01-25 14:08:16</td>\n",
              "      <td>...</td>\n",
              "      <td>domaine-de-la-monardiere-vacqueyras-les-vieill...</td>\n",
              "      <td>2020-08-21 11:35:02</td>\n",
              "      <td>2020-08-21 09:35:02</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/wp-content/uploads/...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>attachment</td>\n",
              "      <td>image/jpeg</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 28 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ae503288-39b7-4499-99c9-114c4bad6d85')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-ae503288-39b7-4499-99c9-114c4bad6d85 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-ae503288-39b7-4499-99c9-114c4bad6d85');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-b26273fd-1951-42f9-a9ac-e0b4de31ea4f\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-b26273fd-1951-42f9-a9ac-e0b4de31ea4f')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-b26273fd-1951-42f9-a9ac-e0b4de31ea4f button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# df liaison\n",
        "\n",
        "liaison = pd.read_excel('fichier_liaison.xlsx')\n",
        "liaison.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 241
        },
        "id": "vjwpkcMYnzfa",
        "outputId": "8e4d33da-72a4-48fa-b539-9b8372a859e9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/openpyxl/worksheet/_reader.py:329: UserWarning: Unknown extension is not supported and will be removed\n",
            "  warn(msg)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   product_id id_web\n",
              "0        3847  15298\n",
              "1        3849  15296\n",
              "2        3850  15300\n",
              "3        4032  19814\n",
              "4        4039  19815"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-bab1399f-b3e2-4ad4-8faf-f04906e91f63\" class=\"colab-df-container\">\n",
              "    <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>product_id</th>\n",
              "      <th>id_web</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3847</td>\n",
              "      <td>15298</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3849</td>\n",
              "      <td>15296</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3850</td>\n",
              "      <td>15300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4032</td>\n",
              "      <td>19814</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4039</td>\n",
              "      <td>19815</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-bab1399f-b3e2-4ad4-8faf-f04906e91f63')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-bab1399f-b3e2-4ad4-8faf-f04906e91f63 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-bab1399f-b3e2-4ad4-8faf-f04906e91f63');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-f9a1753f-b74a-4d6e-bca3-6db0ecab50f2\">\n",
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              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-f9a1753f-b74a-4d6e-bca3-6db0ecab50f2 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 2.Analyse exploratoire des fichiers de données"
      ],
      "metadata": {
        "id": "zjZV00knk8GE"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 2.1 Fichier erp"
      ],
      "metadata": {
        "id": "3nIbb--pm4Eq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Taille du df\n",
        "\n",
        "erp.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "U0D0e3Qyo_9L",
        "outputId": "c434d903-df35-40cb-e14b-848ee8e72b43"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(825, 5)"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Informations sur le df\n",
        "\n",
        "erp.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xYKZv0sfp7zT",
        "outputId": "eda0da4a-8508-4ec8-eb93-223930214381"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 825 entries, 0 to 824\n",
            "Data columns (total 5 columns):\n",
            " #   Column          Non-Null Count  Dtype  \n",
            "---  ------          --------------  -----  \n",
            " 0   product_id      825 non-null    int64  \n",
            " 1   onsale_web      825 non-null    int64  \n",
            " 2   price           825 non-null    float64\n",
            " 3   stock_quantity  825 non-null    int64  \n",
            " 4   stock_status    825 non-null    object \n",
            "dtypes: float64(1), int64(3), object(1)\n",
            "memory usage: 32.4+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Description sur le df\n",
        "\n",
        "erp.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "u-S1iarUSx9N",
        "outputId": "55cdbee1-3139-4cc8-8069-2a8fa597b77c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        product_id  onsale_web       price  stock_quantity\n",
              "count   825.000000  825.000000  825.000000      825.000000\n",
              "mean   5162.597576    0.869091   32.384000       26.583030\n",
              "std     902.644635    0.337506   26.832271       45.875948\n",
              "min    3847.000000    0.000000   -8.000000       -1.000000\n",
              "25%    4348.000000    1.000000   14.600000        1.000000\n",
              "50%    4907.000000    1.000000   24.400000       11.000000\n",
              "75%    5805.000000    1.000000   42.000000       34.000000\n",
              "max    7338.000000    1.000000  225.000000      578.000000"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-0155091a-30fa-48d8-819b-26676889720d\" class=\"colab-df-container\">\n",
              "    <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>product_id</th>\n",
              "      <th>onsale_web</th>\n",
              "      <th>price</th>\n",
              "      <th>stock_quantity</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>825.000000</td>\n",
              "      <td>825.000000</td>\n",
              "      <td>825.000000</td>\n",
              "      <td>825.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>5162.597576</td>\n",
              "      <td>0.869091</td>\n",
              "      <td>32.384000</td>\n",
              "      <td>26.583030</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>902.644635</td>\n",
              "      <td>0.337506</td>\n",
              "      <td>26.832271</td>\n",
              "      <td>45.875948</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>3847.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-8.000000</td>\n",
              "      <td>-1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>4348.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>14.600000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>4907.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>24.400000</td>\n",
              "      <td>11.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>5805.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>42.000000</td>\n",
              "      <td>34.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>7338.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>225.000000</td>\n",
              "      <td>578.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0155091a-30fa-48d8-819b-26676889720d')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-0155091a-30fa-48d8-819b-26676889720d button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-0155091a-30fa-48d8-819b-26676889720d');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-c174fc2e-4b51-4da1-bb7e-714179fb6ad9\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-c174fc2e-4b51-4da1-bb7e-714179fb6ad9')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-c174fc2e-4b51-4da1-bb7e-714179fb6ad9 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 2.2 Fichier web"
      ],
      "metadata": {
        "id": "yJv7Apw2mZuC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Taille du df\n",
        "\n",
        "web.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3Zqv74AQpHEq",
        "outputId": "beb24290-b808-433d-b1cd-01316a3d017e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1513, 28)"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Informations sur le df\n",
        "\n",
        "web.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Rqp88ZUSqQ3C",
        "outputId": "763ac725-712d-407f-8751-89507c1a6339"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 1513 entries, 0 to 1512\n",
            "Data columns (total 28 columns):\n",
            " #   Column                 Non-Null Count  Dtype         \n",
            "---  ------                 --------------  -----         \n",
            " 0   sku                    1428 non-null   object        \n",
            " 1   virtual                1513 non-null   int64         \n",
            " 2   downloadable           1513 non-null   int64         \n",
            " 3   rating_count           1513 non-null   int64         \n",
            " 4   average_rating         1430 non-null   float64       \n",
            " 5   total_sales            1430 non-null   float64       \n",
            " 6   tax_status             716 non-null    object        \n",
            " 7   tax_class              0 non-null      float64       \n",
            " 8   post_author            1430 non-null   float64       \n",
            " 9   post_date              1430 non-null   datetime64[ns]\n",
            " 10  post_date_gmt          1430 non-null   datetime64[ns]\n",
            " 11  post_content           0 non-null      float64       \n",
            " 12  post_title             1430 non-null   object        \n",
            " 13  post_excerpt           716 non-null    object        \n",
            " 14  post_status            1430 non-null   object        \n",
            " 15  comment_status         1430 non-null   object        \n",
            " 16  ping_status            1430 non-null   object        \n",
            " 17  post_password          0 non-null      float64       \n",
            " 18  post_name              1430 non-null   object        \n",
            " 19  post_modified          1430 non-null   datetime64[ns]\n",
            " 20  post_modified_gmt      1430 non-null   datetime64[ns]\n",
            " 21  post_content_filtered  0 non-null      float64       \n",
            " 22  post_parent            1430 non-null   float64       \n",
            " 23  guid                   1430 non-null   object        \n",
            " 24  menu_order             1430 non-null   float64       \n",
            " 25  post_type              1430 non-null   object        \n",
            " 26  post_mime_type         714 non-null    object        \n",
            " 27  comment_count          1430 non-null   float64       \n",
            "dtypes: datetime64[ns](4), float64(10), int64(3), object(11)\n",
            "memory usage: 331.1+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 2.3 Fichier liaison"
      ],
      "metadata": {
        "id": "JhlmBshLmnLC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Taille du df\n",
        "\n",
        "liaison.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QhvfcIYmpK2U",
        "outputId": "11f681e6-afd5-4660-c8c7-1190fb6f5b10"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(825, 2)"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Informations sur le df\n",
        "\n",
        "liaison.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4yYNSZAxqYNR",
        "outputId": "e2a37c64-061b-48d3-9ead-a3b682b64df2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 825 entries, 0 to 824\n",
            "Data columns (total 2 columns):\n",
            " #   Column      Non-Null Count  Dtype \n",
            "---  ------      --------------  ----- \n",
            " 0   product_id  825 non-null    int64 \n",
            " 1   id_web      734 non-null    object\n",
            "dtypes: int64(1), object(1)\n",
            "memory usage: 13.0+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 3.Les incohérences"
      ],
      "metadata": {
        "id": "kBwuSmsa5KF_"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 3.1 Fichier erp"
      ],
      "metadata": {
        "id": "aTSz0ICh18qo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# erp : Valeurs négatives du prix ?\n",
        "\n",
        "erp[erp['price'] < 0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "7J6qWqRea2ZM",
        "outputId": "cf8e3057-9656-4ef1-8cff-74a7508eb99a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     product_id  onsale_web  price  stock_quantity stock_status\n",
              "469        5017           0   -8.0               0   outofstock\n",
              "739        6594           0   -1.0             192      instock"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-ea5e1472-2554-4af4-9d25-aec4b4f971e5\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>product_id</th>\n",
              "      <th>onsale_web</th>\n",
              "      <th>price</th>\n",
              "      <th>stock_quantity</th>\n",
              "      <th>stock_status</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>469</th>\n",
              "      <td>5017</td>\n",
              "      <td>0</td>\n",
              "      <td>-8.0</td>\n",
              "      <td>0</td>\n",
              "      <td>outofstock</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>739</th>\n",
              "      <td>6594</td>\n",
              "      <td>0</td>\n",
              "      <td>-1.0</td>\n",
              "      <td>192</td>\n",
              "      <td>instock</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ea5e1472-2554-4af4-9d25-aec4b4f971e5')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-ea5e1472-2554-4af4-9d25-aec4b4f971e5 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-ea5e1472-2554-4af4-9d25-aec4b4f971e5');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-f05bf29d-ce44-4915-9ebd-5d5e46336658\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-f05bf29d-ce44-4915-9ebd-5d5e46336658')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-f05bf29d-ce44-4915-9ebd-5d5e46336658 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# erp : Valeurs négatives de la quantité ?\n",
        "\n",
        "erp[erp['stock_quantity'] < 0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "EHpKE7bBTdMo",
        "outputId": "050c29fe-f672-4793-8d9e-534c33661a5e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     product_id  onsale_web  price  stock_quantity stock_status\n",
              "449        4973           0   10.0              -1   outofstock\n",
              "573        5700           1   44.5              -1   outofstock"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-67f49bed-f781-497a-a48d-f3659f79ec3a\" class=\"colab-df-container\">\n",
              "    <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>product_id</th>\n",
              "      <th>onsale_web</th>\n",
              "      <th>price</th>\n",
              "      <th>stock_quantity</th>\n",
              "      <th>stock_status</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>449</th>\n",
              "      <td>4973</td>\n",
              "      <td>0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>-1</td>\n",
              "      <td>outofstock</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>573</th>\n",
