Anurag_orta.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "JOpwjUfASk5V"
      },
      "outputs": [],
      "source": [
        "import pandas as pd"
      ]
    },
    {
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      "execution_count": null,
      "metadata": {
        "id": "upmaq6VdSk5Z"
      },
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      "source": [
        "#Load dataset\n",
        "data = pd.read_csv('shopping.csv')"
      ]
    },
    {
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      "execution_count": null,
      "metadata": {
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\"Season\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"Spring\",\n          \"Fall\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Review Rating\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.7162228139312417,\n        \"min\": 2.5,\n        \"max\": 5.0,\n        \"num_unique_values\": 26,\n        \"samples\": [\n          4.9,\n          5.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Subscription Status\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"No\",\n          \"Yes\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Shipping Type\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 6,\n        \"samples\": [\n          \"Express\",\n          \"Free Shipping\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Discount Applied\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"No\",\n          \"Yes\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Promo Code Used\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"No\",\n          \"Yes\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Previous Purchases\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 14,\n        \"min\": 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            "text/plain": [
              "   Customer ID  Age Gender Item Purchased  Category  Purchase Amount (USD)  \\\n",
              "0            1   55   Male         Blouse  Clothing                     53   \n",
              "1            2   19   Male        Sweater  Clothing                     64   \n",
              "2            3   50   Male          Jeans  Clothing                     73   \n",
              "3            4   21   Male        Sandals  Footwear                     90   \n",
              "4            5   45   Male         Blouse  Clothing                     49   \n",
              "\n",
              "        Location Size      Color  Season  Review Rating Subscription Status  \\\n",
              "0       Kentucky    L       Gray  Winter            3.1                 Yes   \n",
              "1          Maine    L     Maroon  Winter            3.1                 Yes   \n",
              "2  Massachusetts    S     Maroon  Spring            3.1                 Yes   \n",
              "3   Rhode Island    M     Maroon  Spring            3.5                 Yes   \n",
              "4         Oregon    M  Turquoise  Spring            2.7                 Yes   \n",
              "\n",
              "   Shipping Type Discount Applied Promo Code Used  Previous Purchases  \\\n",
              "0        Express              Yes             Yes                  14   \n",
              "1        Express              Yes             Yes                   2   \n",
              "2  Free Shipping              Yes             Yes                  23   \n",
              "3   Next Day Air              Yes             Yes                  49   \n",
              "4  Free Shipping              Yes             Yes                  31   \n",
              "\n",
              "  Payment Method Frequency of Purchases  \n",
              "0          Venmo            Fortnightly  \n",
              "1           Cash            Fortnightly  \n",
              "2    Credit Card                 Weekly  \n",
              "3         PayPal                 Weekly  \n",
              "4         PayPal               Annually  "
            ]
          },
          "execution_count": 5,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "data.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ibCMplOYUO70",
        "outputId": "f11b8f44-8551-405e-d952-0d1ae7466cec"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Blouse        171\n",
            "Jewelry       171\n",
            "Pants         171\n",
            "Shirt         169\n",
            "Dress         166\n",
            "Sweater       164\n",
            "Jacket        163\n",
            "Belt          161\n",
            "Sunglasses    161\n",
            "Coat          161\n",
            "Sandals       160\n",
            "Socks         159\n",
            "Skirt         158\n",
            "Shorts        157\n",
            "Scarf         157\n",
            "Hat           154\n",
            "Handbag       153\n",
            "Hoodie        151\n",
            "Shoes         150\n",
            "T-shirt       147\n",
            "Sneakers      145\n",
            "Boots         144\n",
            "Backpack      143\n",
            "Gloves        140\n",
            "Jeans         124\n",
            "Name: Item Purchased, dtype: int64\n"
          ]
        }
      ],
      "source": [
        "# prompt: data.keys\n",
        "\n",
        "data.keys()\n",
        "item_counts = data['Item Purchased'].value_counts()\n",
        "print(item_counts)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nqSbJtuESk5a",
        "outputId": "89bfc487-db76-4c4e-d2da-21fa72a77d66"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(3900, 18)"
            ]
          },
          "execution_count": 6,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "data.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 770
        },
        "id": "FMTY6I19Sk5b",
        "outputId": "cef47f52-abd3-4c62-e9a2-ccd2781ed84e"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "summary": "{\n  \"name\": \"data\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"Customer ID\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1405.274081775269,\n        \"min\": 1.0,\n        \"max\": 3900.0,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          3900.0,\n          1950.5,\n          2925.25\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1364.8783180515723,\n        \"min\": 15.207589127162382,\n        \"max\": 3900.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          44.06846153846154,\n          44.0,\n          3900.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Purchase Amount (USD)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1359.7647934740537,\n        \"min\": 20.0,\n        \"max\": 3900.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          59.76435897435898,\n          60.0,\n          3900.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Review Rating\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1377.6887676679473,\n        \"min\": 0.7162228139312417,\n        \"max\": 3900.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          3.7499487179487176,\n          3.7,\n          3900.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Previous Purchases\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1370.5178374100153,\n        \"min\": 1.0,\n        \"max\": 3900.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          25.35153846153846,\n          25.0,\n          3900.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
              "type": "dataframe"
            },
            "text/html": [
              "\n",
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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",
              "        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>Customer ID</th>\n",
              "      <th>Age</th>\n",
              "      <th>Purchase Amount (USD)</th>\n",
              "      <th>Review Rating</th>\n",
              "      <th>Previous Purchases</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>3900.000000</td>\n",
              "      <td>3900.000000</td>\n",
              "      <td>3900.000000</td>\n",
              "      <td>3900.000000</td>\n",
              "      <td>3900.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>1950.500000</td>\n",
              "      <td>44.068462</td>\n",
              "      <td>59.764359</td>\n",
              "      <td>3.749949</td>\n",
              "      <td>25.351538</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>1125.977353</td>\n",
              "      <td>15.207589</td>\n",
              "      <td>23.685392</td>\n",
              "      <td>0.716223</td>\n",