              "      <td>5700</td>\n",
              "      <td>1</td>\n",
              "      <td>44.5</td>\n",
              "      <td>-1</td>\n",
              "      <td>outofstock</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-67f49bed-f781-497a-a48d-f3659f79ec3a')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-67f49bed-f781-497a-a48d-f3659f79ec3a button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-67f49bed-f781-497a-a48d-f3659f79ec3a');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-cce8e89b-f3d4-4b13-ae0b-87aee0231814\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-cce8e89b-f3d4-4b13-ae0b-87aee0231814')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-cce8e89b-f3d4-4b13-ae0b-87aee0231814 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# erp : instock alors que la quantité est zéro?\n",
        "\n",
        "erp.loc[(erp['stock_quantity'] == 0) & (erp['stock_status'] == 'instock')]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81
        },
        "id": "YPa9UIZPCU83",
        "outputId": "be8badf9-a648-4526-df7d-416598557f0e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     product_id  onsale_web  price  stock_quantity stock_status\n",
              "443        4954           1   25.0               0      instock"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-ffaef62c-ffe8-4ba6-8bad-a78a1b38fead\" class=\"colab-df-container\">\n",
              "    <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>product_id</th>\n",
              "      <th>onsale_web</th>\n",
              "      <th>price</th>\n",
              "      <th>stock_quantity</th>\n",
              "      <th>stock_status</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>443</th>\n",
              "      <td>4954</td>\n",
              "      <td>1</td>\n",
              "      <td>25.0</td>\n",
              "      <td>0</td>\n",
              "      <td>instock</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ffaef62c-ffe8-4ba6-8bad-a78a1b38fead')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-ffaef62c-ffe8-4ba6-8bad-a78a1b38fead button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-ffaef62c-ffe8-4ba6-8bad-a78a1b38fead');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 3.2 Fichier web\n"
      ],
      "metadata": {
        "id": "ZESQh4-D2Clo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# web : Lignes de 'id_web'qui sont des varchars\n",
        "\n",
        "web.loc[(web['sku'].str.isnumeric() == False)]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 467
        },
        "id": "-OjIIn4bBpFZ",
        "outputId": "bdc8a3a5-903b-4cab-c1de-f57c08b714fd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                     sku  virtual  downloadable  rating_count  average_rating  \\\n",
              "196  bon-cadeau-25-euros        0             0             0             0.0   \n",
              "382  bon-cadeau-25-euros        0             0             0             0.0   \n",
              "490              13127-1        0             0             0             0.0   \n",
              "503              13127-1        0             0             0             0.0   \n",
              "\n",
              "     total_sales tax_status  tax_class  post_author           post_date  ...  \\\n",
              "196         10.0    taxable        NaN          1.0 2018-06-01 13:53:46  ...   \n",
              "382         10.0        NaN        NaN          1.0 2018-06-01 13:53:46  ...   \n",
              "490          0.0        NaN        NaN          2.0 2020-06-09 15:42:04  ...   \n",
              "503          0.0    taxable        NaN          2.0 2020-06-09 15:42:04  ...   \n",
              "\n",
              "                                          post_name       post_modified  \\\n",
              "196                          bon-cadeau-de-25-euros 2018-06-01 14:13:57   \n",
              "382                          bon-cadeau-de-25-euros 2018-06-01 14:13:57   \n",
              "490  clos-du-mont-olivet-chateauneuf-du-pape-2007-2 2020-07-20 17:09:06   \n",
              "503  clos-du-mont-olivet-chateauneuf-du-pape-2007-2 2020-07-20 17:09:06   \n",
              "\n",
              "      post_modified_gmt post_content_filtered post_parent  \\\n",
              "196 2018-06-01 12:13:57                   NaN         0.0   \n",
              "382 2018-06-01 12:13:57                   NaN         0.0   \n",
              "490 2020-07-20 15:09:06                   NaN         0.0   \n",
              "503 2020-07-20 15:09:06                   NaN         0.0   \n",
              "\n",
              "                                                  guid menu_order   post_type  \\\n",
              "196  https://www.bottle-neck.fr/?post_type=product&...        0.0     product   \n",
              "382  https://www.bottle-neck.fr/wp-content/uploads/...        0.0  attachment   \n",
              "490  https://www.bottle-neck.fr/wp-content/uploads/...        0.0  attachment   \n",
              "503  https://www.bottle-neck.fr/?post_type=product&...        0.0     product   \n",
              "\n",
              "    post_mime_type comment_count  \n",
              "196            NaN           0.0  \n",
              "382     image/jpeg           0.0  \n",
              "490     image/jpeg           0.0  \n",
              "503            NaN           0.0  \n",
              "\n",
              "[4 rows x 28 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-9bf17049-4c6a-48d2-a3ab-a901edd61864\" class=\"colab-df-container\">\n",
              "    <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",
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              "\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>sku</th>\n",
              "      <th>virtual</th>\n",
              "      <th>downloadable</th>\n",
              "      <th>rating_count</th>\n",
              "      <th>average_rating</th>\n",
              "      <th>total_sales</th>\n",
              "      <th>tax_status</th>\n",
              "      <th>tax_class</th>\n",
              "      <th>post_author</th>\n",
              "      <th>post_date</th>\n",
              "      <th>...</th>\n",
              "      <th>post_name</th>\n",
              "      <th>post_modified</th>\n",
              "      <th>post_modified_gmt</th>\n",
              "      <th>post_content_filtered</th>\n",
              "      <th>post_parent</th>\n",
              "      <th>guid</th>\n",
              "      <th>menu_order</th>\n",
              "      <th>post_type</th>\n",
              "      <th>post_mime_type</th>\n",
              "      <th>comment_count</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>196</th>\n",
              "      <td>bon-cadeau-25-euros</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>taxable</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2018-06-01 13:53:46</td>\n",
              "      <td>...</td>\n",
              "      <td>bon-cadeau-de-25-euros</td>\n",
              "      <td>2018-06-01 14:13:57</td>\n",
              "      <td>2018-06-01 12:13:57</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/?post_type=product&amp;...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>product</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>382</th>\n",
              "      <td>bon-cadeau-25-euros</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2018-06-01 13:53:46</td>\n",
              "      <td>...</td>\n",
              "      <td>bon-cadeau-de-25-euros</td>\n",
              "      <td>2018-06-01 14:13:57</td>\n",
              "      <td>2018-06-01 12:13:57</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/wp-content/uploads/...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>attachment</td>\n",
              "      <td>image/jpeg</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>490</th>\n",
              "      <td>13127-1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2020-06-09 15:42:04</td>\n",
              "      <td>...</td>\n",
              "      <td>clos-du-mont-olivet-chateauneuf-du-pape-2007-2</td>\n",
              "      <td>2020-07-20 17:09:06</td>\n",
              "      <td>2020-07-20 15:09:06</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/wp-content/uploads/...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>attachment</td>\n",
              "      <td>image/jpeg</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>503</th>\n",
              "      <td>13127-1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>taxable</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2020-06-09 15:42:04</td>\n",
              "      <td>...</td>\n",
              "      <td>clos-du-mont-olivet-chateauneuf-du-pape-2007-2</td>\n",
              "      <td>2020-07-20 17:09:06</td>\n",
              "      <td>2020-07-20 15:09:06</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/?post_type=product&amp;...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>product</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>4 rows × 28 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-9bf17049-4c6a-48d2-a3ab-a901edd61864')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-9bf17049-4c6a-48d2-a3ab-a901edd61864 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-9bf17049-4c6a-48d2-a3ab-a901edd61864');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-7ddff71c-03e3-4f5a-8e6c-f959f0396f0d\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-7ddff71c-03e3-4f5a-8e6c-f959f0396f0d')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-7ddff71c-03e3-4f5a-8e6c-f959f0396f0d button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Lignes incohérentes de 'post_title'\n",
        "\n",
        "web.loc[(web['post_title']== 'Bon cadeau de 25€')]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "t8WxvgDS5HjQ",
        "outputId": "fcd21b13-d6c0-4d7f-aaf0-6dd86107da97"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                     sku  virtual  downloadable  rating_count  average_rating  \\\n",
              "196  bon-cadeau-25-euros        0             0             0             0.0   \n",
              "382  bon-cadeau-25-euros        0             0             0             0.0   \n",
              "\n",
              "     total_sales tax_status  tax_class  post_author           post_date  ...  \\\n",
              "196         10.0    taxable        NaN          1.0 2018-06-01 13:53:46  ...   \n",
              "382         10.0        NaN        NaN          1.0 2018-06-01 13:53:46  ...   \n",
              "\n",
              "                  post_name       post_modified   post_modified_gmt  \\\n",
              "196  bon-cadeau-de-25-euros 2018-06-01 14:13:57 2018-06-01 12:13:57   \n",
              "382  bon-cadeau-de-25-euros 2018-06-01 14:13:57 2018-06-01 12:13:57   \n",
              "\n",
              "    post_content_filtered post_parent  \\\n",
              "196                   NaN         0.0   \n",
              "382                   NaN         0.0   \n",
              "\n",
              "                                                  guid menu_order   post_type  \\\n",
              "196  https://www.bottle-neck.fr/?post_type=product&...        0.0     product   \n",
              "382  https://www.bottle-neck.fr/wp-content/uploads/...        0.0  attachment   \n",
              "\n",
              "    post_mime_type comment_count  \n",
              "196            NaN           0.0  \n",
              "382     image/jpeg           0.0  \n",
              "\n",
              "[2 rows x 28 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-34a1536f-a6dd-48a0-9dc9-73ae6892d151\" class=\"colab-df-container\">\n",
              "    <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>sku</th>\n",
              "      <th>virtual</th>\n",
              "      <th>downloadable</th>\n",
              "      <th>rating_count</th>\n",
              "      <th>average_rating</th>\n",
              "      <th>total_sales</th>\n",
              "      <th>tax_status</th>\n",
              "      <th>tax_class</th>\n",
              "      <th>post_author</th>\n",
              "      <th>post_date</th>\n",
              "      <th>...</th>\n",
              "      <th>post_name</th>\n",
              "      <th>post_modified</th>\n",
              "      <th>post_modified_gmt</th>\n",
              "      <th>post_content_filtered</th>\n",
              "      <th>post_parent</th>\n",
              "      <th>guid</th>\n",
              "      <th>menu_order</th>\n",
              "      <th>post_type</th>\n",
              "      <th>post_mime_type</th>\n",
              "      <th>comment_count</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>196</th>\n",
              "      <td>bon-cadeau-25-euros</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>taxable</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2018-06-01 13:53:46</td>\n",
              "      <td>...</td>\n",
              "      <td>bon-cadeau-de-25-euros</td>\n",
              "      <td>2018-06-01 14:13:57</td>\n",
              "      <td>2018-06-01 12:13:57</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/?post_type=product&amp;...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>product</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>382</th>\n",
              "      <td>bon-cadeau-25-euros</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2018-06-01 13:53:46</td>\n",
              "      <td>...</td>\n",
              "      <td>bon-cadeau-de-25-euros</td>\n",
              "      <td>2018-06-01 14:13:57</td>\n",
              "      <td>2018-06-01 12:13:57</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/wp-content/uploads/...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>attachment</td>\n",
              "      <td>image/jpeg</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2 rows × 28 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-34a1536f-a6dd-48a0-9dc9-73ae6892d151')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-34a1536f-a6dd-48a0-9dc9-73ae6892d151 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-34a1536f-a6dd-48a0-9dc9-73ae6892d151');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-136726af-c46f-458d-a9e0-d2aabd5336c2\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-136726af-c46f-458d-a9e0-d2aabd5336c2')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-136726af-c46f-458d-a9e0-d2aabd5336c2 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Lignes incohérentes de 'post_name '\n",
        "\n",
        "web.loc[(web['post_name']== 'bon-cadeau-de-25-euros')]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "aMtN9M3SIudi",
        "outputId": "58d9b18f-232b-46a0-8661-4212d6ee0b49"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                     sku  virtual  downloadable  rating_count  average_rating  \\\n",
              "196  bon-cadeau-25-euros        0             0             0             0.0   \n",
              "382  bon-cadeau-25-euros        0             0             0             0.0   \n",
              "\n",
              "     total_sales tax_status  tax_class  post_author           post_date  ...  \\\n",
              "196         10.0    taxable        NaN          1.0 2018-06-01 13:53:46  ...   \n",
              "382         10.0        NaN        NaN          1.0 2018-06-01 13:53:46  ...   \n",
              "\n",
              "                  post_name       post_modified   post_modified_gmt  \\\n",
              "196  bon-cadeau-de-25-euros 2018-06-01 14:13:57 2018-06-01 12:13:57   \n",
              "382  bon-cadeau-de-25-euros 2018-06-01 14:13:57 2018-06-01 12:13:57   \n",
              "\n",
              "    post_content_filtered post_parent  \\\n",
              "196                   NaN         0.0   \n",
              "382                   NaN         0.0   \n",
              "\n",
              "                                                  guid menu_order   post_type  \\\n",
              "196  https://www.bottle-neck.fr/?post_type=product&...        0.0     product   \n",
              "382  https://www.bottle-neck.fr/wp-content/uploads/...        0.0  attachment   \n",
              "\n",
              "    post_mime_type comment_count  \n",
              "196            NaN           0.0  \n",
              "382     image/jpeg           0.0  \n",
              "\n",
              "[2 rows x 28 columns]"
            ],
            "text/html": [
              "\n",
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              "    <div>\n",
              "<style scoped>\n",
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              "      <th>sku</th>\n",
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              "      <th>average_rating</th>\n",
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              "      <th>post_date</th>\n",
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              "      <th>post_modified</th>\n",
              "      <th>post_modified_gmt</th>\n",
              "      <th>post_content_filtered</th>\n",
              "      <th>post_parent</th>\n",
              "      <th>guid</th>\n",
              "      <th>menu_order</th>\n",
              "      <th>post_type</th>\n",
              "      <th>post_mime_type</th>\n",
              "      <th>comment_count</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>196</th>\n",
              "      <td>bon-cadeau-25-euros</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>taxable</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2018-06-01 13:53:46</td>\n",
              "      <td>...</td>\n",
              "      <td>bon-cadeau-de-25-euros</td>\n",
              "      <td>2018-06-01 14:13:57</td>\n",
              "      <td>2018-06-01 12:13:57</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/?post_type=product&amp;...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>product</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>382</th>\n",
              "      <td>bon-cadeau-25-euros</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2018-06-01 13:53:46</td>\n",
              "      <td>...</td>\n",
              "      <td>bon-cadeau-de-25-euros</td>\n",
              "      <td>2018-06-01 14:13:57</td>\n",
              "      <td>2018-06-01 12:13:57</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/wp-content/uploads/...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>attachment</td>\n",
              "      <td>image/jpeg</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2 rows × 28 columns</p>\n",
              "</div>\n",
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              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-6777e717-38ed-4a51-bd23-ba208e1b50e5 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-6777e717-38ed-4a51-bd23-ba208e1b50e5');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "    </script>\n",
              "  </div>\n",
              "\n",
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              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-feff383e-b29c-4a0a-80f6-e57b5439ac8b')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
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              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-feff383e-b29c-4a0a-80f6-e57b5439ac8b button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 4.Nettoyage des données"
      ],
      "metadata": {
        "id": "gJDlTS8gkk1U"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 4.1 df erp"
      ],
      "metadata": {
        "id": "xcFDLPp4s9ow"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Erreurs de types : vérifier si les variables ont bien été importées dans le bon type\n",
        "\n",
        "erp.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XDfRKoEapZyy",
        "outputId": "53e33414-b1d3-4125-bd94-c15668db08f4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "product_id          int64\n",
              "onsale_web          int64\n",
              "price             float64\n",
              "stock_quantity      int64\n",
              "stock_status       object\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Changement du type de 'product_id'\n",
        "\n",
        "erp['product_id'] = erp['product_id'].astype(object)"
      ],
      "metadata": {
        "id": "5zBL9AEYI5jR"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Vérification des types\n",
        "\n",
        "erp.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HG1_Gc6LNI8e",
        "outputId": "59a94ba2-8077-4db9-b5cf-b334eb4df779"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "product_id         object\n",
              "onsale_web          int64\n",
              "price             float64\n",
              "stock_quantity      int64\n",
              "stock_status       object\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Y a-t-il des lignes dupliquées ? Non puisque tout est \"False\"\n",
        "\n",
        "erp.duplicated()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "khHs1BJRp3Fq",
        "outputId": "f1fa5c68-e8e1-4b3d-b7fc-04c370b49840"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      False\n",
              "1      False\n",
              "2      False\n",
              "3      False\n",
              "4      False\n",
              "       ...  \n",
              "820    False\n",
              "821    False\n",
              "822    False\n",
              "823    False\n",
              "824    False\n",
              "Length: 825, dtype: bool"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Le nombre de valeurs manquantes : 0\n",
        "\n",
        "erp.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "T4x_Q3aXrSPL",
        "outputId": "5ffd7951-575f-4187-a8c3-cff2c199734b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "product_id        0\n",
              "onsale_web        0\n",
              "price             0\n",
              "stock_quantity    0\n",
              "stock_status      0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 4.2 df web"
      ],
      "metadata": {
        "id": "DldfQbrot5NW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Renommer la variable sku en id_web dans le df web\n",
        "\n",
        "web = web.rename(columns ={'sku':'id_web'})\n",
        "web.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 481
        },
        "id": "749eCPYmQItD",
        "outputId": "f0548d49-59e2-479e-f56a-3cfb8533460b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  id_web  virtual  downloadable  rating_count  average_rating  total_sales  \\\n",
              "0  16004        0             0             0             0.0          5.0   \n",
              "1    NaN        0             0             0             NaN          NaN   \n",
              "2  15075        0             0             0             0.0          3.0   \n",
              "3  16209        0             0             0             0.0          6.0   \n",
              "4  15763        0             0             0             0.0          1.0   \n",
              "\n",
              "  tax_status  tax_class  post_author           post_date  ...  \\\n",
              "0        NaN        NaN          2.0 2018-06-07 16:27:25  ...   \n",
              "1        NaN        NaN          NaN                 NaT  ...   \n",
              "2    taxable        NaN          2.0 2018-02-14 15:39:43  ...   \n",
              "3    taxable        NaN          2.0 2018-02-14 17:15:31  ...   \n",
              "4        NaN        NaN          2.0 2020-01-25 14:08:16  ...   \n",
              "\n",
              "                                           post_name       post_modified  \\\n",
              "0                    chateau-du-couvent-pomerol-2017 2020-08-25 18:35:02   \n",
              "1                                                NaN                 NaT   \n",
              "2                  pares-balta-penedes-indigena-2017 2020-08-20 15:35:02   \n",
              "3                     maurel-cabardes-tradition-2017 2020-08-05 18:05:03   \n",
              "4  domaine-de-la-monardiere-vacqueyras-les-vieill... 2020-08-21 11:35:02   \n",
              "\n",
              "    post_modified_gmt post_content_filtered post_parent  \\\n",
              "0 2020-08-25 16:35:02                   NaN         0.0   \n",
              "1                 NaT                   NaN         NaN   \n",
              "2 2020-08-20 13:35:02                   NaN         0.0   \n",
              "3 2020-08-05 16:05:03                   NaN         0.0   \n",
              "4 2020-08-21 09:35:02                   NaN         0.0   \n",
              "\n",
              "                                                guid menu_order   post_type  \\\n",
              "0  https://www.bottle-neck.fr/wp-content/uploads/...        0.0  attachment   \n",
              "1                                                NaN        NaN         NaN   \n",
              "2  https://www.bottle-neck.fr/?post_type=product&...        0.0     product   \n",
              "3  https://www.bottle-neck.fr/?post_type=product&...        0.0     product   \n",
              "4  https://www.bottle-neck.fr/wp-content/uploads/...        0.0  attachment   \n",
              "\n",
              "  post_mime_type comment_count  \n",
              "0     image/jpeg           0.0  \n",
              "1            NaN           NaN  \n",
              "2            NaN           0.0  \n",
              "3            NaN           0.0  \n",
              "4     image/jpeg           0.0  \n",
              "\n",
              "[5 rows x 28 columns]"
            ],
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              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id_web</th>\n",
              "      <th>virtual</th>\n",
              "      <th>downloadable</th>\n",
              "      <th>rating_count</th>\n",
              "      <th>average_rating</th>\n",
              "      <th>total_sales</th>\n",
              "      <th>tax_status</th>\n",
              "      <th>tax_class</th>\n",
              "      <th>post_author</th>\n",
              "      <th>post_date</th>\n",
              "      <th>...</th>\n",
              "      <th>post_name</th>\n",
              "      <th>post_modified</th>\n",
              "      <th>post_modified_gmt</th>\n",
              "      <th>post_content_filtered</th>\n",
              "      <th>post_parent</th>\n",
              "      <th>guid</th>\n",
              "      <th>menu_order</th>\n",
              "      <th>post_type</th>\n",
              "      <th>post_mime_type</th>\n",
              "      <th>comment_count</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>16004</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2018-06-07 16:27:25</td>\n",
              "      <td>...</td>\n",
              "      <td>chateau-du-couvent-pomerol-2017</td>\n",
              "      <td>2020-08-25 18:35:02</td>\n",
              "      <td>2020-08-25 16:35:02</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/wp-content/uploads/...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>attachment</td>\n",
              "      <td>image/jpeg</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaT</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaT</td>\n",
              "      <td>NaT</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>15075</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>taxable</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2018-02-14 15:39:43</td>\n",
              "      <td>...</td>\n",
              "      <td>pares-balta-penedes-indigena-2017</td>\n",
              "      <td>2020-08-20 15:35:02</td>\n",
              "      <td>2020-08-20 13:35:02</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/?post_type=product&amp;...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>product</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>16209</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>taxable</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2018-02-14 17:15:31</td>\n",
              "      <td>...</td>\n",
              "      <td>maurel-cabardes-tradition-2017</td>\n",
              "      <td>2020-08-05 18:05:03</td>\n",
              "      <td>2020-08-05 16:05:03</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/?post_type=product&amp;...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>product</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>15763</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2020-01-25 14:08:16</td>\n",
              "      <td>...</td>\n",
              "      <td>domaine-de-la-monardiere-vacqueyras-les-vieill...</td>\n",
              "      <td>2020-08-21 11:35:02</td>\n",
              "      <td>2020-08-21 09:35:02</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/wp-content/uploads/...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>attachment</td>\n",
              "      <td>image/jpeg</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 28 columns</p>\n",
              "</div>\n",
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              "\n",
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              "  <style>\n",
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              "      display:flex;\n",
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              "\n",
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              "      background-color: #E8F0FE;\n",
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              "      display: none;\n",
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              "      padding: 0 0 0 0;\n",
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              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
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              "      background-color: #434B5C;\n",
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              "  </style>\n",
              "\n",
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              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "        const element = document.querySelector('#df-a093a550-ac2e-46ba-8e8b-30d0256564b8');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "\n",
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              "      --disabled-fill-color: #AAA;\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "      --hover-bg-color: #434B5C;\n",