              "      <td>14.447125</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>20.000000</td>\n",
              "      <td>2.500000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>975.750000</td>\n",
              "      <td>31.000000</td>\n",
              "      <td>39.000000</td>\n",
              "      <td>3.100000</td>\n",
              "      <td>13.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>1950.500000</td>\n",
              "      <td>44.000000</td>\n",
              "      <td>60.000000</td>\n",
              "      <td>3.700000</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>2925.250000</td>\n",
              "      <td>57.000000</td>\n",
              "      <td>81.000000</td>\n",
              "      <td>4.400000</td>\n",
              "      <td>38.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>3900.000000</td>\n",
              "      <td>70.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>50.000000</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-db55e7a9-2c31-40e7-a72e-fb6df587a9ac')\"\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-db55e7a9-2c31-40e7-a72e-fb6df587a9ac 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-db55e7a9-2c31-40e7-a72e-fb6df587a9ac');\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-2d5c0102-a3a7-4218-96a6-0cead9f65516\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-2d5c0102-a3a7-4218-96a6-0cead9f65516')\"\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-2d5c0102-a3a7-4218-96a6-0cead9f65516 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "       Customer ID          Age  Purchase Amount (USD)  Review Rating  \\\n",
              "count  3900.000000  3900.000000            3900.000000    3900.000000   \n",
              "mean   1950.500000    44.068462              59.764359       3.749949   \n",
              "std    1125.977353    15.207589              23.685392       0.716223   \n",
              "min       1.000000    18.000000              20.000000       2.500000   \n",
              "25%     975.750000    31.000000              39.000000       3.100000   \n",
              "50%    1950.500000    44.000000              60.000000       3.700000   \n",
              "75%    2925.250000    57.000000              81.000000       4.400000   \n",
              "max    3900.000000    70.000000             100.000000       5.000000   \n",
              "\n",
              "       Previous Purchases  \n",
              "count         3900.000000  \n",
              "mean            25.351538  \n",
              "std             14.447125  \n",
              "min              1.000000  \n",
              "25%             13.000000  \n",
              "50%             25.000000  \n",
              "75%             38.000000  \n",
              "max             50.000000  "
            ]
          },
          "execution_count": 7,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
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              "uwoAAAAASUVORK5CYII=\n",
              "\">\n",
              "      </div>\n",
              "      <script type=\"text/javascript\">\n",
              "        (() => {\n",
              "          const chartElement = document.getElementById(\"chart-d35509d9-daa2-49cc-adda-e3d326f0306b\");\n",
              "          async function getCodeForChartHandler(event) {\n",
              "            const chartCodeResponse =  await google.colab.kernel.invokeFunction(\n",
              "                'getCodeForChart', [\"chart-d35509d9-daa2-49cc-adda-e3d326f0306b\"], {});\n",
              "            const responseJson = chartCodeResponse.data['application/json'];\n",
              "            await google.colab.notebook.addCell(responseJson.code, 'code');\n",
              "          }\n",
              "          chartElement.onclick = getCodeForChartHandler;\n",
              "        })();\n",
              "      </script>\n",
              "      <style>\n",
              "        .colab-quickchart-chart-with-code  {\n",
              "            display: block;\n",
              "            float: left;\n",
              "            border: 1px solid transparent;\n",
              "        }\n",
              "\n",
              "        .colab-quickchart-chart-with-code:hover {\n",
              "            cursor: pointer;\n",
              "            border: 1px solid #aaa;\n",
              "        }\n",
              "      </style>"
            ],
            "text/plain": [
              "from matplotlib import pyplot as plt\n",
              "_df_0['Customer ID'].plot(kind='hist', bins=20, title='Customer ID')\n",
              "plt.gca().spines[['top', 'right',]].set_visible(False)"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
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              "RK5CYII=\n",
              "\">\n",
              "      </div>\n",
              "      <script type=\"text/javascript\">\n",
              "        (() => {\n",
              "          const chartElement = document.getElementById(\"chart-a966bb24-b5d6-48ef-a566-912e87e862d7\");\n",
              "          async function getCodeForChartHandler(event) {\n",
              "            const chartCodeResponse =  await google.colab.kernel.invokeFunction(\n",
              "                'getCodeForChart', [\"chart-a966bb24-b5d6-48ef-a566-912e87e862d7\"], {});\n",
              "            const responseJson = chartCodeResponse.data['application/json'];\n",
              "            await google.colab.notebook.addCell(responseJson.code, 'code');\n",
              "          }\n",
              "          chartElement.onclick = getCodeForChartHandler;\n",
              "        })();\n",
              "      </script>\n",
              "      <style>\n",
              "        .colab-quickchart-chart-with-code  {\n",
              "            display: block;\n",
              "            float: left;\n",
              "            border: 1px solid transparent;\n",
              "        }\n",
              "\n",
              "        .colab-quickchart-chart-with-code:hover {\n",
              "            cursor: pointer;\n",
              "            border: 1px solid #aaa;\n",
              "        }\n",
              "      </style>"
            ],
            "text/plain": [
              "from matplotlib import pyplot as plt\n",
              "_df_1['Age'].plot(kind='hist', bins=20, title='Age')\n",
              "plt.gca().spines[['top', 'right',]].set_visible(False)"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
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              "AAAAAElFTkSuQmCC\n",
              "\">\n",
              "      </div>\n",
              "      <script type=\"text/javascript\">\n",
              "        (() => {\n",
              "          const chartElement = document.getElementById(\"chart-675d28c5-3bb0-4b52-8a1b-9cf0fa201432\");\n",
              "          async function getCodeForChartHandler(event) {\n",
              "            const chartCodeResponse =  await google.colab.kernel.invokeFunction(\n",
              "                'getCodeForChart', [\"chart-675d28c5-3bb0-4b52-8a1b-9cf0fa201432\"], {});\n",
              "            const responseJson = chartCodeResponse.data['application/json'];\n",
              "            await google.colab.notebook.addCell(responseJson.code, 'code');\n",
              "          }\n",
              "          chartElement.onclick = getCodeForChartHandler;\n",
              "        })();\n",
              "      </script>\n",
              "      <style>\n",
              "        .colab-quickchart-chart-with-code  {\n",
              "            display: block;\n",
              "            float: left;\n",
              "            border: 1px solid transparent;\n",
              "        }\n",
              "\n",
              "        .colab-quickchart-chart-with-code:hover {\n",
              "            cursor: pointer;\n",
              "            border: 1px solid #aaa;\n",
              "        }\n",
              "      </style>"
            ],
            "text/plain": [
              "from matplotlib import pyplot as plt\n",
              "_df_2['Purchase Amount (USD)'].plot(kind='hist', bins=20, title='Purchase Amount (USD)')\n",
              "plt.gca().spines[['top', 'right',]].set_visible(False)"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
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              "\">\n",
              "      </div>\n",
              "      <script type=\"text/javascript\">\n",
              "        (() => {\n",
              "          const chartElement = document.getElementById(\"chart-ed2b667a-080a-42be-adae-84493300c2a7\");\n",
              "          async function getCodeForChartHandler(event) {\n",
              "            const chartCodeResponse =  await google.colab.kernel.invokeFunction(\n",
              "                'getCodeForChart', [\"chart-ed2b667a-080a-42be-adae-84493300c2a7\"], {});\n",
              "            const responseJson = chartCodeResponse.data['application/json'];\n",
              "            await google.colab.notebook.addCell(responseJson.code, 'code');\n",
              "          }\n",
              "          chartElement.onclick = getCodeForChartHandler;\n",
              "        })();\n",
              "      </script>\n",
              "      <style>\n",
              "        .colab-quickchart-chart-with-code  {\n",
              "            display: block;\n",
              "            float: left;\n",
              "            border: 1px solid transparent;\n",
              "        }\n",
              "\n",
              "        .colab-quickchart-chart-with-code:hover {\n",
              "            cursor: pointer;\n",
              "            border: 1px solid #aaa;\n",
              "        }\n",
              "      </style>"
            ],
            "text/plain": [
              "from matplotlib import pyplot as plt\n",
              "_df_3['Review Rating'].plot(kind='hist', bins=20, title='Review Rating')\n",
              "plt.gca().spines[['top', 'right',]].set_visible(False)"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/html": [
              "<h4 class=\"colab-quickchart-section-title\">2-d distributions</h4>\n",
              "<style>\n",
              "  .colab-quickchart-section-title {\n",
              "      clear: both;\n",
              "  }\n",
              "</style>"
            ],
            "text/plain": [
              "<google.colab._quickchart_helpers.SectionTitle at 0x7da57011f0d0>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/html": [
              "      <div class=\"colab-quickchart-chart-with-code\" id=\"chart-30e1c66e-f448-41f9-81dd-475f2f90ab54\">\n",
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              "AAAASUVORK5CYII=\n",
              "\">\n",
              "      </div>\n",
              "      <script type=\"text/javascript\">\n",
              "        (() => {\n",
              "          const chartElement = document.getElementById(\"chart-30e1c66e-f448-41f9-81dd-475f2f90ab54\");\n",
              "          async function getCodeForChartHandler(event) {\n",
              "            const chartCodeResponse =  await google.colab.kernel.invokeFunction(\n",
              "                'getCodeForChart', [\"chart-30e1c66e-f448-41f9-81dd-475f2f90ab54\"], {});\n",
              "            const responseJson = chartCodeResponse.data['application/json'];\n",
              "            await google.colab.notebook.addCell(responseJson.code, 'code');\n",
              "          }\n",
              "          chartElement.onclick = getCodeForChartHandler;\n",
              "        })();\n",
              "      </script>\n",
              "      <style>\n",
              "        .colab-quickchart-chart-with-code  {\n",
              "            display: block;\n",
              "            float: left;\n",
              "            border: 1px solid transparent;\n",
              "        }\n",
              "\n",
              "        .colab-quickchart-chart-with-code:hover {\n",
              "            cursor: pointer;\n",
              "            border: 1px solid #aaa;\n",
              "        }\n",
              "      </style>"
            ],
            "text/plain": [
              "from matplotlib import pyplot as plt\n",
              "_df_4.plot(kind='scatter', x='Customer ID', y='Age', s=32, alpha=.8)\n",
              "plt.gca().spines[['top', 'right',]].set_visible(False)"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
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              "\">\n",
              "      </div>\n",
              "      <script type=\"text/javascript\">\n",
              "        (() => {\n",
              "          const chartElement = document.getElementById(\"chart-d8381b17-2ad9-464e-8a5c-958e60c32bda\");\n",
              "          async function getCodeForChartHandler(event) {\n",
              "            const chartCodeResponse =  await google.colab.kernel.invokeFunction(\n",
              "                'getCodeForChart', [\"chart-d8381b17-2ad9-464e-8a5c-958e60c32bda\"], {});\n",
              "            const responseJson = chartCodeResponse.data['application/json'];\n",
              "            await google.colab.notebook.addCell(responseJson.code, 'code');\n",
              "          }\n",
              "          chartElement.onclick = getCodeForChartHandler;\n",
              "        })();\n",
              "      </script>\n",
              "      <style>\n",
              "        .colab-quickchart-chart-with-code  {\n",
              "            display: block;\n",
              "            float: left;\n",
              "            border: 1px solid transparent;\n",
              "        }\n",
              "\n",
              "        .colab-quickchart-chart-with-code:hover {\n",
              "            cursor: pointer;\n",
              "            border: 1px solid #aaa;\n",
              "        }\n",
              "      </style>"
            ],
            "text/plain": [
              "from matplotlib import pyplot as plt\n",
              "_df_5.plot(kind='scatter', x='Age', y='Purchase Amount (USD)', s=32, alpha=.8)\n",
              "plt.gca().spines[['top', 'right',]].set_visible(False)"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
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              "\">\n",
              "      </div>\n",
              "      <script type=\"text/javascript\">\n",
              "        (() => {\n",
              "          const chartElement = document.getElementById(\"chart-72a63ade-794e-4a7d-8266-96c7f958f2d0\");\n",
              "          async function getCodeForChartHandler(event) {\n",
              "            const chartCodeResponse =  await google.colab.kernel.invokeFunction(\n",
              "                'getCodeForChart', [\"chart-72a63ade-794e-4a7d-8266-96c7f958f2d0\"], {});\n",
              "            const responseJson = chartCodeResponse.data['application/json'];\n",
              "            await google.colab.notebook.addCell(responseJson.code, 'code');\n",
              "          }\n",
              "          chartElement.onclick = getCodeForChartHandler;\n",
              "        })();\n",
              "      </script>\n",
              "      <style>\n",
              "        .colab-quickchart-chart-with-code  {\n",
              "            display: block;\n",
              "            float: left;\n",
              "            border: 1px solid transparent;\n",
              "        }\n",
              "\n",
              "        .colab-quickchart-chart-with-code:hover {\n",
              "            cursor: pointer;\n",
              "            border: 1px solid #aaa;\n",
              "        }\n",
              "      </style>"
            ],
            "text/plain": [
              "from matplotlib import pyplot as plt\n",
              "_df_6.plot(kind='scatter', x='Purchase Amount (USD)', y='Review Rating', s=32, alpha=.8)\n",
              "plt.gca().spines[['top', 'right',]].set_visible(False)"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
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              "ANMh4AAAANMh4AAAANMh4AAAANMh4AAAANP5/wGcSNWTwNlZxQAAAABJRU5ErkJggg==\n",
              "\">\n",
              "      </div>\n",
              "      <script type=\"text/javascript\">\n",
              "        (() => {\n",
              "          const chartElement = document.getElementById(\"chart-e824d729-2db0-4ca9-ab43-c79b94db8fec\");\n",
              "          async function getCodeForChartHandler(event) {\n",
              "            const chartCodeResponse =  await google.colab.kernel.invokeFunction(\n",
              "                'getCodeForChart', [\"chart-e824d729-2db0-4ca9-ab43-c79b94db8fec\"], {});\n",
              "            const responseJson = chartCodeResponse.data['application/json'];\n",
              "            await google.colab.notebook.addCell(responseJson.code, 'code');\n",
              "          }\n",