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              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-8202be84-8901-4cd2-8c8f-1ed04cb8feaa button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
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              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Les types de données dans chaque variable du df semblent corrects, même les dates\n",
        "\n",
        "web.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "l-SYi5uhpnEt",
        "outputId": "52a53990-3ac7-482a-91e8-9b75a951dfbb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id_web                           object\n",
              "virtual                           int64\n",
              "downloadable                      int64\n",
              "rating_count                      int64\n",
              "average_rating                  float64\n",
              "total_sales                     float64\n",
              "tax_status                       object\n",
              "tax_class                       float64\n",
              "post_author                     float64\n",
              "post_date                datetime64[ns]\n",
              "post_date_gmt            datetime64[ns]\n",
              "post_content                    float64\n",
              "post_title                       object\n",
              "post_excerpt                     object\n",
              "post_status                      object\n",
              "comment_status                   object\n",
              "ping_status                      object\n",
              "post_password                   float64\n",
              "post_name                        object\n",
              "post_modified            datetime64[ns]\n",
              "post_modified_gmt        datetime64[ns]\n",
              "post_content_filtered           float64\n",
              "post_parent                     float64\n",
              "guid                             object\n",
              "menu_order                      float64\n",
              "post_type                        object\n",
              "post_mime_type                   object\n",
              "comment_count                   float64\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Données dupliquées ? Non\n",
        "\n",
        "web.duplicated()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3kpDy8rKxm2n",
        "outputId": "b1876538-e7f1-4a3c-f21f-7bf4f22c67a2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0       False\n",
              "1       False\n",
              "2       False\n",
              "3       False\n",
              "4       False\n",
              "        ...  \n",
              "1508    False\n",
              "1509    False\n",
              "1510    False\n",
              "1511    False\n",
              "1512    False\n",
              "Length: 1513, dtype: bool"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Présence des valeurs manquantes ? Oui\n",
        "\n",
        "web.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wahrMI1Zql8i",
        "outputId": "a0430bf5-060d-42d0-e556-5b7af451dc46"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id_web                     85\n",
              "virtual                     0\n",
              "downloadable                0\n",
              "rating_count                0\n",
              "average_rating             83\n",
              "total_sales                83\n",
              "tax_status                797\n",
              "tax_class                1513\n",
              "post_author                83\n",
              "post_date                  83\n",
              "post_date_gmt              83\n",
              "post_content             1513\n",
              "post_title                 83\n",
              "post_excerpt              797\n",
              "post_status                83\n",
              "comment_status             83\n",
              "ping_status                83\n",
              "post_password            1513\n",
              "post_name                  83\n",
              "post_modified              83\n",
              "post_modified_gmt          83\n",
              "post_content_filtered    1513\n",
              "post_parent                83\n",
              "guid                       83\n",
              "menu_order                 83\n",
              "post_type                  83\n",
              "post_mime_type            799\n",
              "comment_count              83\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Echantillon du df web sans les valeurs manquantes de la colonne 'id_web'\n",
        "\n",
        "Web_not_null = web[web['id_web'].notnull()]\n",
        "Web_not_null.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 550
        },
        "id": "D0RVjC3q1PnM",
        "outputId": "e9731bdf-8a2a-4ed8-b49b-1e9642a20c5f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  id_web  virtual  downloadable  rating_count  average_rating  total_sales  \\\n",
              "0  16004        0             0             0             0.0          5.0   \n",
              "2  15075        0             0             0             0.0          3.0   \n",
              "3  16209        0             0             0             0.0          6.0   \n",
              "4  15763        0             0             0             0.0          1.0   \n",
              "5  13895        0             0             0             0.0          0.0   \n",
              "\n",
              "  tax_status  tax_class  post_author           post_date  ...  \\\n",
              "0        NaN        NaN          2.0 2018-06-07 16:27:25  ...   \n",
              "2    taxable        NaN          2.0 2018-02-14 15:39:43  ...   \n",
              "3    taxable        NaN          2.0 2018-02-14 17:15:31  ...   \n",
              "4        NaN        NaN          2.0 2020-01-25 14:08:16  ...   \n",
              "5    taxable        NaN          2.0 2019-03-19 10:41:50  ...   \n",
              "\n",
              "                                           post_name       post_modified  \\\n",
              "0                    chateau-du-couvent-pomerol-2017 2020-08-25 18:35:02   \n",
              "2                  pares-balta-penedes-indigena-2017 2020-08-20 15:35:02   \n",
              "3                     maurel-cabardes-tradition-2017 2020-08-05 18:05:03   \n",
              "4  domaine-de-la-monardiere-vacqueyras-les-vieill... 2020-08-21 11:35:02   \n",
              "5         chateau-saransot-dupre-bordeaux-blanc-2016 2020-04-25 21:11:40   \n",
              "\n",
              "    post_modified_gmt post_content_filtered post_parent  \\\n",
              "0 2020-08-25 16:35:02                   NaN         0.0   \n",
              "2 2020-08-20 13:35:02                   NaN         0.0   \n",
              "3 2020-08-05 16:05:03                   NaN         0.0   \n",
              "4 2020-08-21 09:35:02                   NaN         0.0   \n",
              "5 2020-04-25 19:11:40                   NaN         0.0   \n",
              "\n",
              "                                                guid menu_order   post_type  \\\n",
              "0  https://www.bottle-neck.fr/wp-content/uploads/...        0.0  attachment   \n",
              "2  https://www.bottle-neck.fr/?post_type=product&...        0.0     product   \n",
              "3  https://www.bottle-neck.fr/?post_type=product&...        0.0     product   \n",
              "4  https://www.bottle-neck.fr/wp-content/uploads/...        0.0  attachment   \n",
              "5  https://www.bottle-neck.fr/?post_type=product&...        0.0     product   \n",
              "\n",
              "  post_mime_type comment_count  \n",
              "0     image/jpeg           0.0  \n",
              "2            NaN           0.0  \n",
              "3            NaN           0.0  \n",
              "4     image/jpeg           0.0  \n",
              "5            NaN           0.0  \n",
              "\n",
              "[5 rows x 28 columns]"
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              "      <th></th>\n",
              "      <th>id_web</th>\n",
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              "      <th>0</th>\n",
              "      <td>16004</td>\n",
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              "      <td>5.0</td>\n",
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              "      <td>2.0</td>\n",
              "      <td>2018-06-07 16:27:25</td>\n",
              "      <td>...</td>\n",
              "      <td>chateau-du-couvent-pomerol-2017</td>\n",
              "      <td>2020-08-25 18:35:02</td>\n",
              "      <td>2020-08-25 16:35:02</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/wp-content/uploads/...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>attachment</td>\n",
              "      <td>image/jpeg</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>15075</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>taxable</td>\n",
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              "      <td>2.0</td>\n",
              "      <td>2018-02-14 15:39:43</td>\n",
              "      <td>...</td>\n",
              "      <td>pares-balta-penedes-indigena-2017</td>\n",
              "      <td>2020-08-20 15:35:02</td>\n",
              "      <td>2020-08-20 13:35:02</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/?post_type=product&amp;...</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>16209</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>taxable</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2018-02-14 17:15:31</td>\n",
              "      <td>...</td>\n",
              "      <td>maurel-cabardes-tradition-2017</td>\n",
              "      <td>2020-08-05 18:05:03</td>\n",
              "      <td>2020-08-05 16:05:03</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/?post_type=product&amp;...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>product</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>15763</td>\n",
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              "      <td>1.0</td>\n",
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              "      <td>2.0</td>\n",
              "      <td>2020-01-25 14:08:16</td>\n",
              "      <td>...</td>\n",
              "      <td>domaine-de-la-monardiere-vacqueyras-les-vieill...</td>\n",
              "      <td>2020-08-21 11:35:02</td>\n",
              "      <td>2020-08-21 09:35:02</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/wp-content/uploads/...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>attachment</td>\n",
              "      <td>image/jpeg</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>13895</td>\n",
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              "      <td>2019-03-19 10:41:50</td>\n",
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              "      <td>chateau-saransot-dupre-bordeaux-blanc-2016</td>\n",
              "      <td>2020-04-25 21:11:40</td>\n",
              "      <td>2020-04-25 19:11:40</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/?post_type=product&amp;...</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 28 columns</p>\n",
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              "\n",
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              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-728253e2-078e-4f0b-b719-deda4722d028');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "          + ' to learn more about interactive tables.';\n",
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              "\n",
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              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "\n",
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              "\n",
              "  .colab-df-spinner {\n",
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              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
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              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "    (() => {\n",
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              "        document.querySelector('#df-91b03c8a-ed7d-43b7-b582-11bdb1a74860 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#  Les infos du df, particulièrement pour la variable 'id_web'\n",
        "\n",
        "Web_not_null.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R4c5RMUa21uk",
        "outputId": "40b3331b-1bd3-4f22-c0c2-9922c67a7a50"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 1428 entries, 0 to 1512\n",
            "Data columns (total 28 columns):\n",
            " #   Column                 Non-Null Count  Dtype         \n",
            "---  ------                 --------------  -----         \n",
            " 0   id_web                 1428 non-null   object        \n",
            " 1   virtual                1428 non-null   int64         \n",
            " 2   downloadable           1428 non-null   int64         \n",
            " 3   rating_count           1428 non-null   int64         \n",
            " 4   average_rating         1428 non-null   float64       \n",
            " 5   total_sales            1428 non-null   float64       \n",
            " 6   tax_status             714 non-null    object        \n",
            " 7   tax_class              0 non-null      float64       \n",
            " 8   post_author            1428 non-null   float64       \n",
            " 9   post_date              1428 non-null   datetime64[ns]\n",
            " 10  post_date_gmt          1428 non-null   datetime64[ns]\n",
            " 11  post_content           0 non-null      float64       \n",
            " 12  post_title             1428 non-null   object        \n",
            " 13  post_excerpt           714 non-null    object        \n",
            " 14  post_status            1428 non-null   object        \n",
            " 15  comment_status         1428 non-null   object        \n",
            " 16  ping_status            1428 non-null   object        \n",
            " 17  post_password          0 non-null      float64       \n",
            " 18  post_name              1428 non-null   object        \n",
            " 19  post_modified          1428 non-null   datetime64[ns]\n",
            " 20  post_modified_gmt      1428 non-null   datetime64[ns]\n",
            " 21  post_content_filtered  0 non-null      float64       \n",
            " 22  post_parent            1428 non-null   float64       \n",
            " 23  guid                   1428 non-null   object        \n",
            " 24  menu_order             1428 non-null   float64       \n",
            " 25  post_type              1428 non-null   object        \n",
            " 26  post_mime_type         714 non-null    object        \n",
            " 27  comment_count          1428 non-null   float64       \n",
            "dtypes: datetime64[ns](4), float64(10), int64(3), object(11)\n",
            "memory usage: 323.5+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 4.3 df liaison\n"