              "          chartElement.onclick = getCodeForChartHandler;\n",
              "        })();\n",
              "      </script>\n",
              "      <style>\n",
              "        .colab-quickchart-chart-with-code  {\n",
              "            display: block;\n",
              "            float: left;\n",
              "            border: 1px solid transparent;\n",
              "        }\n",
              "\n",
              "        .colab-quickchart-chart-with-code:hover {\n",
              "            cursor: pointer;\n",
              "            border: 1px solid #aaa;\n",
              "        }\n",
              "      </style>"
            ],
            "text/plain": [
              "from matplotlib import pyplot as plt\n",
              "_df_7.plot(kind='scatter', x='Review Rating', y='Previous Purchases', s=32, alpha=.8)\n",
              "plt.gca().spines[['top', 'right',]].set_visible(False)"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/html": [
              "<h4 class=\"colab-quickchart-section-title\">Values</h4>\n",
              "<style>\n",
              "  .colab-quickchart-section-title {\n",
              "      clear: both;\n",
              "  }\n",
              "</style>"
            ],
            "text/plain": [
              "<google.colab._quickchart_helpers.SectionTitle at 0x7da5ab282980>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
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              "\">\n",
              "      </div>\n",
              "      <script type=\"text/javascript\">\n",
              "        (() => {\n",
              "          const chartElement = document.getElementById(\"chart-e82516fa-fc31-4a61-840d-3166e07041d7\");\n",
              "          async function getCodeForChartHandler(event) {\n",
              "            const chartCodeResponse =  await google.colab.kernel.invokeFunction(\n",
              "                'getCodeForChart', [\"chart-e82516fa-fc31-4a61-840d-3166e07041d7\"], {});\n",
              "            const responseJson = chartCodeResponse.data['application/json'];\n",
              "            await google.colab.notebook.addCell(responseJson.code, 'code');\n",
              "          }\n",
              "          chartElement.onclick = getCodeForChartHandler;\n",
              "        })();\n",
              "      </script>\n",
              "      <style>\n",
              "        .colab-quickchart-chart-with-code  {\n",
              "            display: block;\n",
              "            float: left;\n",
              "            border: 1px solid transparent;\n",
              "        }\n",
              "\n",
              "        .colab-quickchart-chart-with-code:hover {\n",
              "            cursor: pointer;\n",
              "            border: 1px solid #aaa;\n",
              "        }\n",
              "      </style>"
            ],
            "text/plain": [
              "from matplotlib import pyplot as plt\n",
              "_df_8['Customer ID'].plot(kind='line', figsize=(8, 4), title='Customer ID')\n",
              "plt.gca().spines[['top', 'right']].set_visible(False)"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
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              "rdWWfO9ElegAAAAASUVORK5CYII=\n",
              "\">\n",
              "      </div>\n",
              "      <script type=\"text/javascript\">\n",
              "        (() => {\n",
              "          const chartElement = document.getElementById(\"chart-8b9813b4-f939-4fdf-b431-640beb3a9e22\");\n",
              "          async function getCodeForChartHandler(event) {\n",
              "            const chartCodeResponse =  await google.colab.kernel.invokeFunction(\n",
              "                'getCodeForChart', [\"chart-8b9813b4-f939-4fdf-b431-640beb3a9e22\"], {});\n",
              "            const responseJson = chartCodeResponse.data['application/json'];\n",
              "            await google.colab.notebook.addCell(responseJson.code, 'code');\n",
              "          }\n",
              "          chartElement.onclick = getCodeForChartHandler;\n",
              "        })();\n",
              "      </script>\n",
              "      <style>\n",
              "        .colab-quickchart-chart-with-code  {\n",
              "            display: block;\n",
              "            float: left;\n",
              "            border: 1px solid transparent;\n",
              "        }\n",
              "\n",
              "        .colab-quickchart-chart-with-code:hover {\n",
              "            cursor: pointer;\n",
              "            border: 1px solid #aaa;\n",
              "        }\n",
              "      </style>"
            ],
            "text/plain": [
              "from matplotlib import pyplot as plt\n",
              "_df_9['Age'].plot(kind='line', figsize=(8, 4), title='Age')\n",
              "plt.gca().spines[['top', 'right']].set_visible(False)"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
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              "QmCC\n",
              "\">\n",
              "      </div>\n",
              "      <script type=\"text/javascript\">\n",
              "        (() => {\n",
              "          const chartElement = document.getElementById(\"chart-357b2dee-08c6-4617-90cb-09d7fda068cc\");\n",
              "          async function getCodeForChartHandler(event) {\n",
              "            const chartCodeResponse =  await google.colab.kernel.invokeFunction(\n",
              "                'getCodeForChart', [\"chart-357b2dee-08c6-4617-90cb-09d7fda068cc\"], {});\n",
              "            const responseJson = chartCodeResponse.data['application/json'];\n",
              "            await google.colab.notebook.addCell(responseJson.code, 'code');\n",
              "          }\n",
              "          chartElement.onclick = getCodeForChartHandler;\n",
              "        })();\n",
              "      </script>\n",
              "      <style>\n",
              "        .colab-quickchart-chart-with-code  {\n",
              "            display: block;\n",
              "            float: left;\n",
              "            border: 1px solid transparent;\n",
              "        }\n",
              "\n",
              "        .colab-quickchart-chart-with-code:hover {\n",
              "            cursor: pointer;\n",
              "            border: 1px solid #aaa;\n",
              "        }\n",
              "      </style>"
            ],
            "text/plain": [
              "from matplotlib import pyplot as plt\n",
              "_df_10['Purchase Amount (USD)'].plot(kind='line', figsize=(8, 4), title='Purchase Amount (USD)')\n",
              "plt.gca().spines[['top', 'right']].set_visible(False)"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
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              "9moAAAAASUVORK5CYII=\n",
              "\">\n",
              "      </div>\n",
              "      <script type=\"text/javascript\">\n",
              "        (() => {\n",
              "          const chartElement = document.getElementById(\"chart-f77d25b5-f2b7-438c-9d15-52c4fe18d7be\");\n",
              "          async function getCodeForChartHandler(event) {\n",
              "            const chartCodeResponse =  await google.colab.kernel.invokeFunction(\n",
              "                'getCodeForChart', [\"chart-f77d25b5-f2b7-438c-9d15-52c4fe18d7be\"], {});\n",
              "            const responseJson = chartCodeResponse.data['application/json'];\n",
              "            await google.colab.notebook.addCell(responseJson.code, 'code');\n",
              "          }\n",
              "          chartElement.onclick = getCodeForChartHandler;\n",
              "        })();\n",
              "      </script>\n",
              "      <style>\n",
              "        .colab-quickchart-chart-with-code  {\n",
              "            display: block;\n",
              "            float: left;\n",
              "            border: 1px solid transparent;\n",
              "        }\n",
              "\n",
              "        .colab-quickchart-chart-with-code:hover {\n",
              "            cursor: pointer;\n",
              "            border: 1px solid #aaa;\n",
              "        }\n",
              "      </style>"
            ],
            "text/plain": [
              "from matplotlib import pyplot as plt\n",
              "_df_11['Review Rating'].plot(kind='line', figsize=(8, 4), title='Review Rating')\n",