      ],
      "metadata": {
        "id": "dLm5n4ynuVa3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Les types de données dans chaque variable du df semblent corrects\n",
        "\n",
        "liaison.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nUt0ZkYdptV5",
        "outputId": "c9c79171-7923-4235-8ec3-769d3c770b4e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "product_id     int64\n",
              "id_web        object\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Données dupliquées ? Non\n",
        "\n",
        "liaison.duplicated()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "v1JmcIzEuRrw",
        "outputId": "431b0f61-ad8d-4566-c093-c2e228f67226"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      False\n",
              "1      False\n",
              "2      False\n",
              "3      False\n",
              "4      False\n",
              "       ...  \n",
              "820    False\n",
              "821    False\n",
              "822    False\n",
              "823    False\n",
              "824    False\n",
              "Length: 825, dtype: bool"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Le nombre de valeurs manquantes ?\n",
        "\n",
        "liaison.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "slB9k0rorFgG",
        "outputId": "7b2eeb7d-0918-4cce-ddbf-8a2a47721357"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "product_id     0\n",
              "id_web        91\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 5.Définition de la clé pour la jointure et jointure"
      ],
      "metadata": {
        "id": "ZM8OI4vJtXW4"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "## 5.1 Recherche des clés primaires"
      ],
      "metadata": {
        "id": "_1uVBrYVCi7M"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Création de la fonction pour la clé primaire\n",
        "\n",
        "def pri_key(df):\n",
        "    print('Le nombre de lignes du df =',df.shape[0])\n",
        "    for i in df.columns:\n",
        "        print(\"Le nombre valeur unique\", i,\":\", df.drop_duplicates([i]).shape[0])\n",
        "\n",
        "    a=0\n",
        "    for i in df.columns:\n",
        "\n",
        "        if df.shape[0] == df.drop_duplicates([i]).shape[0]:\n",
        "            print(\"Le valeur \", i,\":\",\"peut être defini comme primary key\")\n",
        "            a +=1\n",
        "\n",
        "    if a== 0:\n",
        "        print(\"Oopps!. Vérifiez le dataframe\" )"
      ],
      "metadata": {
        "id": "j_H9c6n3Bc-W"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# df erp\n",
        "\n",
        "pri_key(erp)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZbwpzGIK9kvi",
        "outputId": "3f1155f7-8955-41f2-9963-a33b11de6328"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Le nombre de lignes du df = 825\n",
            "Le nombre valeur unique product_id : 825\n",
            "Le nombre valeur unique onsale_web : 2\n",
            "Le nombre valeur unique price : 382\n",
            "Le nombre valeur unique stock_quantity : 129\n",
            "Le nombre valeur unique stock_status : 2\n",
            "Le valeur  product_id : peut être defini comme primary key\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "product_id peut être défini comme primary key donc UNICITE"
      ],
      "metadata": {
        "id": "SqASXpvJ7SEn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# df Web_not_null\n",
        "\n",
        "pri_key(Web_not_null)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "T8vW0dypBjUm",
        "outputId": "12964846-c7a0-4d64-bf01-17116bcdf362"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Le nombre de lignes du df = 1428\n",
            "Le nombre valeur unique id_web : 714\n",
            "Le nombre valeur unique virtual : 1\n",
            "Le nombre valeur unique downloadable : 1\n",
            "Le nombre valeur unique rating_count : 1\n",
            "Le nombre valeur unique average_rating : 1\n",
            "Le nombre valeur unique total_sales : 41\n",
            "Le nombre valeur unique tax_status : 2\n",
            "Le nombre valeur unique tax_class : 1\n",
            "Le nombre valeur unique post_author : 2\n",
            "Le nombre valeur unique post_date : 714\n",
            "Le nombre valeur unique post_date_gmt : 714\n",
            "Le nombre valeur unique post_content : 1\n",
            "Le nombre valeur unique post_title : 711\n",
            "Le nombre valeur unique post_excerpt : 678\n",
            "Le nombre valeur unique post_status : 1\n",
            "Le nombre valeur unique comment_status : 1\n",
            "Le nombre valeur unique ping_status : 1\n",
            "Le nombre valeur unique post_password : 1\n",
            "Le nombre valeur unique post_name : 714\n",
            "Le nombre valeur unique post_modified : 587\n",
            "Le nombre valeur unique post_modified_gmt : 587\n",
            "Le nombre valeur unique post_content_filtered : 1\n",
            "Le nombre valeur unique post_parent : 1\n",
            "Le nombre valeur unique guid : 1428\n",
            "Le nombre valeur unique menu_order : 1\n",
            "Le nombre valeur unique post_type : 2\n",
            "Le nombre valeur unique post_mime_type : 2\n",
            "Le nombre valeur unique comment_count : 1\n",
            "Le valeur  guid : peut être defini comme primary key\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "id_web ne peut pas être défini comme clé primaire, car elle est présente plusieurs fois dans le df"
      ],
      "metadata": {
        "id": "f7G5XN6U6YzO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Filtrage des produits dans 'post_type' car il ya aussi les pièces jointes (Attachment)\n",
        "\n",
        "produit = Web_not_null[Web_not_null['post_type'] == 'product']\n",
        "produit.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VrCTCXiQ350M",
        "outputId": "de2d167d-bdab-48fd-ee2e-16d888cd2d27"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 714 entries, 2 to 1510\n",
            "Data columns (total 28 columns):\n",
            " #   Column                 Non-Null Count  Dtype         \n",
            "---  ------                 --------------  -----         \n",
            " 0   id_web                 714 non-null    object        \n",
            " 1   virtual                714 non-null    int64         \n",
            " 2   downloadable           714 non-null    int64         \n",
            " 3   rating_count           714 non-null    int64         \n",
            " 4   average_rating         714 non-null    float64       \n",
            " 5   total_sales            714 non-null    float64       \n",
            " 6   tax_status             714 non-null    object        \n",
            " 7   tax_class              0 non-null      float64       \n",
            " 8   post_author            714 non-null    float64       \n",
            " 9   post_date              714 non-null    datetime64[ns]\n",
            " 10  post_date_gmt          714 non-null    datetime64[ns]\n",
            " 11  post_content           0 non-null      float64       \n",
            " 12  post_title             714 non-null    object        \n",
            " 13  post_excerpt           714 non-null    object        \n",
            " 14  post_status            714 non-null    object        \n",
            " 15  comment_status         714 non-null    object        \n",
            " 16  ping_status            714 non-null    object        \n",
            " 17  post_password          0 non-null      float64       \n",
            " 18  post_name              714 non-null    object        \n",
            " 19  post_modified          714 non-null    datetime64[ns]\n",
            " 20  post_modified_gmt      714 non-null    datetime64[ns]\n",
            " 21  post_content_filtered  0 non-null      float64       \n",
            " 22  post_parent            714 non-null    float64       \n",
            " 23  guid                   714 non-null    object        \n",
            " 24  menu_order             714 non-null    float64       \n",
            " 25  post_type              714 non-null    object        \n",
            " 26  post_mime_type         0 non-null      object        \n",
            " 27  comment_count          714 non-null    float64       \n",
            "dtypes: datetime64[ns](4), float64(10), int64(3), object(11)\n",
            "memory usage: 161.8+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# df produit\n",
        "\n",
        "pri_key(produit)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LGbh3fev6JsN",
        "outputId": "378f57e4-2b2c-4d61-a63a-cdbfdae2ebb6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Le nombre de lignes du df = 714\n",
            "Le nombre valeur unique id_web : 714\n",
            "Le nombre valeur unique virtual : 1\n",
            "Le nombre valeur unique downloadable : 1\n",
            "Le nombre valeur unique rating_count : 1\n",
            "Le nombre valeur unique average_rating : 1\n",
            "Le nombre valeur unique total_sales : 41\n",
            "Le nombre valeur unique tax_status : 1\n",
            "Le nombre valeur unique tax_class : 1\n",
            "Le nombre valeur unique post_author : 2\n",
            "Le nombre valeur unique post_date : 714\n",
            "Le nombre valeur unique post_date_gmt : 714\n",
            "Le nombre valeur unique post_content : 1\n",
            "Le nombre valeur unique post_title : 711\n",
            "Le nombre valeur unique post_excerpt : 677\n",
            "Le nombre valeur unique post_status : 1\n",
            "Le nombre valeur unique comment_status : 1\n",
            "Le nombre valeur unique ping_status : 1\n",
            "Le nombre valeur unique post_password : 1\n",
            "Le nombre valeur unique post_name : 714\n",
            "Le nombre valeur unique post_modified : 587\n",
            "Le nombre valeur unique post_modified_gmt : 587\n",
            "Le nombre valeur unique post_content_filtered : 1\n",
            "Le nombre valeur unique post_parent : 1\n",
            "Le nombre valeur unique guid : 714\n",
            "Le nombre valeur unique menu_order : 1\n",
            "Le nombre valeur unique post_type : 1\n",
            "Le nombre valeur unique post_mime_type : 1\n",
            "Le nombre valeur unique comment_count : 1\n",
            "Le valeur  id_web : peut être defini comme primary key\n",
            "Le valeur  post_date : peut être defini comme primary key\n",
            "Le valeur  post_date_gmt : peut être defini comme primary key\n",
            "Le valeur  post_name : peut être defini comme primary key\n",
            "Le valeur  guid : peut être defini comme primary key\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "id_web peut donc être défini comme clé primaire donc UNICITE\n",
        "\n"
      ],
      "metadata": {
        "id": "8g8rrhTp66NA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# df liaison\n",
        "\n",
        "pri_key(liaison)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2GLS0NfQBoYN",
        "outputId": "d5102105-fc60-465c-9743-ac1f47400111"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Le nombre de lignes du df = 825\n",
            "Le nombre valeur unique product_id : 825\n",
            "Le nombre valeur unique id_web : 735\n",
            "Le valeur  product_id : peut être defini comme primary key\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "product_id peut être défini comme clé primaire, donc UNICITE"
      ],
      "metadata": {
        "id": "XpRd_h0X7oco"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 5.2 Jointure des dataframes"
      ],
      "metadata": {
        "id": "u4EBx9AZCqJc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Première jointure, merge permet de vérifier la qualité de la jointure, et tester\n",
        "\n",
        "erp_liaison = pd.merge(erp, liaison, on = 'product_id')\n",
        "erp_liaison"
      ],
      "metadata": {
        "id": "GbC9qFcgCyjW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "outputId": "5afbe80c-af24-4866-e0ba-b481934cfa34"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    product_id  onsale_web  price  stock_quantity stock_status   id_web\n",
              "0         3847           1   24.2               0   outofstock    15298\n",
              "1         3849           1   34.3               0   outofstock    15296\n",
              "2         3850           1   20.8               0   outofstock    15300\n",
              "3         4032           1   14.1               0   outofstock    19814\n",
              "4         4039           1   46.0               0   outofstock    19815\n",
              "..         ...         ...    ...             ...          ...      ...\n",
              "820       7203           0   45.0              30      instock      NaN\n",
              "821       7204           0   45.0               9      instock      NaN\n",
              "822       7247           1   54.8              23      instock  13127-1\n",
              "823       7329           0   26.5              14      instock  14680-1\n",
              "824       7338           1   16.3              45      instock    16230\n",
              "\n",
              "[825 rows x 6 columns]"
            ],
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "      quickchartButtonEl.style.display =\n",
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              "    </div>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Jointure finale\n",
        "\n",
        "jointure = pd.merge(erp_liaison, produit, on = 'id_web', how = 'right')\n",
        "jointure.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TiMFWLgaQZ5g",
        "outputId": "cea9939d-3592-4732-b616-a1f60e0e87db"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 714 entries, 0 to 713\n",
            "Data columns (total 33 columns):\n",
            " #   Column                 Non-Null Count  Dtype         \n",
            "---  ------                 --------------  -----         \n",
            " 0   product_id             714 non-null    object        \n",
            " 1   onsale_web             714 non-null    int64         \n",
            " 2   price                  714 non-null    float64       \n",
            " 3   stock_quantity         714 non-null    int64         \n",
            " 4   stock_status           714 non-null    object        \n",
            " 5   id_web                 714 non-null    object        \n",
            " 6   virtual                714 non-null    int64         \n",
            " 7   downloadable           714 non-null    int64         \n",
            " 8   rating_count           714 non-null    int64         \n",
            " 9   average_rating         714 non-null    float64       \n",
            " 10  total_sales            714 non-null    float64       \n",
            " 11  tax_status             714 non-null    object        \n",
            " 12  tax_class              0 non-null      float64       \n",
            " 13  post_author            714 non-null    float64       \n",
            " 14  post_date              714 non-null    datetime64[ns]\n",
            " 15  post_date_gmt          714 non-null    datetime64[ns]\n",
            " 16  post_content           0 non-null      float64       \n",
            " 17  post_title             714 non-null    object        \n",
            " 18  post_excerpt           714 non-null    object        \n",
            " 19  post_status            714 non-null    object        \n",
            " 20  comment_status         714 non-null    object        \n",
            " 21  ping_status            714 non-null    object        \n",
            " 22  post_password          0 non-null      float64       \n",
            " 23  post_name              714 non-null    object        \n",
            " 24  post_modified          714 non-null    datetime64[ns]\n",
            " 25  post_modified_gmt      714 non-null    datetime64[ns]\n",
            " 26  post_content_filtered  0 non-null      float64       \n",
            " 27  post_parent            714 non-null    float64       \n",
            " 28  guid                   714 non-null    object        \n",
            " 29  menu_order             714 non-null    float64       \n",
            " 30  post_type              714 non-null    object        \n",
            " 31  post_mime_type         0 non-null      object        \n",
            " 32  comment_count          714 non-null    float64       \n",
            "dtypes: datetime64[ns](4), float64(11), int64(5), object(13)\n",
            "memory usage: 189.7+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "jointure"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "Pq4OXUm4Yvm-",
        "outputId": "fb246f29-0fd3-4a9d-d72e-d0f9d4faa0e5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    product_id  onsale_web  price  stock_quantity stock_status id_web  \\\n",
              "0         4165           1   12.0              57      instock  15075   \n",
              "1         4174           1    5.7              94      instock  16209   \n",
              "2         5796           1   12.5              12      instock  13895   \n",
              "3         4582           1  109.6               7      instock  12857   \n",
              "4         6106           1   74.8              15      instock  14106   \n",
              "..         ...         ...    ...             ...          ...    ...   \n",
              "709       4074           1   12.7              50      instock  15941   \n",
              "710       4617           1   67.5               1      instock  10459   \n",
              "711       4062           1   11.9              60      instock  16320   \n",
              "712       4262           1   15.8              35      instock  15663   \n",
              "713       5896           1   24.7              17      instock  15910   \n",
              "\n",
              "     virtual  downloadable  rating_count  average_rating  ...  \\\n",
              "0          0             0             0             0.0  ...   \n",
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              "\n",
              "                                             post_name       post_modified  \\\n",
              "0                    pares-balta-penedes-indigena-2017 2020-08-20 15:35:02   \n",
              "1                       maurel-cabardes-tradition-2017 2020-08-05 18:05:03   \n",
              "2           chateau-saransot-dupre-bordeaux-blanc-2016 2020-04-25 21:11:40   \n",
              "3    chateau-de-puligny-montrachet-1cru-champ-canet... 2020-02-06 16:35:02   \n",
              "4                  stephane-tissot-chateau-chalon-2011 2020-05-29 17:35:03   \n",
              "..                                                 ...                 ...   \n",
              "709                         jerome-cotes-du-rhone-2018 2020-06-25 14:00:03   \n",
              "710  alphonse-mellot-sancerre-rouge-generation-xix-... 2020-08-24 14:05:02   \n",
              "711  mourgues-du-gres-costieres-de-nimes-terre-darg... 2020-08-25 11:15:03   \n",
              "712  chermette-domaine-du-vissoux-brouilly-pierreux... 2020-08-01 09:35:02   \n",
              "713     thevenet-quintaine-vire-clesse-la-bongran-2015 2020-08-14 10:45:02   \n",
              "\n",
              "      post_modified_gmt  post_content_filtered post_parent  \\\n",
              "0   2020-08-20 13:35:02                    NaN         0.0   \n",
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              "4   2020-05-29 15:35:03                    NaN         0.0   \n",
              "..                  ...                    ...         ...   \n",
              "709 2020-06-25 12:00:03                    NaN         0.0   \n",
              "710 2020-08-24 12:05:02                    NaN         0.0   \n",
              "711 2020-08-25 09:15:03                    NaN         0.0   \n",
              "712 2020-08-01 07:35:02                    NaN         0.0   \n",
              "713 2020-08-14 08:45:02                    NaN         0.0   \n",
              "\n",
              "                                                  guid  menu_order post_type  \\\n",
              "0    https://www.bottle-neck.fr/?post_type=product&...         0.0   product   \n",
              "1    https://www.bottle-neck.fr/?post_type=product&...         0.0   product   \n",
              "2    https://www.bottle-neck.fr/?post_type=product&...         0.0   product   \n",
              "3    https://www.bottle-neck.fr/?post_type=product&...         0.0   product   \n",
              "4    https://www.bottle-neck.fr/?post_type=product&...         0.0   product   \n",
              "..                                                 ...         ...       ...   \n",
              "709  https://www.bottle-neck.fr/?post_type=product&...         0.0   product   \n",
              "710  https://www.bottle-neck.fr/?post_type=product&...         0.0   product   \n",
              "711  https://www.bottle-neck.fr/?post_type=product&...         0.0   product   \n",
              "712  https://www.bottle-neck.fr/?post_type=product&...         0.0   product   \n",
              "713  https://www.bottle-neck.fr/?post_type=product&...         0.0   product   \n",
              "\n",
              "    post_mime_type comment_count  \n",
              "0              NaN           0.0  \n",
              "1              NaN           0.0  \n",
              "2              NaN           0.0  \n",
              "3              NaN           0.0  \n",
              "4              NaN           0.0  \n",
              "..             ...           ...  \n",
              "709            NaN           0.0  \n",
              "710            NaN           0.0  \n",
              "711            NaN           0.0  \n",
              "712            NaN           0.0  \n",
              "713            NaN           0.0  \n",
              "\n",
              "[714 rows x 33 columns]"
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              "      <th>710</th>\n",
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              "    <tr>\n",
              "      <th>711</th>\n",
              "      <td>4062</td>\n",
              "      <td>1</td>\n",
              "      <td>11.9</td>\n",
              "      <td>60</td>\n",
              "      <td>instock</td>\n",
              "      <td>16320</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>mourgues-du-gres-costieres-de-nimes-terre-darg...</td>\n",
              "      <td>2020-08-25 11:15:03</td>\n",
              "      <td>2020-08-25 09:15:03</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/?post_type=product&amp;...</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>712</th>\n",
              "      <td>4262</td>\n",
              "      <td>1</td>\n",
              "      <td>15.8</td>\n",
              "      <td>35</td>\n",
              "      <td>instock</td>\n",
              "      <td>15663</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>chermette-domaine-du-vissoux-brouilly-pierreux...</td>\n",
              "      <td>2020-08-01 09:35:02</td>\n",
              "      <td>2020-08-01 07:35:02</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/?post_type=product&amp;...</td>\n",
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              "      <td>product</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>713</th>\n",
              "      <td>5896</td>\n",
              "      <td>1</td>\n",
              "      <td>24.7</td>\n",
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              "      <td>instock</td>\n",
              "      <td>15910</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>thevenet-quintaine-vire-clesse-la-bongran-2015</td>\n",
              "      <td>2020-08-14 10:45:02</td>\n",
              "      <td>2020-08-14 08:45:02</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/?post_type=product&amp;...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>product</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>714 rows × 33 columns</p>\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "          + ' to learn more about interactive tables.';\n",
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              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
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              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
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              "    </div>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 6.Calcul du ca_produit et du CA total\n"
      ],
      "metadata": {
        "id": "D0K_4CDWCWE5"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 6.1 Colonne de chiffre d'affaire de chaque produit"
      ],
      "metadata": {
        "id": "CwPAAiGNCxp6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Création de la colonne 'ca_produit'\n",
        "\n",
        "jointure['ca_produit'] = jointure['price']*jointure['total_sales']\n",
        "jointure"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 790
        },
        "id": "ViNIKFmjeVOF",
        "outputId": "98d72f60-f2c7-4813-84c4-1aac14fa173f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    product_id  onsale_web  price  stock_quantity stock_status id_web  \\\n",
              "0         4165           1   12.0              57      instock  15075   \n",
              "1         4174           1    5.7              94      instock  16209   \n",
              "2         5796           1   12.5              12      instock  13895   \n",
              "3         4582           1  109.6               7      instock  12857   \n",
              "4         6106           1   74.8              15      instock  14106   \n",
              "..         ...         ...    ...             ...          ...    ...   \n",
              "709       4074           1   12.7              50      instock  15941   \n",
              "710       4617           1   67.5               1      instock  10459   \n",
              "711       4062           1   11.9              60      instock  16320   \n",
              "712       4262           1   15.8              35      instock  15663   \n",
              "713       5896           1   24.7              17      instock  15910   \n",
              "\n",
              "     virtual  downloadable  rating_count  average_rating  ...  \\\n",
              "0          0             0             0             0.0  ...   \n",
              "1          0             0             0             0.0  ...   \n",
              "2          0             0             0             0.0  ...   \n",
              "3          0             0             0             0.0  ...   \n",
              "4          0             0             0             0.0  ...   \n",
              "..       ...           ...           ...             ...  ...   \n",
              "709        0             0             0             0.0  ...   \n",
              "710        0             0             0             0.0  ...   \n",
              "711        0             0             0             0.0  ...   \n",
              "712        0             0             0             0.0  ...   \n",
              "713        0             0             0             0.0  ...   \n",
              "\n",
              "          post_modified   post_modified_gmt  post_content_filtered  \\\n",
              "0   2020-08-20 15:35:02 2020-08-20 13:35:02                    NaN   \n",
              "1   2020-08-05 18:05:03 2020-08-05 16:05:03                    NaN   \n",
              "2   2020-04-25 21:11:40 2020-04-25 19:11:40                    NaN   \n",
              "3   2020-02-06 16:35:02 2020-02-06 15:35:02                    NaN   \n",
              "4   2020-05-29 17:35:03 2020-05-29 15:35:03                    NaN   \n",
              "..                  ...                 ...                    ...   \n",
              "709 2020-06-25 14:00:03 2020-06-25 12:00:03                    NaN   \n",
              "710 2020-08-24 14:05:02 2020-08-24 12:05:02                    NaN   \n",
              "711 2020-08-25 11:15:03 2020-08-25 09:15:03                    NaN   \n",
              "712 2020-08-01 09:35:02 2020-08-01 07:35:02                    NaN   \n",
              "713 2020-08-14 10:45:02 2020-08-14 08:45:02                    NaN   \n",
              "\n",
              "     post_parent                                               guid  \\\n",
              "0            0.0  https://www.bottle-neck.fr/?post_type=product&...   \n",
              "1            0.0  https://www.bottle-neck.fr/?post_type=product&...   \n",
              "2            0.0  https://www.bottle-neck.fr/?post_type=product&...   \n",
              "3            0.0  https://www.bottle-neck.fr/?post_type=product&...   \n",
              "4            0.0  https://www.bottle-neck.fr/?post_type=product&...   \n",
              "..           ...                                                ...   \n",
              "709          0.0  https://www.bottle-neck.fr/?post_type=product&...   \n",
              "710          0.0  https://www.bottle-neck.fr/?post_type=product&...   \n",
              "711          0.0  https://www.bottle-neck.fr/?post_type=product&...   \n",
              "712          0.0  https://www.bottle-neck.fr/?post_type=product&...   \n",
              "713          0.0  https://www.bottle-neck.fr/?post_type=product&...   \n",
              "\n",
              "    menu_order  post_type post_mime_type comment_count ca_produit  \n",
              "0          0.0    product            NaN           0.0       36.0  \n",
              "1          0.0    product            NaN           0.0       34.2  \n",
              "2          0.0    product            NaN           0.0        0.0  \n",
              "3          0.0    product            NaN           0.0        0.0  \n",
              "4          0.0    product            NaN           0.0        0.0  \n",
              "..         ...        ...            ...           ...        ...  \n",
              "709        0.0    product            NaN           0.0       50.8  \n",
              "710        0.0    product            NaN           0.0        0.0  \n",
              "711        0.0    product            NaN           0.0       35.7  \n",