              "plt.gca().spines[['top', 'right']].set_visible(False)"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "data.describe()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SByvheHnSk5b",
        "outputId": "6be39e35-5135-4282-f8e1-a7df259903f7"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Customer ID               0\n",
              "Age                       0\n",
              "Gender                    0\n",
              "Item Purchased            0\n",
              "Category                  0\n",
              "Purchase Amount (USD)     0\n",
              "Location                  0\n",
              "Size                      0\n",
              "Color                     0\n",
              "Season                    0\n",
              "Review Rating             0\n",
              "Subscription Status       0\n",
              "Shipping Type             0\n",
              "Discount Applied          0\n",
              "Promo Code Used           0\n",
              "Previous Purchases        0\n",
              "Payment Method            0\n",
              "Frequency of Purchases    0\n",
              "dtype: int64"
            ]
          },
          "execution_count": 8,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "data.isnull().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hTd_5B3eSk5c",
        "outputId": "7b922a89-a091-43f3-b75a-e298044af3de"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Customer ID               3900\n",
              "Age                         53\n",
              "Gender                       2\n",
              "Item Purchased              25\n",
              "Category                     4\n",
              "Purchase Amount (USD)       81\n",
              "Location                    50\n",
              "Size                         4\n",
              "Color                       25\n",
              "Season                       4\n",
              "Review Rating               26\n",
              "Subscription Status          2\n",
              "Shipping Type                6\n",
              "Discount Applied             2\n",
              "Promo Code Used              2\n",
              "Previous Purchases          50\n",
              "Payment Method               6\n",
              "Frequency of Purchases       7\n",
              "dtype: int64"
            ]
          },
          "execution_count": 9,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "data.nunique()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EoeNMUImSk5c",
        "outputId": "81db1239-cb2c-4c41-aab4-86898576477c"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Customer ID                 int64\n",
              "Age                         int64\n",
              "Gender                     object\n",
              "Item Purchased             object\n",
              "Category                   object\n",
              "Purchase Amount (USD)       int64\n",
              "Location                   object\n",
              "Size                       object\n",
              "Color                      object\n",
              "Season                     object\n",
              "Review Rating             float64\n",
              "Subscription Status        object\n",
              "Shipping Type              object\n",
              "Discount Applied           object\n",
              "Promo Code Used            object\n",
              "Previous Purchases          int64\n",
              "Payment Method             object\n",
              "Frequency of Purchases     object\n",
              "dtype: object"
            ]
          },
          "execution_count": 10,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "data.dtypes"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "fYD4IRKNSk5d"
      },
      "outputs": [],
      "source": [
        "data.drop_duplicates(inplace=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0lRYqe_qVdIy",
        "outputId": "a34a2af2-e5e7-4043-9a8c-cc057287b481"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Item Purchased\n",
            "Backpack       8636\n",
            "Belt           9635\n",
            "Blouse        10410\n",
            "Boots          9018\n",
            "Coat           9275\n",
            "Dress         10320\n",
            "Gloves         8477\n",
            "Handbag        8857\n",
            "Hat            9375\n",
            "Hoodie         8767\n",
            "Jacket         9249\n",
            "Jeans          7548\n",
            "Jewelry       10010\n",
            "Pants         10090\n",
            "Sandals        9200\n",
            "Scarf          9561\n",
            "Shirt         10332\n",
            "Shoes          9240\n",
            "Shorts         9433\n",
            "Skirt          9402\n",
            "Sneakers       8635\n",
            "Socks          9252\n",
            "Sunglasses     9649\n",
            "Sweater        9462\n",
            "T-shirt        9248\n",
            "Name: Purchase Amount (USD), dtype: int64\n"
          ]
        }
      ],
      "source": [
        "df = pd.DataFrame(data)\n",
        "grouped_by_item = df.groupby('Item Purchased')\n",
        "total_purchase_per_item = grouped_by_item['Purchase Amount (USD)'].sum()\n",
        "print(total_purchase_per_item)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 682
        },
        "id": "JqF_7JRJVxGm",
        "outputId": "885ca42a-6e00-40a9-96a2-7f194b381233"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 800x800 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Create a pie chart of the total purchase amount per item\n",
        "plt.figure(figsize=(8, 8))\n",
        "plt.pie(total_purchase_per_item, labels=total_purchase_per_item.index, autopct=\"%1.1f%%\", startangle=140)\n",
        "plt.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
        "\n",
        "plt.title('Total Purchase Amount per Item Purchased')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "WwX10xg9bmrl",
        "outputId": "c9197baa-099c-408b-bd78-87aa14b3e4f4"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "   Item Purchased  Average Rating\n",
            "16          Shirt        3.629586\n",
            "11          Jeans        3.648387\n",
            "2          Blouse        3.683626\n",
            "15          Scarf        3.700000\n",
            "18         Shorts        3.711465\n",
            "13          Pants        3.718713\n",
            "9          Hoodie        3.719205\n",
            "4            Coat        3.730435\n",
            "22     Sunglasses        3.744720\n",
            "17          Shoes        3.747333\n",
            "21          Socks        3.750943\n",
            "0        Backpack        3.752448\n",
            "5           Dress        3.754819\n",
            "12        Jewelry        3.756140\n",
            "20       Sneakers        3.757931\n",
            "1            Belt        3.761491\n",
            "10         Jacket        3.763190\n",
            "23        Sweater        3.767073\n",
            "7         Handbag        3.775163\n",
            "19          Skirt        3.782278\n",
            "24        T-shirt        3.782993\n",
            "8             Hat        3.806494\n",
            "3           Boots        3.812500\n",
            "14        Sandals        3.841250\n",
            "6          Gloves        3.864286\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "df = pd.DataFrame(data)\n",
        "grouped_by_item = df.groupby('Item Purchased')\n",
        "average_rating_per_item = grouped_by_item['Review Rating'].mean()\n",
        "results = pd.DataFrame({'Item Purchased': average_rating_per_item.index, 'Average Rating': average_rating_per_item.values})\n",
        "sorted_results = results.sort_values(by='Average Rating', ascending=True)\n",
        "print(sorted_results)\n",
        "#plot\n",
        "least_rated_5 = sorted_results.head(5)\n",
        "item_names = least_rated_5['Item Purchased'].to_numpy()\n",
        "avg_ratings = least_rated_5['Average Rating'].to_numpy()\n",
        "plt.figure(figsize=(8, 6))\n",
        "plt.bar(item_names, avg_ratings)\n",
        "plt.xlabel('Item Purchased')\n",
        "plt.ylabel('Average Rating')\n",
        "plt.title('Average Rating of Least Rated Items (Top 5)')\n",
        "plt.xticks(rotation=45, ha='right')\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 434
        },
        "id": "eizDbxOYdOF0",