              "712        0.0    product            NaN           0.0       47.4  \n",
              "713        0.0    product            NaN           0.0        0.0  \n",
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              "      <td>0.0</td>\n",
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              "      <td>2020-08-01 09:35:02</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/?post_type=product&amp;...</td>\n",
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              "      <td>47.4</td>\n",
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              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>2020-08-14 10:45:02</td>\n",
              "      <td>2020-08-14 08:45:02</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>https://www.bottle-neck.fr/?post_type=product&amp;...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>product</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>714 rows × 34 columns</p>\n",
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              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "\n",
              "  .colab-df-quickchart {\n",
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              "    height: 32px;\n",
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              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
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              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "      border-left-color: var(--fill-color);\n",
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              "      border-left-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-0dc3ef64-ee22-4f0f-80de-0f434f62f409 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 6.2 Calcul du CA total"
      ],
      "metadata": {
        "id": "ElRGvT63C27L"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Calcul du CA total\n",
        "\n",
        "CA_total = jointure['ca_produit'].sum()"
      ],
      "metadata": {
        "id": "2KmAdnI6e397"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Affichage\n",
        "\n",
        "print(\"Le chiffre d'affaires total est de:\", CA_total, 'euros')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XaYHP3lnA6zD",
        "outputId": "0da743d6-34fa-433e-a609-7c948047c048"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Le chiffre d'affaires total est de: 70568.6 euros\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 7.Analyse des outliers de la variable 'price'\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "cbXIipBAtzqm"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 7.1 Quelques indicateurs statistiques"
      ],
      "metadata": {
        "id": "v8rGM3Ti5cZJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Description de 'price'\n",
        "\n",
        "jointure['price'].describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3cp2err3fBQi",
        "outputId": "30ec4627-c12d-4976-b83a-756d8578260d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    714.000000\n",
              "mean      32.493137\n",
              "std       27.810525\n",
              "min        5.200000\n",
              "25%       14.100000\n",
              "50%       23.550000\n",
              "75%       42.175000\n",
              "max      225.000000\n",
              "Name: price, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Indicateurs statistiques de la variable 'price'\n",
        "\n",
        "print(\"Le mode est de\", jointure['price'].mode())\n",
        "print(\"La variance est de\", round(jointure['price'].var(ddof=0),2))\n",
        "print(\"Le Skewness est de\", round(jointure['price'].skew(),2))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mO3XM2w8kfUf",
        "outputId": "664934e4-ff3b-4d06-c89f-fcdefaf354b1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Le mode est de 0    19.0\n",
            "Name: price, dtype: float64\n",
            "La variance est de 772.34\n",
            "Le Skewness est de 2.58\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# La médiane\n",
        "\n",
        "jointure['price'].median()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PogLKfFMwefe",
        "outputId": "e990ef5f-2c61-4e2f-df15-ff79a12d1611"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "23.55"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Z-score method (Utilisation de la moyenne et de l'écart-type)\n",
        "\n",
        "mean = np.mean(jointure['price'])\n",
        "std = np.std(jointure['price'])\n",
        "threshold = 2\n",
        "outliers = []\n",
        "for x in jointure['price'] :\n",
        "    z_score = (x -mean) / std\n",
        "    if abs(z_score) > threshold :\n",
        "        outliers.append(x)\n",
        "print(\"Mean : \",mean)\n",
        "print(\"\\nStandard deviation :\",std)\n",
        "print(\"Nombre d'outliers détectés : \" + str(len(outliers)))\n",
        "print('nOutliers', outliers)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SkU_8eg5DIxA",
        "outputId": "3e3b9168-8f47-4d40-c343-940808951133"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mean :  32.49313725490196\n",
            "\n",
            "Standard deviation : 27.791042941002917\n",
            "Nombre d'outliers détectés : 30\n",
            "nOutliers [109.6, 115.0, 100.0, 102.3, 105.0, 99.0, 88.4, 175.0, 124.8, 176.0, 112.0, 121.0, 105.0, 122.0, 105.6, 217.5, 137.0, 121.0, 115.0, 116.4, 104.0, 93.0, 157.0, 114.0, 126.5, 92.0, 191.3, 135.0, 108.5, 225.0]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "outliers"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RZsz50sRp6dt",
        "outputId": "c939ae04-8c42-4a1f-b35f-777593918389"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[109.6,\n",
              " 115.0,\n",
              " 100.0,\n",
              " 102.3,\n",
              " 105.0,\n",
              " 99.0,\n",
              " 88.4,\n",
              " 175.0,\n",
              " 124.8,\n",
              " 176.0,\n",
              " 112.0,\n",
              " 121.0,\n",
              " 105.0,\n",
              " 122.0,\n",
              " 105.6,\n",
              " 217.5,\n",
              " 137.0,\n",
              " 121.0,\n",
              " 115.0,\n",
              " 116.4,\n",
              " 104.0,\n",
              " 93.0,\n",
              " 157.0,\n",
              " 114.0,\n",
              " 126.5,\n",
              " 92.0,\n",
              " 191.3,\n",
              " 135.0,\n",
              " 108.5,\n",
              " 225.0]"
            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        " # Affichage des outliers\n",
        "\n",
        "affichage = jointure[jointure['price'].isin(outliers)]\n",
        "affichage[['id_web', 'post_title', 'price', 'ca_produit']]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 990
        },
        "id": "9CiJfM8mByN2",
        "outputId": "df7fc2c7-db12-4631-eb1b-8f2cce6d3866"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    id_web                                         post_title  price  \\\n",
              "3    12857  Château de Meursault Puligny-Montrachet 1er Cr...  109.6   \n",
              "5    13996  Domaine des Comtes Lafon Volnay 1er Cru Santen...  115.0   \n",
              "16   15382  Zind-Humbrecht Riesling Grand Cru Rangen De Th...  100.0   \n",
              "37   14805  Domaine Des Croix Corton Grand Cru Les Grèves ...  102.3   \n",
              "102  12791  Domaine des Comtes Lafon Volnay 1er Cru Santen...  105.0   \n",
              "119  11601  Domaine des Comtes Lafon Volnay 1er Cru Champa...   99.0   \n",
              "152  11668  Zind-Humbrecht Pinot Gris Grand Cru Rangen De ...   88.4   \n",
              "177  15185                Camille Giroud Clos de Vougeot 2016  175.0   \n",
              "181  14915  Domaine Weinbach Gewurztraminer Grand Cru Furs...  124.8   \n",
              "186   3510                               Cognac Frapin VIP XO  176.0   \n",
              "187  13914  Champagne Agrapart &amp; Fils L'Avizoise Extra...  112.0   \n",
              "201  15070  Domaine des Comtes Lafon Volnay 1er Cru Champa...  121.0   \n",
              "232  11602  Domaine des Comtes Lafon Volnay 1er Cru Santen...  105.0   \n",
              "239  14775  Wemyss Malts Single Cask Scotch Whisky Choc 'n...  122.0   \n",
              "286  14596  David Duband Chambolle-Musigny 1er Cru Les Sen...  105.6   \n",
              "315  14581     David Duband Charmes-Chambertin Grand Cru 2014  217.5   \n",
              "334  14220  Domaine Des Croix Corton Charlemagne Grand Cru...  137.0   \n",
              "393  15072  Domaine des Comtes Lafon Volnay 1er Cru Santen...  121.0   \n",
              "396  12790  Domaine des Comtes Lafon Volnay 1er Cru Champa...  115.0   \n",
              "405  15126  Domaine Clerget Echezeaux Grand Cru En Orveaux...  116.4   \n",
              "410   3509                          Cognac Frapin Cigar Blend  104.0   \n",
              "437  14774  Wemyss Malts Single Cask Scotch Whisky Chocola...   93.0   \n",
              "464   7819  Cognac Frapin Château de Fontpinot 1989 20 Ans...  157.0   \n",
              "508  14773  Wemyss Malts Single Cask Scotch Whisky Chai Ca...  114.0   \n",
              "519  12589     Champagne Egly-Ouriet Grand Cru Blanc de Noirs  126.5   \n",
              "546  19822                      Tempier Bandol Cabassaou 2017   92.0   \n",
              "559  14983  Coteaux Champenois Egly-Ouriet Ambonnay Rouge ...  191.3   \n",
              "572  14923             Champagne Gosset Célébris Vintage 2007  135.0   \n",
              "580   3507              Cognac Frapin Château de Fontpinot XO  108.5   \n",
              "670  15940     Champagne Egly-Ouriet Grand Cru Millésimé 2008  225.0   \n",
              "\n",
              "     ca_produit  \n",
              "3           0.0  \n",
              "5         230.0  \n",
              "16          0.0  \n",
              "37          0.0  \n",
              "102         0.0  \n",
              "119         0.0  \n",
              "152         0.0  \n",
              "177         0.0  \n",
              "181         0.0  \n",
              "186      2288.0  \n",
              "187         0.0  \n",
              "201         0.0  \n",
              "232         0.0  \n",
              "239         0.0  \n",
              "286         0.0  \n",
              "315         0.0  \n",
              "334       685.0  \n",
              "393         0.0  \n",
              "396         0.0  \n",
              "405         0.0  \n",
              "410       104.0  \n",
              "437         0.0  \n",
              "464         0.0  \n",
              "508         0.0  \n",
              "519      1391.5  \n",
              "546         0.0  \n",
              "559       573.9  \n",
              "572       270.0  \n",
              "580       217.0  \n",
              "670      1125.0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-403e7b8a-bfa6-4872-9c6b-14b7d642de28\" class=\"colab-df-container\">\n",
              "    <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>id_web</th>\n",
              "      <th>post_title</th>\n",
              "      <th>price</th>\n",
              "      <th>ca_produit</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>12857</td>\n",
              "      <td>Château de Meursault Puligny-Montrachet 1er Cr...</td>\n",
              "      <td>109.6</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>13996</td>\n",
              "      <td>Domaine des Comtes Lafon Volnay 1er Cru Santen...</td>\n",
              "      <td>115.0</td>\n",
              "      <td>230.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>15382</td>\n",
              "      <td>Zind-Humbrecht Riesling Grand Cru Rangen De Th...</td>\n",
              "      <td>100.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>14805</td>\n",
              "      <td>Domaine Des Croix Corton Grand Cru Les Grèves ...</td>\n",
              "      <td>102.3</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>102</th>\n",
              "      <td>12791</td>\n",
              "      <td>Domaine des Comtes Lafon Volnay 1er Cru Santen...</td>\n",
              "      <td>105.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119</th>\n",
              "      <td>11601</td>\n",
              "      <td>Domaine des Comtes Lafon Volnay 1er Cru Champa...</td>\n",
              "      <td>99.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>152</th>\n",
              "      <td>11668</td>\n",
              "      <td>Zind-Humbrecht Pinot Gris Grand Cru Rangen De ...</td>\n",
              "      <td>88.4</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>177</th>\n",
              "      <td>15185</td>\n",
              "      <td>Camille Giroud Clos de Vougeot 2016</td>\n",
              "      <td>175.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>181</th>\n",
              "      <td>14915</td>\n",
              "      <td>Domaine Weinbach Gewurztraminer Grand Cru Furs...</td>\n",
              "      <td>124.8</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>186</th>\n",
              "      <td>3510</td>\n",
              "      <td>Cognac Frapin VIP XO</td>\n",
              "      <td>176.0</td>\n",
              "      <td>2288.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>187</th>\n",
              "      <td>13914</td>\n",
              "      <td>Champagne Agrapart &amp;amp; Fils L'Avizoise Extra...</td>\n",
              "      <td>112.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201</th>\n",
              "      <td>15070</td>\n",
              "      <td>Domaine des Comtes Lafon Volnay 1er Cru Champa...</td>\n",
              "      <td>121.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>232</th>\n",
              "      <td>11602</td>\n",
              "      <td>Domaine des Comtes Lafon Volnay 1er Cru Santen...</td>\n",
              "      <td>105.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>239</th>\n",
              "      <td>14775</td>\n",
              "      <td>Wemyss Malts Single Cask Scotch Whisky Choc 'n...</td>\n",
              "      <td>122.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>286</th>\n",
              "      <td>14596</td>\n",
              "      <td>David Duband Chambolle-Musigny 1er Cru Les Sen...</td>\n",
              "      <td>105.6</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>315</th>\n",
              "      <td>14581</td>\n",
              "      <td>David Duband Charmes-Chambertin Grand Cru 2014</td>\n",
              "      <td>217.5</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>334</th>\n",
              "      <td>14220</td>\n",
              "      <td>Domaine Des Croix Corton Charlemagne Grand Cru...</td>\n",
              "      <td>137.0</td>\n",
              "      <td>685.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>393</th>\n",
              "      <td>15072</td>\n",
              "      <td>Domaine des Comtes Lafon Volnay 1er Cru Santen...</td>\n",
              "      <td>121.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>396</th>\n",
              "      <td>12790</td>\n",
              "      <td>Domaine des Comtes Lafon Volnay 1er Cru Champa...</td>\n",
              "      <td>115.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>405</th>\n",
              "      <td>15126</td>\n",
              "      <td>Domaine Clerget Echezeaux Grand Cru En Orveaux...</td>\n",
              "      <td>116.4</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>410</th>\n",
              "      <td>3509</td>\n",
              "      <td>Cognac Frapin Cigar Blend</td>\n",
              "      <td>104.0</td>\n",
              "      <td>104.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>437</th>\n",
              "      <td>14774</td>\n",
              "      <td>Wemyss Malts Single Cask Scotch Whisky Chocola...</td>\n",
              "      <td>93.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>464</th>\n",
              "      <td>7819</td>\n",
              "      <td>Cognac Frapin Château de Fontpinot 1989 20 Ans...</td>\n",
              "      <td>157.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>508</th>\n",
              "      <td>14773</td>\n",
              "      <td>Wemyss Malts Single Cask Scotch Whisky Chai Ca...</td>\n",
              "      <td>114.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>519</th>\n",
              "      <td>12589</td>\n",
              "      <td>Champagne Egly-Ouriet Grand Cru Blanc de Noirs</td>\n",
              "      <td>126.5</td>\n",
              "      <td>1391.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>546</th>\n",
              "      <td>19822</td>\n",
              "      <td>Tempier Bandol Cabassaou 2017</td>\n",
              "      <td>92.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>559</th>\n",
              "      <td>14983</td>\n",
              "      <td>Coteaux Champenois Egly-Ouriet Ambonnay Rouge ...</td>\n",
              "      <td>191.3</td>\n",
              "      <td>573.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>572</th>\n",
              "      <td>14923</td>\n",
              "      <td>Champagne Gosset Célébris Vintage 2007</td>\n",
              "      <td>135.0</td>\n",
              "      <td>270.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>580</th>\n",
              "      <td>3507</td>\n",
              "      <td>Cognac Frapin Château de Fontpinot XO</td>\n",
              "      <td>108.5</td>\n",
              "      <td>217.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>670</th>\n",
              "      <td>15940</td>\n",
              "      <td>Champagne Egly-Ouriet Grand Cru Millésimé 2008</td>\n",
              "      <td>225.0</td>\n",
              "      <td>1125.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "    .colab-df-convert:hover {\n",
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              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-403e7b8a-bfa6-4872-9c6b-14b7d642de28 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-403e7b8a-bfa6-4872-9c6b-14b7d642de28');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "    </g>\n",
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              "  </button>\n",
              "\n",
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              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
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              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
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              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
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              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
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              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "    background-color: var(--disabled-bg-color);\n",
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              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-916787e0-a1bb-4f18-9b4b-fe2474c16466 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Méthode 2 : Ecarts des interquartiles IQR\n",
        "\n",
        "Q1 = np.percentile(jointure['price'], 25, method='midpoint')\n",
        "Q3 = np.percentile(jointure['price'], 75, method='midpoint')\n",
        "IQR = Q3 - Q1\n",
        "print(IQR)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VD1qUg8LV-yn",
        "outputId": "e75b521f-c1ff-4ee0-ede4-a2847a0ef4b2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "28.050000000000004\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Au dessus de Q3\n",
        "\n",
        "upper = Q3+1.5*IQR\n",
        "upper_array = np.array(jointure['price']) >= upper\n",
        "print(\"Upper Bound:\", upper)\n",
        "print(upper_array.sum())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MHhIdEZ5WWW9",
        "outputId": "5c0256da-5054-4fc8-f7e2-047d54216d1e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Upper Bound: 84.22500000000001\n",
            "32\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# En dessous de Q1\n",
        "\n",
        "lower = Q1-1.5*IQR\n",
        "lower_array = np.array(jointure['price']) <= lower\n",
        "print(\"Lower Bound:\", lower)\n",
        "print(lower_array.sum())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-22n2x2XXQf9",
        "outputId": "916e954f-da03-4203-fbf6-5a8b2b3b01cf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Lower Bound: -27.975\n",
            "0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Affichage des outliers\n",
        "\n",
        "print(\"\\n\",jointure.loc[(jointure['price']>84.225),('price','post_title')])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4o6Fq1-dYt8S",
        "outputId": "8e353589-981b-4800-adb9-c7837e06417c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "      price                                         post_title\n",
            "3    109.6  Château de Meursault Puligny-Montrachet 1er Cr...\n",
            "5    115.0  Domaine des Comtes Lafon Volnay 1er Cru Santen...\n",
            "12    86.8  Champagne Agrapart &amp; Fils Minéral Extra Br...\n",
            "16   100.0  Zind-Humbrecht Riesling Grand Cru Rangen De Th...\n",
            "37   102.3  Domaine Des Croix Corton Grand Cru Les Grèves ...\n",
            "102  105.0  Domaine des Comtes Lafon Volnay 1er Cru Santen...\n",
            "119   99.0  Domaine des Comtes Lafon Volnay 1er Cru Champa...\n",
            "152   88.4  Zind-Humbrecht Pinot Gris Grand Cru Rangen De ...\n",
            "177  175.0                Camille Giroud Clos de Vougeot 2016\n",
            "181  124.8  Domaine Weinbach Gewurztraminer Grand Cru Furs...\n",
            "186  176.0                               Cognac Frapin VIP XO\n",
            "187  112.0  Champagne Agrapart &amp; Fils L'Avizoise Extra...\n",
            "201  121.0  Domaine des Comtes Lafon Volnay 1er Cru Champa...\n",
            "232  105.0  Domaine des Comtes Lafon Volnay 1er Cru Santen...\n",
            "239  122.0  Wemyss Malts Single Cask Scotch Whisky Choc 'n...\n",
            "286  105.6  David Duband Chambolle-Musigny 1er Cru Les Sen...\n",
            "315  217.5     David Duband Charmes-Chambertin Grand Cru 2014\n",
            "334  137.0  Domaine Des Croix Corton Charlemagne Grand Cru...\n",
            "393  121.0  Domaine des Comtes Lafon Volnay 1er Cru Santen...\n",
            "396  115.0  Domaine des Comtes Lafon Volnay 1er Cru Champa...\n",
            "405  116.4  Domaine Clerget Echezeaux Grand Cru En Orveaux...\n",
            "410  104.0                          Cognac Frapin Cigar Blend\n",
            "437   93.0  Wemyss Malts Single Cask Scotch Whisky Chocola...\n",
            "464  157.0  Cognac Frapin Château de Fontpinot 1989 20 Ans...\n",
            "508  114.0  Wemyss Malts Single Cask Scotch Whisky Chai Ca...\n",
            "519  126.5     Champagne Egly-Ouriet Grand Cru Blanc de Noirs\n",
            "541   85.6  Champagne Larmandier-Bernier Grand Cru Les Che...\n",
            "546   92.0                      Tempier Bandol Cabassaou 2017\n",
            "559  191.3  Coteaux Champenois Egly-Ouriet Ambonnay Rouge ...\n",
            "572  135.0             Champagne Gosset Célébris Vintage 2007\n",
            "580  108.5              Cognac Frapin Château de Fontpinot XO\n",
            "670  225.0     Champagne Egly-Ouriet Grand Cru Millésimé 2008\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 7.2 Graphiques : representations de la dispersion des prix"
      ],
      "metadata": {
        "id": "pLZA7aKPmQyu"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Representation de la repartition des prix : Histogramme\n",
        "\n",
        "mean = jointure['price'].mean()\n",
        "median = jointure['price'].median()\n",
        "sb.histplot(data= jointure['price'])\n",
        "plt.axvline(mean, color=\"black\", linestyle=\"--\")\n",
        "plt.axvline(median, color=\"black\", linestyle=\"-\")\n",
        "plt.legend({\"Moyenne\":mean,\"Mediane\":median})\n",
        "plt.title(\"Graphique 1 : Histogramme des prix\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 489
        },
        "id": "339nDHyBkzSg",
        "outputId": "e78ecc8e-b499-45b7-9b1a-fcef25846e31"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Graphique 1 : Histogramme des prix')"
            ]
          },
          "metadata": {},
          "execution_count": 54
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Représentation graphique Box plot/ Boîte à moustache\n",
        "\n",
        "sb.set(style ='whitegrid')\n",
        "sb.boxplot(x = 'price', data = jointure)\n",
        "plt.title(\"Graphique 2 : Boîte à moustache de la répartition des prix\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 498
        },
        "id": "p1vIYO2GP8-Y",
        "outputId": "d3f5c96e-d13c-43f5-bfae-22b20423defd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Graphique 2 : Boîte à moustache de la répartition des prix')"
            ]
          },
          "metadata": {},
          "execution_count": 55
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Scatter plot/ Nuage des points\n",
        "\n",
        "plt.scatter(jointure['price'].index, jointure['price'].values)\n",
        "plt.axhline(y = 84.225, color = 'r', linestyle ='-')\n",
        "plt.title(\"Graphique 3 : Scatter plot de la répartition des prix\")\n",
        "plt.show"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 474
        },
        "id": "Mir90otaKuNm",
        "outputId": "ee00584b-42c7-41df-8241-f932c750651d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<function matplotlib.pyplot.show(close=None, block=None)>"
            ]
          },
          "metadata": {},
          "execution_count": 56
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 8.Pour aller plus loin :"
      ],
      "metadata": {
        "id": "7dog7qyRZzxj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Identifier les 10 bouteilles les plus vendues, nom, nombre de ventes, prix, ca et disponibilité en stock\n",
        "\n",
        "Best_Seller = jointure[['id_web','post_title','total_sales','price', 'ca_produit', 'stock_status']]\n",
        "print(Best_Seller.nlargest(10,'total_sales'))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RJFPFH5yZQXt",
        "outputId": "b5b20c04-24eb-4c5a-c994-81f7f47f2eed"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "    id_web                                         post_title  total_sales  \\\n",
            "365   7818             Champagne Gosset Grand Blanc de Blancs         96.0   \n",
            "666   1662                        Champagne Gosset Grand Rosé         87.0   \n",
            "525  16416  Gilles Robin Crozes-Hermitage Rouge Papillon 2019         62.0   \n",
            "138  16295  Moulin de Gassac IGP Pays d'Hérault Guilhem Ro...         46.0   \n",
            "104  16210                   Maurel Pays d'Oc Chardonnay 2019         43.0   \n",
            "265  16189  Le Pas de l'Escalette Languedoc Les Petits Pas...         42.0   \n",
            "566  16580           Domaine Giudicelli Patrimonio Blanc 2019         41.0   \n",
            "367    304                    Champagne Gosset Grande Réserve         40.0   \n",
            "92   16264     Château de La Liquière Faugères L'Ampoule 2019         38.0   \n",
            "534     38         Emile Boeckel Crémant Brut Blanc de Blancs         38.0   \n",
            "\n",
            "     price  ca_produit stock_status  \n",
            "365   49.0      4704.0   outofstock  \n",
            "666   49.0      4263.0      instock  \n",
            "525   16.6      1029.2      instock  \n",
            "138    5.8       266.8      instock  \n",
            "104    5.7       245.1      instock  \n",
            "265   13.3       558.6      instock  \n",
            "566   25.2      1033.2      instock  \n",
            "367   39.0      1560.0      instock  \n",
            "92    10.9       414.2      instock  \n",
            "534    8.6       326.8      instock  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Identifier les 10 bouteilles les plus chères, nom, total des ventes, prix, ca et disponibilité en stock\n",
        "\n",
        "More_expensive = jointure[['id_web','post_title','total_sales','price', 'ca_produit', 'stock_status']]\n",
        "print(More_expensive.nlargest(10,'price'))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_SiAYIBn3mk1",
        "outputId": "6f4be48c-8c0d-4472-cf2d-ec3eb002b524"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "    id_web                                         post_title  total_sales  \\\n",
            "670  15940     Champagne Egly-Ouriet Grand Cru Millésimé 2008          5.0   \n",
            "315  14581     David Duband Charmes-Chambertin Grand Cru 2014          0.0   \n",
            "559  14983  Coteaux Champenois Egly-Ouriet Ambonnay Rouge ...          3.0   \n",
            "186   3510                               Cognac Frapin VIP XO         13.0   \n",
            "177  15185                Camille Giroud Clos de Vougeot 2016          0.0   \n",
            "464   7819  Cognac Frapin Château de Fontpinot 1989 20 Ans...          0.0   \n",
            "334  14220  Domaine Des Croix Corton Charlemagne Grand Cru...          5.0   \n",
            "572  14923             Champagne Gosset Célébris Vintage 2007          2.0   \n",
            "519  12589     Champagne Egly-Ouriet Grand Cru Blanc de Noirs         11.0   \n",
            "181  14915  Domaine Weinbach Gewurztraminer Grand Cru Furs...          0.0   \n",
            "\n",
            "     price  ca_produit stock_status  \n",
            "670  225.0      1125.0   outofstock  \n",
            "315  217.5         0.0      instock  \n",
            "559  191.3       573.9      instock  \n",
            "186  176.0      2288.0      instock  \n",
            "177  175.0         0.0      instock  \n",
            "464  157.0         0.0      instock  \n",
            "334  137.0       685.0      instock  \n",
            "572  135.0       270.0      instock  \n",
            "519  126.5      1391.5      instock  \n",
            "181  124.8         0.0      instock  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Il serait intéressant d'analyser la corrélation entre 'price' et 'total_sales'..."
      ],
      "metadata": {
        "id": "mQzY_1Vhjvue"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}