        "outputId": "c7400d0a-fc05-4acb-b77d-ef83a0708568"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plt.pie(results_avg, labels=results_avg.index, autopct=\"%1.1f%%\", startangle=140)\n",
        "plt.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
        "\n",
        "plt.title('Total Purchase Amount per Item Purchased')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "7T--6eGiSk5d"
      },
      "outputs": [],
      "source": [
        "from matplotlib import pyplot as plt\n",
        "import seaborn as sns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 564
        },
        "id": "tiSlUreuSk5d",
        "outputId": "2c8a2d92-cccd-40a7-8fb7-698098485c9e"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Distribution of Purchase Amount\n",
        "plt.figure(figsize=(10, 6))\n",
        "sns.histplot(data['Purchase Amount (USD)'], bins=30, kde=True, color='skyblue')\n",
        "plt.title('Distribution of Purchase Amount')\n",
        "plt.xlabel('Purchase Amount (USD)')\n",
        "plt.ylabel('Frequency')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 743
        },
        "id": "dQJPB8QKSk5e",
        "outputId": "0401b0f7-13f7-4bdd-ac95-60851f749842"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "<ipython-input-36-2863bd5f461c>:3: FutureWarning: \n",
            "\n",
            "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
            "\n",
            "  sns.countplot(x='Frequency of Purchases', data=data, palette='plasma')\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Distribution of transaction frequency\n",
        "plt.figure(figsize=(10, 6))\n",
        "sns.countplot(x='Frequency of Purchases', data=data, palette='plasma')\n",
        "plt.title('Distribution of Transaction Frequency')\n",
        "plt.xlabel('Transaction Frequency')\n",
        "plt.ylabel('Count')\n",
        "plt.xticks(rotation=45)\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 564
        },
        "id": "AeNI5r0JSk5e",
        "outputId": "de569d87-dac5-44c8-c069-436ed72b1858"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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fflh79+5VWlqaPvnkExUXF0tyfHf/jTfe0LBhw9S3b1/deeed6tq1q/Ly8rR69WodPnxYmzdv/sV8u3fv1r/+9S8ZhqHy8nJt3rxZ8+fPV2VlpV555RWNHTv2hF87cuRIXXPNNerVq5fc3d21cOFC5eXl6brrrrNvN3DgQL311lt69tln1a1bN0VGRh51VOdkde/eXbfffrvWrVunqKgovfPOO8rLy9OsWbPs24wePVoJCQm6/fbb9etf/1pubm565513FBERoaysLIfHO9lsHh4eevHFF3Xrrbfqggsu0PXXX2+f/jwpKUkPPfRQq17Pz0VEROjxxx/XM888o7Fjx+qyyy5TRkaG3nzzTQ0ePPioiyefrPPOO09vvPGG7r33XqWlpemmm25SamqqKioqtGLFCn3yySd69tlnJTWfY3T11Vfr9ddfl8ViUUpKihYtWnTUuUSn+vN/7LHH9O9//1vjxo3TAw88oNDQUM2ZM0eZmZn68MMPHSbbOBUpKSl69tln9fjjj+vAgQOaMGGCAgIClJmZqYULF+quu+7SI488csLHmDNnjt58801dccUVSklJUUVFhf7xj38oMDDQfsFqAGgVcyYLBADXd+mllxre3t5GVVXVcbe55ZZbDA8PD6OwsNAwDMMoKCgwbrjhBiMgIMAICgoybrnlFuPbb781JBnz5s1z+Np9+/YZN998sxEdHW14eHgYXbp0MS655BLjP//5zy9mk2S/Wa1WIzg42BgwYIAxbdo0Y/v27Udt//PprwsLC42pU6caaWlphp+fnxEUFGQMGTLE+OCDDxy+Ljc31xg/frwREBBgSLJPhd0yHfmxppQ+3vTn48ePN7744gujX79+hpeXl5GWlmbMnz//qK/fsGGDMWTIEMPT09NISEgwXnnllWM+5vGyHW8K8Pfff98YMGCA4eXlZYSGhho33nijcfjwYYdtJk+ebPj5+R2V6XjTsh/LX//6VyMtLc3w8PAwoqKijClTphglJSXHfLxfmv78pzZs2GDccMMNRmxsrOHh4WGEhIQYI0eONObMmeMw3XpBQYExceJEw9fX1wgJCTHuvvtuY9u2bW368zeM5v33qquuMoKDgw1vb2/jnHPOMRYtWuTw9S0/i5//nI+3/xzv+/Lhhx8aw4YNM/z8/Aw/Pz8jLS3NmDp1qpGRkWHf5oILLjB69+591Pdt48aNxvXXX28kJCQYXl5eRmRkpHHJJZcY69ev/+VvOgCcgMUwfna8GwDQpj766CNdccUVWrVqlYYOHWp2HAAA0AYoUgDQhmpqahxmDmtqatLo0aO1fv165ebmtvksdwAAwBycIwUAbej+++9XTU2N0tPTVVdXpwULFui7777T888/T4kCAKAD4YgUALSh9957Ty+//LL27t2r2tpadevWTVOmTNF9991ndjQAANCGKFIAAAAA4CSuIwUAAAAATqJIAQAAAICTmGxCks1mU3Z2tgICAhwumAkAAACgczEMQxUVFYqNjT3hBcYpUpKys7MVHx9vdgwAAAAALuLQoUOKi4s77nqKlKSAgABJzd+swMBAk9MAAAAAMEt5ebni4+PtHeF4KFKSfThfYGAgRQoAAADAL57yw2QTAAAAAOAkihQAAAAAOMnUIjVjxgwNHjxYAQEBioyM1IQJE5SRkeGwzYUXXiiLxeJwu+eeexy2ycrK0vjx4+Xr66vIyEj9+te/VmNj45l8KQAAAAA6EVPPkVq5cqWmTp2qwYMHq7GxUb/97W81evRo7dixQ35+fvbt7rzzTv3hD3+w3/f19bV/3tTUpPHjxys6OlrfffedcnJydPPNN8vDw0PPP//8GX09AAAAADoHi2EYhtkhWhQUFCgyMlIrV67U+eefL6n5iFT//v316quvHvNrPv/8c11yySXKzs5WVFSUJGnmzJl69NFHVVBQIE9Pz1983vLycgUFBamsrIzJJgAAAIBO7GS7gUudI1VWViZJCg0NdVg+d+5chYeHq0+fPnr88cdVXV1tX7d69Wr17dvXXqIkacyYMSovL9f27duP+Tx1dXUqLy93uAEAAADAyXKZ6c9tNpsefPBBDR06VH369LEvv+GGG5SYmKjY2Fht2bJFjz76qDIyMrRgwQJJUm5urkOJkmS/n5ube8znmjFjhp555pnT9EoAAAAAdHQuU6SmTp2qbdu2adWqVQ7L77rrLvvnffv2VUxMjEaOHKl9+/YpJSWlVc/1+OOPa/r06fb7LRfdAgAAAICT4RJD++677z4tWrRIy5cvV1xc3Am3HTJkiCRp7969kqTo6Gjl5eU5bNNyPzo6+piP4eXlZb/4LhfhBQAAAOAsU4uUYRi67777tHDhQi1btkzJycm/+DWbNm2SJMXExEiS0tPTtXXrVuXn59u3WbJkiQIDA9WrV6/TkhsAAABA52bq0L6pU6fqvffe08cff6yAgAD7OU1BQUHy8fHRvn379N577+niiy9WWFiYtmzZooceekjnn3+++vXrJ0kaPXq0evXqpZtuukkvvfSScnNz9cQTT2jq1Kny8vIy8+UBAAAA6KBMnf7cYrEcc/msWbN0yy236NChQ5o0aZK2bdumqqoqxcfH64orrtATTzzhMBzv4MGDmjJlilasWCE/Pz9NnjxZL7zwgtzdT64nMv05AAAAAOnku4FLXUfKLBQpAAAAAFI7vY4UAAAAALQHFCkAAAAAcBJFCgAAAACcRJECAAAAACdRpAAAAADASaZeRwoAAABtIysrS4WFhWbHsAsPD1dCQoLZMYDThiIFAADQzmVlZSmtZ5pqqmvMjmLn4+ujXTt3UabQYVGkAAAA2rnCwkLVVNfoit9eoYjECLPjqOBggRY+v1CFhYUUKXRYFCkAAIAOIiIxQjHdY8yOAXQKTDYBAAAAAE6iSAEAAACAkyhSAAAAAOAkihQAAAAAOIkiBQAAAABOokgBAAAAgJMoUgAAAADgJIoUAAAAADiJIgUAAAAATqJIAQAAAICTKFIAAAAA4CSKFAAAAAA4iSIFAAAAAE6iSAEAAACAkyhSAAAAAOAkihQAAAAAOIkiBQAAAABOcjc7ANBeZWVlqbCw0OwYkqTw8HAlJCSYHQMAAKDToEgBrZCVlaW0nmmqqa4xO4okycfXR7t27qJMAQAAnCEUKaAVCgsLVVNdoyt+e4UiEiNMzVJwsEALn1+owsJCihQAADhpjK45NRQp4BREJEYopnuM2TEAAACcwuiaU0eRAgAAADoZRtecOooUAAAA0Ekxuqb1mP4cAAAAAJxEkQIAAAAAJ1GkAAAAAMBJFCkAAAAAcBKTTQBAJ8S1Q9Cesf8CcAUUKQDoZLh2CNoz9l8AroIiBQCdDNcOQXvG/gvAVVCkALQphty0H1w7BO0Z+y8As1GkALQZhtwAAIDOgiIFoM0w5AZoO650dFfiCC8A/BxFCkCbY8gNcGpc7eiuxBFeAPg5ihQAAC7GlY7uShzhBYBjoUgBAOCiOLoLAK7LanYAAAAAAGhvKFIAAAAA4CSKFAAAAAA4iSIFAAAAAE6iSAEAAACAkyhSAAAAAOAkihQAAAAAOIkiBQAAAABOokgBAAAAgJMoUgAAAADgJIoUAAAAADiJIgUAAAAATnI3OwAAnE47d+40O4IkKTw8XAkJCWbHAAAAbYQiBaBDqiyulCRNmjTJ5CTNfHx9tGvnLsoUAAAdBEUKQIdUW1krSRpx7wilnpVqapaCgwVa+PxCFRYWUqQAdCqMCkBHRpEC0KGFdAlRTPcYs2MAQKfCqAB0BhQpF5SVlaXCwkKzY0jiHRwAAOA8RgWgM6BIuZisrCyl9UxTTXWN2VEk8Q4OAABoPUYFoCOjSLmYwsJC1VTX6IrfXqGIxAhTs/AODgAAAHBsFCkXFZEYwTs4AAAAgIvigrwAAAAA4CSKFAAAAAA4iSIFAAAAAE6iSAEAAACAkyhSAAAAAOAkihQAAAAAOIkiBQAAAABO4jpS+EU7d+40O4IkKTw8nAsDAwAAwCVQpHBclcWVkqRJkyaZnKSZj6+Pdu3cRZkCAACA6ShSOK7aylpJ0oh7Ryj1rFRTsxQcLNDC5xeqsLCQIgUAAADTUaTwi0K6hCime4zZMQAAAACXwWQTAAAAAOAkihQAAAAAOIkiBQAAAABOokgBAAAAgJNMLVIzZszQ4MGDFRAQoMjISE2YMEEZGRkO29TW1mrq1KkKCwuTv7+/Jk6cqLy8PIdtsrKyNH78ePn6+ioyMlK//vWv1djYeCZfCgAAAIBOxNQitXLlSk2dOlVr1qzRkiVL1NDQoNGjR6uqqsq+zUMPPaRPP/1U8+fP18qVK5Wdna0rr7zSvr6pqUnjx49XfX29vvvuO82ZM0ezZ8/Wk08+acZLAgAAANAJmDr9+eLFix3uz549W5GRkdqwYYPOP/98lZWV6e2339Z7772niy66SJI0a9Ys9ezZU2vWrNG5556rL7/8Ujt27NBXX32lqKgo9e/fX3/84x/16KOP6umnn5anp6cZLw0AAABAB+ZS50iVlZVJkkJDQyVJGzZsUENDg0aNGmXfJi0tTQkJCVq9erUkafXq1erbt6+ioqLs24wZM0bl5eXavn37MZ+nrq5O5eXlDjcAAAAAOFkuc0Fem82mBx98UEOHDlWfPn0kSbm5ufL09FRwcLDDtlFRUcrNzbVv89MS1bK+Zd2xzJgxQ88880wbvwIAQHuXlZWlwsJCs2No586dZkdAKxiGoeqGahXVFKm0tlSV9ZUOt6r6KlXWV6q2sVZNRpNshs1+a7I137dYLPL18D3mzd/TX1F+UYryj1KoT6isFpd6PxzodFymSE2dOlXbtm3TqlWrTvtzPf7445o+fbr9fnl5ueLj40/78wIAXFdWVpbSeqapprrG7Ch2lZWVZkfo1BqaGlTdUP3jrbH5Y01DTXNhKimSbpZuWHmDqlZWqbC6ULWNtWckm7vV3V6qov2j5VHnIQ2T9tfsl7XSqlCfUHm4eZyRLEBn5RJF6r777tOiRYv09ddfKy4uzr48Ojpa9fX1Ki0tdTgqlZeXp+joaPs233//vcPjtczq17LNz3l5ecnLy6uNXwUAoD0rLCxUTXWNrvjtFYpIjDA1y561e7T8neWqrT0zf5R3BscqRS2F6KflqKUsVTdUq9F2EjMAd5Uyyh1nHPZ081SId4j8Pf0dbn6efvL39Je3m7fcrG5ys7jJarHab25WN9kMm2oaalTVUOWYt6Fa5XXlyqvKU3FNsRptjTpScURHKo78+MSjpK9Kv9JXG76SJAV6BSrMJ0yhPqGK9o9WtH+0ovyiKFhAGzG1SBmGofvvv18LFy7UihUrlJyc7LB+4MCB8vDw0NKlSzVx4kRJUkZGhrKyspSeni5JSk9P13PPPaf8/HxFRkZKkpYsWaLAwED16tXrzL4g4BQ12Zqah380/Dj8o76pXnVNdWpoalCT0STDMJqHf8giq9WqmooaaZj0QeYH2uG+Q0FeQQrzDVOXgC6KCYiRpxsTrgDOiEiMUEz3GFMzFGaZP7zQpXlIlU2VyqnIaS5BjTUOhaPVpegYrBbrUUPsfNx95Ovhq8bSRq2etVqvv/S6zu13rsJ9wxXuGy4/Dz9ZLJY2ftE/qm+qV35VvnIrc5Vbmau8yjyty1inv83/myIGRajCqFBtY63K68pVXleuzNJM+9daZFG4b7hi/GMU7R+tmIAYxfjHyMudN5gBZ5lapKZOnar33ntPH3/8sQICAuznNAUFBcnHx0dBQUG6/fbbNX36dIWGhiowMFD333+/0tPTde6550qSRo8erV69eummm27SSy+9pNzcXD3xxBOaOnUqR53gkmyGTUXVRcqvzldBVYGKa4pVWluqktoSVda3chjPKOnFbS9K245eFekXqS4BXdQlsIu6BHRRYlCiekb0VM/wnkoJTZG71SUOTAPoxCrrK5Vfla/8qnzlVeY1f6xq/lhQXaDC6kIVVhc2/+6szJd+J72X/56U79zzOJQi9/+VIg+fY5aklpunm+dxS1HO7hyt3rpa50Wep7Njz26D78TJ8XTzVFxgnOICfxzFM0AD9LeFf9MVY69QdGq0ahprVFRdpOKaYhVUFyivMk85lTmqaqhSQXWBCqoLtCV/i6TmchXlH6X4wHjFB8UrITBBQd5BZ+z1dDaci9lxmPoX1FtvvSVJuvDCCx2Wz5o1S7fccosk6f/9v/8nq9WqiRMnqq6uTmPGjNGbb75p39bNzU2LFi3SlClTlJ6eLj8/P02ePFl/+MMfztTLAI7LMAwV1RTpSPkRHa44rOyKbOVV5qnJaDru11gtVvl5/G/4h7u3vNy85OXuJQ83jx+HgMgqQ4aajCZVlFRo57c7NfLikbL4WFRWW6aC6gJlV2Tb37XMr8rXD7k/HPVcHlYPdQ/rrp4RPdUrvJd6R/bWoNhBSg5OPq3vpgLoHJpsTcqtzFVWWZYOlh1s/lh6UIcrDiuvMs9elqobqp1+bKus8vX0dShGPy9FPy9GJypFHYl9woogX8UH/XgOuGEYqqyvVE5ljnIqc5RbmavsimyV15Xbj26ty14nqXlYYHxgvBKDEpUUnKRw3/BO8b073TgXs2MxfWjfL/H29tYbb7yhN95447jbJCYm6rPPPmvLaECrldaWal/JPh0oPaADpQeOeZTJw+qhSL9IRfhFKNwnXME+wQrxDlGwd7B83H2c+s8qZ3eOdn68Uy89+ZLOPvvHd0QNw1BhdWHzGPryI/aP+0v3a0fBDu0q3KXqhmptL9iu7QWOlwoI9QnVoNhBGhw7WINjB2tQ7CB1CezS+m8KgA7LZth0uPywMgozlFGUYf+4t3ivDpUfOukhdT7uPoryj1KkX6Si/H78GOEXYR8yF+YTptzMXF028jLd/trtiu0Re5pfXcdisVgU4BWgAK8AdQ/rbl9eXleuQ2WHdKi8+ZZTkaPyunKH/x/8Pf2VFJykpOAkJQcnK8Q7hGLVCpyL2bEwpgc4RS1/ROwu2q3dRbtVUF3gsN7N4qbYgFj70LouAV0U7B182v8DslgsivCLUIRfhPpH9z9m7kNlh7SzcKd2FOzQzoKd2py3WZvzNqu4plhf7vtSX+770r59bECshiUM0/CE4RqeMFx9IvvIzep2Wl8DANdSVl+mZZnLtCl3k37I/UFb87ZqT/GeEx5RcrO4KS4wTonBiUoISlBCYILig+IV7R9tL0tR/lEnfV7RxryNUr34I74NBXoFqndkb/WO7C2p+Rys7IpsZZVl6UDpAR0qP6TK+kpty9+mbfnb7F+THJxsL1fB3sEmvoL2h3MxOwaKFNAKNsMmJUjfln2rg2sOOhx1ssii+MB4JYU0v2sXFxjnkuchWS1WJQYnKjE4UWO7jbUvr2+q19a8rVqXvU7rjqzTuux12l6wXdkV2fpg+wf6YPsHkqQgryCdF3+ehicM1/mJ52twl8FmvRQAp0FNQ40Olx/WkYojOlB8QHpQuuiLi465rYfVQymhKeoR1qP5Ft5D3cO6Kyk4STH+Mbzp0s54unnaC9L5ieer0daow+WHdaD0gDJLM3W4/LDK68rtb75JUoh3iMMRK6AzcL2/7gAXtq94n2Zvmq3/W/9/0m3S9urmIQ/e7t5KDU1V97DuSglJkY+Hj8lJW8/TzVMDYwdqYOxA3TPoHklSVX2V1mev1zdZ3+ibrG/03aHvVFZXps/3fq7P934uqXlYTr/gftJwKbc+V5G2SP54AtqJlqHALUO7DpcfVmH1z96tDm7+0DWkq/pH99eA6AE6K+ospYWnKTkk2SXfMELbcLe620vShbpQDU0NOlR+SJklmTpQekBHKo6opLZEJbkl9vNx/d39pUukQ7ZDSqpLUoBXgMmvAmh7/NYDfkF9U73+s+M/+tuGv+nrg1//uKJW6h7SXYNSBqlrSNcOXRr8PP10QdIFuiDpAklSo61Rm3M324vV1we/VmF1odYWrpVGSp8UfaLPv/1cCUEJ9v98YwNiZbVYTX4lAKTm4pRbmavM0kz70K1jXUg2zCdMcYFx8q3x1eq/rNaK91fogiEXmJAYrsTDzUNdQ7qqa0hXSVJdY52yyrLs+1NOZY4qLZXSIGld0zqtW7NOYT5hSgxOVFJQ8/8JFCt0BBQp4DiOlB/RzPUz9Y+N/1BeVfNFni2yaHTKaF0YdKEev/JxXfjGhYoJM3eMsxncre72o1YPnvugDMPQjoIdevebd/XSBy/Jq7eX6mx12leyT/tK9klqPtKVEJRg/080JiCGYgWcIYZhqKC6oPkP3ZIDOlB24Kji5G51V5eALvYpsOMC4+Tr4Svpf9N8H1ytAA/++MXRvNy9lBqWqtSwVEnNw0K/+fobrf5+tYLPC1apSlVUU6SimiJtzNkoqXlSo6TgJCUFJSkxOFGBXoFmvgSgVShSwM9szduqP6/+s97b+p59tqnYgFjdPfBu3TbgNsUFxmnjxo16vPFxk5O6DovFot6RvXVt8rV66YOXdPPMm+XWxc0+c2HLH217i/dqb/FeSZKXm5fDEato/2iKVTtgGIYabA1qsjXJZtjUZDQ5fG4Yhtyt7vabh5uH3K3u/GzPMMMwVFxTbD9CkFmaedSEEJ5unvaprZOCkxTlF9Whj6zjzPHx8FGMESN9KV10wUVKPSfVPnHFgdIDyq3MVXFNsYprih2KVWJQ83m7CYEJZ2RSJuBUUaSA//nu0Hd67pvn9NmeH6fSPz/xfN1/zv26vMfl8nDzMDFd+2KxNF/cMco/SkPihsgwDOVV5SmzNFMHSw/qQOkB1TXVaU/xHu0p3iOpuVglBifa36GM9o/mP9EzpK6xThX1FSqvK1d5Xbkq6ipU2VCp2oZa1TTWqKahpvnj/z439MuXrvg5q8UqD6uH/Dz95OfhZ/9oVBjSYGlp9lIZ0YZSQlOY/auVSmtL7aUpsyRTFfUVDuvdre72Ny+Sg5MZboszxtvdW93DutunXK9trD1usWo5x8rPw08JQQmKC4xTQlCCov2jOQ8PLoc9Ep3e6kOr9fTKp+1TfVstVk3sOVG/Pu/XzETXRiwWi6L9oxXtH630uHTZDJvyKn8sVgfLDqquqc4+hbzU/B9vy7vlycHJivSLpFi1Um1jrfaX7Ne+4uahlmsy1kg3Sh8UfKCa/BrVNdW1+rFbLhLtZnGTm9VNFlnUaGtUg62heXbL/7EZNtU11amupk7FNcWODzJe+s2G30gbmu+GeIeoa0hXpYSmqGtw88e08DT1juitEJ+QVmftaCrrK+2l6UDpAZXUljisb5l2vGWK6i6BXfhDFC7hRMXqUNkhZVdmq6qhSjsLd2pn4U5Jzftzl4AuiguKU0Jgc8Hy8/Qz82UAFCl0XptyN+nxpY9r8d7Fkprfrb3lrFv06LBH1S20m8npOjarxaqYgBjFBMTovPjzZDNsDie+Z5VlqbaxtvninkUZkpr/4+0S0KX5mlwBXdQlsIv8Pf1NfiWuo7S21F6U9hbvtX++r2SfDpcfPvoLUqXSxlL7XS83LwV6BSrAK0CBXoHy9/CXj4dP8839f7f/fe7l7iU3i5usFusJy63NsKnR1mi/1TfVq6q+SlUNVaqsr1RVQ5UKCgq0c8NO9T2vr/Lr85VXlaeS2hJtyNmgDTkbjnrM2IBY9Y7ord4RvdUnso96R/ZWr4heneL8isr6Sod38X9+zTqLLOoS2EXJwcn2Sy9wJB3twc+LVUNTg3Iqc5RVlqXD5Yd1qPyQqhuqlVWepazyLH2n7yQ1T4bSck5ffGC8wn3DecMNZxRFCp3OwdKDemL5E5q7Za4MGXKzuOmW/rfod8N/p+QQrn1hBqvFqtiAWMUGxGpo/FDZDJuyK7LtfzC2FKufTl4hNV8QsktAF8UExCjKL0oRvhEddlx9k62p+Xo+pQccji7tLd6rfSX7jj7K8zMBngHqFtpNKaEp8qv305xX5ujiWy5WckqyAjwD5OXu1eaZrRarPN085enmaV8W7hvusE1OfY52vr9Ts38zW2effXbzUZaSTO0r2af9Jfu1v2S/9hbv1Y6CHTpUfkjZFdnKrsjWkv1LHB4nPjBevSN7q09EH/WK6KXekb3VM7xnu50ZzCabFC3ta9qnPTv36FD5IZXWlh61XbR/tL04JQQlnJafI3Cmebh5NF+8OShB0o/n/GWVZ+lQWfP0/AXVBfYJLDblbZLUfBmO+KB4+0WfYwNiOQqL04q9C51GZX2lnvv6Ob2y5hXVN9VLkq7rc52eHfGsUkJTTE6Hn7JarIoLjFNcYJyGJQxTk61J+VX5OlJxREcqjii7Ilv5Vfn2c3pahn5IzRcGjfCLaH4nPl3KteUqpjpGQV5BLv3ufMtRuQOlB+xDtX46UUBWWZZ98pPjifKLUkpoSnNhCklpvoU2f/zpO7UbN27UnI1zFHd33FHFxmz+nv7qG9VXfaP6HrWurLZMOwp2aHvBdm3P367tBdu1LX+bcipz7Nc/ajnC3KKlYPUK7+VQsIK8g87US/pFDU0Nyq/KV35V8xG5vKo8HXY/LN0jbbZtlvJ/3DbKL0rxQfHqGtxVicGJ9ln1gI7MYrEozDdMYb5hGhA9QNKPF4xuKVdHKo6oprHGYYh4y3DAkKYQqbtUVl9m5stAB0SRQodnGIbmbZunXy/5tY5UHJEkjUgaoZd+9ZIGxQ4yOR1OhpvVzT4UcJCaf2Z1jXXKqcxRdkW2cipzVFBVoMLqQjXYGpRdkS1ZJY2Rvmv6Tt+tax4G4ufhp2DvYPstyCtIvh6+8vHwaf7o3vyxLQpXy+x2tY21Km4olhKkr3O/1oYNG5RTmaOcipzmj//7PLcyVw22hhM+pofVwz4hR0rITwpTaIq6hnTt8EMdg7yDlB6frvT4dIflJTUlDuWqpWzlVuYet2DFBcapW2g3JQUn2c/Fqyusk4LlcG5XW7EZNlXWV6qkpkSltaUqri1WQVWB8qryjn000SKpVor0iVTPhJ6KD2yejpwjTkAzHw8fhynXm2xNyq3MVVZZ8/C/rLKsH4cDKku6Qbroi4vUa2MvXZh4oUZ1HaULky7kvEucEooUOrSdBTt1z3/vsV9It2tIV/2/Mf9Pl3a/tEMO/+pMvNy97NM2t7AZNhXXFCu/Kl9bt27Vrl27FNg7ULVutc3n5zQ0n5/TUqiPx93qLh93H7lb3eVmdZObxa358/9NqOBmcftx6u+fTf/dZGtSXVOdahtrHf8gv016aN1DJ3xeq8Wq+MB4JYck2yfZaJkoIDkkWTH+MUxPfQwhPiEaljBMwxKGOSwvrinWzoKd9nLVUrCyK7J1uPzwsc8de1B6O/dt+RX7ydfDV34ezR+93L3kafWUp7unPKwe9vPDrLI6/OxbynPLPlBVX6WK+gpV1VedcLZDPw8/RflFKdIvUpH+karaVqWlLy7VsGeHqW/S0UfnADhys7qpS2Dz+bPpSncYDpiRlaGMQxlSuOy/C95c/6asFqsGxQ7SyOSRGtV1lM6LP0/e7t5mvxS0IxQpdEh1jXV6YdULen7V86pvqpePu49+O/y3euS8R/gl2YFZLVaF+4Yr3DdcTbYm7Zq/S6P6j1Kf9D6qbaxVaW3pj7e6UpXXlqu6sVo1DTWqbqhWTWONfYKEn08dfSqZPC2eqi2oVa+uvZQc2VyIYgJijvnRlYcftjehPqEamjBUQxOGOiwvrS3VjoId9iGUB8uap+TPyMtQVlmWDHdDlfWVqqyvbNM8FlkU5B2kEO8QBXsHK8I3QlH+zeXp50cTt27bqlbMMg/gf346HDC6PFoZj2ZoyXdLVBFcoWWZy/RV5lfaVbhL3x/5Xt8f+V4zVs2Qt7u3Lkq+SBN6TNClPS5VtH+02S8DLo4ihQ5nzeE1uu3j2+znzVycerHevPhNJQYnmpwMZrFYLPYZ6GICYo67nWEYqm+qt5eqJlvzEadGW6P985aPP53y+6efu1nc5OXuJW93b3m7e8vD6qHcPbn6+5N/1z83/FNnn332GXzlOJZg72CdF3+ezos/z2H5xo0bNXDQQE16Y5J843xV1VCl6oZqVTdUq66pTvVN9apvqlejrVE2wybDMGQzbM0//58cufR2927eB9y85efpJ39PfwV4BsjP04/rNgEmCvUK1aieo3RFzyskSYfLD2vp/qVamrlUX+3/SjmVOfpsz2f6bM9nsiyyKD0+XRN6TNCEtAn2IYTAT1Gk0GHUN9Xr6RVP68VvX5TNsCnSL1KvjX1N1/S+hmF8OCkWi0Ve7l7ycvdSiBg33ykZkq+b7wkLN4COIS4wTpP7T9bk/pNlGIa2F2zXJxmf6KNdH2ld9jp9d+g7fXfoO/3mq9+od0RvTew5UTeddROXSIEdRQodwta8rbpp4U3anLdZknRTv5v06thXFeoTanIyAADg6iwWi/pE9lGfyD767fDf6nD5YX2S8YkW7lqoFQdWNE9oU7Bdf/j6Dzo37lzd3O9mXd/3egV7B5sdHSZijAHaNcMw9Pra1zXoH4O0OW+zwn3D9eE1H+rdK96lRAEAgFaJC4zTvYPv1ZKblij/kXy9O+Fdje02VlaLVWsOr9G9n92r2JdjdfvHt2vdkXVmx4VJKFJot0pqSnTlB1fqgcUPqL6pXpd0v0Rbp2zVlT2vNDsaAADoIEJ8QnTTWTfp8xs/1+GHDuvl0S+rd0Rv1TTW6J1N7+ic/ztHg/8xWO9ve/8Xr/eHjoUihXZp7eG1GvC3Afpo10fydPPUa2Nf0yfXfcIMOwAA4LSJCYjR9PTp2jplq1bdukqT+k2Sp5un1mev13UfXqfU11P12trXVFVfZXZUnAEUKbQ7/9jwDw2fNVwHyw4qJSRF3932ne4fcj8TSgAAgDPCYrFoaMJQ/fOKf+rwQ4f19AVPK9w3XAdKD2ja4mlKeS1Fr655VbWNtWZHxWlEkUL74SY9v+V53bXoLjXYGnRlzyu18e6NGhg70OxkAACgk4rwi9BTFz6lrAezNHP8TCUHJyuvKk8PffGQUl5L0Vvr3mLIXwdFkUK7UN1ULU2WPjz4oSyy6LmLntN/rv6PAr0CzY4GAAAgHw8f3T3obmXcl6G/X/J3xQfGK7siW/d+dq/6z+yvr/Z/ZXZEtDGKFFxeYXWhPi76WEqQ/N39teiGRfrt8N8ylA8AALgcDzcP3TnwTu25f49eG/uawnzCtL1gu371z19p+vfTxWUKOw6KFFzawdKDevuHt1XRVCEVS3OGz9HFqRebHQsAAOCEvNy9dP+Q+7Xn/j2aNmSa3CxuWpm3Upoiba3aKpthMzsiThFFCi5ra/5W/XPLP1XbWKtIj0jp/6Qk/ySzYwEAAJy0EJ8QvTr2VW2dslWDwgZJntLq8tV654d3lF+Vb3Y8nAKKFFzSuux1WrBzgZqMJvUM76lLwi6Rqs1OBQAA0Do9I3pqZvpM6RPJw+KhIxVH9PcNf9faw2tlGIbZ8dAKFCm4nFVZq/TZns8kSYNjB+vqXlfL3eJucioAAIBTY7FYpI3SNRHXKDU0VU1GkxbvW6x52+epuoF3jNsbihRchmEYWpq5VEszl0qShiUM07hu45hUAgAAdCh+bn66vs/1GtdtnNwsbtpdtFsz189UVlmW2dHgBIoUXIJhGFqyf4lWZa2SJI1MHqmRySMpUQAAoEOyWCw6p8s5uuPsOxTmE6aK+grN2TxHG3M2mh0NJ4kiBZew/MByrT68WpI0rts4DUsYZnIiAACA0y/aP1p3DbxLvSN6y2bY9OnuT7V472Jm9WsHKFIw3cqDK/VN1jeSpLHdxuqcLueYnAgAAODM8XTz1MSeE3Vh0oWSpLVH1uq9re+prrHO3GA4IYoUTPXtoW+14sAKSdKvuv5KQ7oMMTcQAACACSwWiy5IvEBX97paHlYP7SvZpzmb56iqvsrsaDgOihRMsyl3k77a/5Uk6aKki3Re/HkmJwIAADBXr4heuqX/LfL18FVOZY5mb56tstoys2PhGChSMMWeoj36JOMTSdLQ+KEanjjc5EQAAACuITYgVrf2v1WBXoEqrC7UrE2zVFRdZHYs/AxFCmfckfIjmr9jvgwZ6hfVTyOTR5odCQAAwKWE+4brtv63KcwnTGV1ZZq9ebaKa4rNjoWfoEjhjCquKdZ7295Tg61BKSEpuqz7ZUxxDgAAcAxB3kG6tf+tivSLVGV9pd7d/C7D/FwIRQpnTF1jnf697d+qbqhWtH+0ru51tdysbmbHAgAAcFl+nn66qd9N9iNT7255VxV1FWbHgihSOEMMw9CCXQtUWF2oAM8A3dDnBnm5e5kdCwAAwOX5e/rrpn43KcgrSMU1xfrnln+quqHa7FidHkUKZ8SyA8u0u2i33Cxuurb3tQrwCjA7EgAAQLsR5B2kyWdNVoBngAqqC/T+9vfVaGs0O1anRpHCabctf5tWZa2SJF3W4zJ1CexiciIAAID2J8QnRJP6TZKXm5eyyrL06e5PZRiG2bE6LYoUTqv8qnx9nPGxJCk9Ll39ovqZnAgAAKD9ivSL1NW9rpZFFm3J26Jvsr4xO1KnRZHCaVPfVK/5O+ar0daoriFdNarrKLMjAQAAtHspoSm6OPViSdLyA8u1LX+byYk6J4oUTpvP9nymwupC+Xv668q0K2W1sLsBAAC0hUGxg3Ru3LmSpI8zPlZeZZ7JiTof/rLFabEpd5M2522WRRZN7DlRfp5+ZkcCAADoUH7V9VdKCUlRo61R83fMV11jndmROhWKFNpcQVWBPtvzmSTpgqQLlBScZG4gAACADshqserKnlcq0CtQRTVFTD5xhlGk0KaabE1asGuBGmwN6hrcVcMThpsdCQAAoMPy9fDVVT2vktVi1faC7fo++3uzI3UaFCm0qZUHVyq3Mlc+7j6akDaB86IAAABOs/igeP2q668kSV/u+1JHyo+YnKhz4K9ctJkj5Ufs14sa3308F90FAAA4Q4Z0GaKe4T1lM2xauGuhGpoazI7U4VGk0CYamhq0cNdCGTLUJ7KPekf0NjsSAABAp2GxWHRp90sV4BmgopoifZX5ldmROjyKFNrE0sylKqopkr+nvy7udrHZcQAAADodHw8fXdbjMknS90e+V2ZJpsmJOjaKFE5ZVlmW1h5ZK0m6rPtl8vHwMTkRAABA59QttJsGxgyUJH2U8ZFqG2tNTtRxUaRwSppsTVq0e5EkqX90f6WGpZqcCAAAoHMbnTJaId4hKq8r1+K9i82O02FRpHBKvjv0nQqqC+Tr4avRXUebHQcAAKDT83Tz1IS0CZKkzXmbtb9kv7mBOiiKFFqtuKZYX2d9LUkakzKGIX0AAAAuIiEoQed0OUeS9N89/1WjrdHkRB0PRQqtYhiG/R9l1+Cu6hvZ1+xIAAAA+IkRSSPk7+mv4ppi+yVq0HYoUmiVbfnbtL9kv9yt7hrffbwsFovZkQAAAPAT3u7eGpsyVpK0KmuViqqLTE7UsVCk4LT6pnp9uf9LSdLwhOEK9Qk1OREAAACOpVdEL3UL6aYmo0n/3fNfGYZhdqQOgyIFp32T9Y0q6ysV4h2i8+LPMzsOAAAAjsNisWhc6ji5W92VWZqpbfnbzI7UYVCk4JSSmhKtPrRaUvPUmu5Wd5MTAQAA4ERCfUI1PGG4JOmrzK/U0NRgcqKOgSIFp3y1/ys1GU1KDk5Wj7AeZscBAADASUiPS1eQV5DK68q1+vBqs+N0CBQpnLQDpQe0o3CHLLJoTMoYJpgAAABoJzzcPDQyeaQk6dtD36pWtSYnav8oUjgpNsNmvzL2wNiBivKPMjkRAAAAnNEnso+6BHRRfVO9drjtMDtOu0eRwknZkrdFeVV58nb31oikEWbHAQAAgJMsFotGp4yWJB2wHJAizc3T3lGk8IuajCatOLBCkjQsfph8PXzNDQQAAIBWSQhKUK/wXpJF0hiz07RvFCn8okxbpsrqyhTgGaBzupxjdhwAAACcglFdR8liWKQUqcBWYHacdou5q3FinlKGLUOSdH7i+fJw8zA5EICOaOfOnWZHcIkMAHAmhPiEKNmWrP1u+7XDtkMjjBFMItYKFCmc2LlSneoU6hOqAdEDzE4DoIOpLK6UJE2aNMnkJD+qrKw0OwIAnHY9bD2037ZfRR5F2leyT91Cu5kdqd2hSOG46lQnndf8+YikEXKzupkbCECHU1vZPP3uiHtHKPWsVFOz7Fm7R8vfWa7aWqYEBtDx+chHWi8pXVp+YLlSQlI4KuUkihSOa7d1t+QhBSlIvSN6mx0HQAcW0iVEMd1jTM1QmFVo6vMDwBm3SnJLd1N2Rbb2FO9R97DuZidqV5hsAsdUVV+l/db9kqRebr14hwIAAKCjqZJSrCmSmo9KGYZhcqD2hSKFY1p9eLWaLE3SESnaEm12HAAAAJwGqdZUebp5KrcyV7sKd5kdp12hSOEo1Q3VWpe9rvnO1+JoFAAAQAflZfHSkC5DJEnfZH3DUSkncI4UjrL28FrVN9UryAhSWUaZ2XEAAC7CFaaId4UMQEdzbty5WnN4jXIqc7S/ZL9SQlPMjtQuUKTgoLaxVmuPrJUkpTWlaa3WmpwIAGA2pqkHOjZfD1+dHXO21h5Zq1WHVlGkThJFCg6+P/K96prqFOEbodiyWLPjAABcANPUAx1fely61mWv04HSAzpcflhxgXFmR3J5FCnY1TXWac3hNZKk4QnDpa0mBwIAuBSmqQc6riDvIPWL7KdNeZv07aFvdW3va82O5PIoUrDbmLtRNY01CvUJVe/I3tqu7WZHOoqrjI13lRwAAABt5bz487Qpb5N2Fe5SQVWBIvwizI7k0ihSkCQ12Zq09nDz+VDnxZ8nq8W1JnR0xfH5EmP0AQBAxxHhF6G0sDTtKtql7w5/p8t7XG52JJdmapH6+uuv9ac//UkbNmxQTk6OFi5cqAkTJtjX33LLLZozZ47D14wZM0aLFy+23y8uLtb999+vTz/9VFarVRMnTtRf/vIX+fv7n6mX0SHsKNyhsroy+Xn46ayos8yOcxRXGp8vMUYfAAB0TEMThmpX0S5tyduiEUkjFOgVaHYkl2VqkaqqqtJZZ52l2267TVdeeeUxtxk7dqxmzZplv+/l5eWw/sYbb1ROTo6WLFmihoYG3Xrrrbrrrrv03nvvndbsHYlhGFp9aLUkaXCXwXK3uu6BSlcYny8xRh8AAHRMcYFxSgxK1MGyg1qfvV4XJV9kdiSXZepfzOPGjdO4ceNOuI2Xl5eio6OPuW7nzp1avHix1q1bp0GDBkmSXn/9dV188cX685//rNhYZp07GQdKDyinMkfuVncNjh1sdhwAAACYaEiXITpYdlAbcjbo/MTzXfpNdjO51okwx7BixQpFRkaqR48emjJlioqKiuzrVq9ereDgYHuJkqRRo0bJarVq7drjX/+orq5O5eXlDrfObPXh5qNRA6IHyNfD1+Q0AAAAMFOP8B4K8gpSdUO1tuYxjfPxuHSRGjt2rN59910tXbpUL774olauXKlx48apqalJkpSbm6vIyEiHr3F3d1doaKhyc3OP+7gzZsxQUFCQ/RYfH39aX4cry6/K157iPZKar2oNAACAzs1qsWpwl+ZRSmuPrJVhGCYnck0uXaSuu+46XXbZZerbt68mTJigRYsWad26dVqxYsUpPe7jjz+usrIy++3QoUNtE7gdajka1TO8p0J9Qk1OAwAAAFdwdvTZ8rB6KK8qTwfLDpodxyW5dJH6ua5duyo8PFx79+6VJEVHRys/P99hm8bGRhUXFx/3vCqp+byrwMBAh1tn9NPDtelx6SanAQAAgKvw8fBRv6h+kmS/RA4ctaszxw4fPqyioiLFxDTP2paenq7S0lJt2LBBAwcOlCQtW7ZMNptNQ4YMMTNqu7AxZ6OajCbFBsQqLjDO7DgAAACnzc6dO82O4BIZnDGkyxBtyNmgXUW7VFJTohCfELMjuRRTi1RlZaX96JIkZWZmatOmTQoNDVVoaKieeeYZTZw4UdHR0dq3b59+85vfqFu3bhozZowkqWfPnho7dqzuvPNOzZw5Uw0NDbrvvvt03XXXMWPfL7AZNq3PXi9JGhw7WBaLxeREAAAAba+yuFKSNGnSJJOT/KiystLsCCclwi9CXUO6an/Jfn2f/b3GpIwxO5JLMbVIrV+/XiNGjLDfnz59uiRp8uTJeuutt7RlyxbNmTNHpaWlio2N1ejRo/XHP/7R4VpSc+fO1X333aeRI0faL8j72muvnfHX0t7sLtqtsroy+bj7qE9kH7PjoA24wrtcrpDBlbnK98dVcgAdhSv8m3KFDK6qtrJWkjTi3hFKPSvV1Cx71u7R8neWq7a21tQczhjSZYj2l+zX5tzNGpk8kqnQf8LU78SFF154wllAvvjii198jNDQUC6+2wrfH/leknR2zNn8g2jneKfN9bniz0ji5wScKlf8t82/6+ML6RKimO4xpmYozCo09flbo1toNwV6Baq8rlw7CnbYz5tCOztHCm2joKpAmaWZssiiQbGDfvkL4NJ4p831udLPSOLnBLQVV/q3zb9rnC5Wi1VnR5+tFQdXaEPOBorUT7SqSO3fv19du3Zt6yw4Q9Zlr5Mk9QjroWDvYHPDoM3wTpvrc4WfkcTPCWhrrvBvm3/XOJ0GxAzQyoMrlVWWpYKqAkX4RZgdySW0avrzbt26acSIEfrXv/7FOx/tTF1jnTbnbZYk+4XWAAAAgOMJ9ApU97DukqQNORtMTuM6WlWkNm7cqH79+mn69OmKjo7W3Xffre+//76ts+E02JK3RfVN9Qr3DVdycLLZcQAAANAODIxpvtTQ5rzNamhqMDmNa2hVkerfv7/+8pe/KDs7W++8845ycnI0bNgw9enTR6+88ooKCgraOifagGEY9ncRBsYMZMpzAAAAnJSU0BQFeQWptrFWOwp2mB3HJbSqSLVwd3fXlVdeqfnz5+vFF1/U3r179cgjjyg+Pl4333yzcnJy2ion2kB2RbbyqvLkZnHTWVFnmR0HAAAA7YTVYtXZMWdLYnhfi1MqUuvXr9e9996rmJgYvfLKK3rkkUe0b98+LVmyRNnZ2br88svbKifawMbcjZKkXhG95OPhY3IaAAAAtCcDogfIarHqUPkh5Vflmx3HdK0qUq+88or69u2r8847T9nZ2Xr33Xd18OBBPfvss0pOTtbw4cM1e/Zsbdy4sa3zopXqGuu0NW+rJNnfTQAAAABOVoBXgLqHNk86sSl3k7lhXECritRbb72lG264QQcPHtRHH32kSy65RFar40NFRkbq7bffbpOQOHXbCrapwdagMJ8wJQYlmh0HAAAA7VD/6P6Smicwa7I1mRvGZK26jtSePXt+cRtPT09Nnjy5NQ+P02BjTvPRwbNjzmaSCQAAALRKt9Bu8vPwU1VDlfYW71WP8B5mRzJNq45IzZo1S/Pnzz9q+fz58zVnzpxTDoW2lVuZq+yKbFktViaZAAAAQKu5Wd3UN6qvJNmvTdpZtapIzZgxQ+Hh4Uctj4yM1PPPP3/KodC2WmZW6RneU36efianAQAAQHvWP6q/JCmjKEPVDdXmhjFRq4pUVlaWkpOPvphrYmKisrKyTjkU2k5DUwOTTAAAAKDNRPlHKcY/RjbDZv87szNqVZGKjIzUli1bjlq+efNmhYWFnXIotJ2MogzVNdUpyCtIycFHl18AAADAWS2TTmzK22RqDjO1qkhdf/31euCBB7R8+XI1NTWpqalJy5Yt07Rp03Tddde1dUacgpapKc+KOotJJgAAANAm+kT2kZvFTbmVucqtzDU7jilaVaT++Mc/asiQIRo5cqR8fHzk4+Oj0aNH66KLLuIcKRdSUVeh/SX7JUlnRTPJBAAAANqGr4eveoQ1z9jXWa8p1arpzz09PfX+++/rj3/8ozZv3iwfHx/17dtXiYlcn8iVbMnbIkOG4gPjFeoTanYcAAAAdCBnRZ+lHYU7tC1/m0anjJbV0qpjNO1Wq4pUi+7du6t79+5tlQVtyDAM+5jVljGsAAAAQFtJCUmRr4evqhqqtL9kv7qFdjM70hnVqiLV1NSk2bNna+nSpcrPz5fNZnNYv2zZsjYJh9bLrshWYXWh3K3u6hXRy+w4AAAA6GDcrG7qFdFL67PXa2v+VorUyZg2bZpmz56t8ePHq0+fPkxi4IJajkb1DO8pb3dvc8MAAACgQ+oX2U/rs9drV+EuNTQ1yMPNw+xIZ0yritS8efP0wQcf6OKLL27rPGgDjbZGbcvfJql5tj4AAADgdIgLjFOwd7BKa0uVUZShPpF9zI50xrTqjDBPT09169a5Dt21J7uLdqu2sVYBngFKDuHaUQAAADg9LBaL+kb2laROd3HeVhWphx9+WH/5y19kGEZb50EbaNmJ+0b17XSzpwAAAODMailSe0v2qrqh2uQ0Z06rhvatWrVKy5cv1+eff67evXvLw8NxLOSCBQvaJBycV9NQoz3FeyQ1j1kFAAAATqcIvwhF+0crtzJXOwp2aFDsILMjnRGtKlLBwcG64oor2joL2sDOwp1qMpoU6RepKP8os+MAAACgE+gb2Ve5lbnamreVInUis2bNauscaCP2YX3/O8QKAAAAnG59Ivtoyf4lyirPUmltqYK9g82OdNq1+gSaxsZGffXVV/rb3/6miooKSVJ2drYqKyvbLBycU15XrgNlBySpU82YAgAAAHMFegUqKThJkrQ9f7u5Yc6QVhWpgwcPqm/fvrr88ss1depUFRQUSJJefPFFPfLII20aECevZcrzhMCETvEuAAAAAFxH74jekqTtBRSp45o2bZoGDRqkkpIS+fj42JdfccUVWrp0aZuFg3O25v84Wx8AAABwJvUM7ymLLMqpzFFxTbHZcU67VhWpb775Rk888YQ8PT0dliclJenIkSNtEgzOKagqUG5lrqwWq3pF9DI7DgAAADoZP08/JQc3X8N0R8EOk9Ocfq0qUjabTU1NTUctP3z4sAICAk45FJzXcjSqW0g3+Xr4mpwGAAAAnVHvyM4zvK9VRWr06NF69dVX7fctFosqKyv11FNP6eKLL26rbDhJhmHYz49iWB8AAADMkhaeJossyq3MVVF1kdlxTqtWFamXX35Z3377rXr16qXa2lrdcMMN9mF9L774YltnxC/IrshWSW2JPKwe6h7W3ew4AAAA6KR8PXzVNaSrpI5/VKpV15GKi4vT5s2bNW/ePG3ZskWVlZW6/fbbdeONNzpMPoEzo2Un7RHWQ55unr+wNQAAAHD69I7srX0l+7SjYIfOTzzf7DinTauKlCS5u7tr0qRJbZkFrWAYhr1I9YpkkgkAAACYKy0sTYssi5RXlafC6kKF+4abHem0aFWRevfdd0+4/uabb25VGDjvcPlhldeVy9PNU6mhqWbHAQAAQCfn4+GjlJAU7Sneo+3523VB0gVmRzotWlWkpk2b5nC/oaFB1dXV8vT0lK+vL0XqDPrpsD53a6sPMAIAAABtpndE7+YiVdBxi1SrJpsoKSlxuFVWViojI0PDhg3Tv//977bOiOMwDMM+R3/LlaQBAAAAs/UI7yGrxaqC6gIVVheaHee0aFWROpbU1FS98MILRx2twumTVZalivoKebl5KSU0xew4AAAAgCTJ291bXYObZ+/bWbjT5DSnR5sVKal5Aors7Oy2fEicQMuwvrTwNIb1AQAAwKWkRaRJknYWdMwi1aq/vj/55BOH+4ZhKCcnR3/96181dOjQNgmGE7MZNob1AQAAwGWlhaXpv/qvcipzVFpbqmDvYLMjtalWFakJEyY43LdYLIqIiNBFF12kl19+uS1y4RccLD2oqoaq5sOm/7voGQAAAOAq/Dz9lBCUoINlB7WzcKfS49LNjtSmWlWkbDZbW+eAk3YUNh+N6hneU25WN5PTAAAAAEfrGdGzuUgVdLwi1abnSOHMsBk2+1jTXhFchBcAAACuqWd4T0nSofJDqqirMDlN22rVEanp06ef9LavvPJKa54CJ3Co7JB9WF9ycLLZcQAAAIBjCvQKVJeALjpScUS7inZpcOxgsyO1mVYVqR9++EE//PCDGhoa1KNHD0nS7t275ebmprPPPtu+ncViaZuUcNAyhWSPsB4M6wMAAIBL6xnRU0cqjmhnwU6K1KWXXqqAgADNmTNHISEhkpov0nvrrbdq+PDhevjhh9s0JH5kGIa9SLUcKgUAAABcVc/wnvpq/1c6UHpA1Q3V8vXwNTtSm2jVOVIvv/yyZsyYYS9RkhQSEqJnn32WWftOsyMVR1ReVy5PN08uwgsAAACXF+oTqii/KBkylFGUYXacNtOqIlVeXq6CgoKjlhcUFKiiomOdROZqWiaZSA1N5SK8AAAAaBfSwpsvzru7cLfJSdpOq4rUFVdcoVtvvVULFizQ4cOHdfjwYX344Ye6/fbbdeWVV7Z1RvzPT4f1MVsfAAAA2oseYc3zKuwr2aeGpgaT07SNVh3SmDlzph555BHdcMMNamho/ka4u7vr9ttv15/+9Kc2DYgf5VXlqaS2RO5Wd3UL7WZ2HAAAAOCkRPtHK9ArUOV15coszVT3sO5mRzplrToi5evrqzfffFNFRUX2GfyKi4v15ptvys/Pr60z4n92FDRfhLdbaDd5unmanAYAAAA4ORaLxX5UalfhLpPTtI1TuiBvTk6OcnJylJqaKj8/PxmG0Va5cAzM1gcAAID2qqVI7S7a3SF6Q6uKVFFRkUaOHKnu3bvr4osvVk5OjiTp9ttvZ+rz06SwulCF1YWyWqwd4lAoAAAAOpek4CR5uXmpqqFKRyqOmB3nlLWqSD300EPy8PBQVlaWfH1/nAf+2muv1eLFi9ssHH7Ucgi0a3BXebt7m5wGAAAAcI6b1c1+nn9HGN7XqiL15Zdf6sUXX1RcXJzD8tTUVB08eLBNgsFRy87WI7yHyUkAAACA1mn5W3Z3UfufBr1VRaqqqsrhSFSL4uJieXl5nXIoOKqoq7Af/mwZWwoAAAC0N6mhqbJarCqoLlBxTbHZcU5Jq4rU8OHD9e6779rvWywW2Ww2vfTSSxoxYkSbhUOzlitAdwnoogCvAJPTAAAAAK3j7e6txKBESVJGYYbJaU5Nq64j9dJLL2nkyJFav3696uvr9Zvf/Ebbt29XcXGxvv3227bO2Om17GQtV4QGAAAA2qseYT2UWZqpjKIMpcenmx2n1Vp1RKpPnz7avXu3hg0bpssvv1xVVVW68sor9cMPPyglJaWtM3ZqdY11yizNlMSwPgAAALR/LedJZZVlqbqh2uQ0ref0EamGhgaNHTtWM2fO1O9+97vTkQk/sbd4r5qMJoX5hCncN9zsOAAAAMApCfYOVpRflPKq8rSnaI8iFWl2pFZx+oiUh4eHtmzZcjqy4Bh2Ff04W5/FYjE5DQAAAHDqWkZatcwF0B61amjfpEmT9Pbbb7d1FvxMk61Je4r2SJLSwjg/CgAAAB1Dy/C+vcV71Wg0mpymdVo12URjY6PeeecdffXVVxo4cKD8/Pwc1r/yyittEq6zO1B6QHVNdfLz8FNcYNwvfwEAAADQDsT4xyjAM0AV9RXKrss2O06rOFWk9u/fr6SkJG3btk1nn322JGn3bseLaTH8rO0wrA8AAAAdkcViUY/wHlqfvV4H6g6YHadVnCpSqampysnJ0fLlyyVJ1157rV577TVFRUWdlnCdmWEY9jGjDOsDAABAR9MjrLlIZdVmSe3wmIFT50gZhuFw//PPP1dVVVWbBkKzwoZCVdRXyMPqoeSQZLPjAAAAAG0qKThJnm6eqrZVS7Fmp3FeqyabaPHzYoW203KIMzU0Ve7WVp3KBgAAALgsd6u7uoV2a77TDi+X6lSRslgsR52rw7k7p8eB2gOSfpzRBAAAAOhoWqZBb49FyqlDHYZh6JZbbpGXl5ckqba2Vvfcc89Rs/YtWLCg7RJ2RqFSSWOJLLIoNTTV7DQAAADAaZEamiqLLDKiDB2uOqyzdbbZkU6aU0Vq8uTJDvcnTZrUpmHwP/9r5EnBSfLx8DE3CwAAAHCa+Hj4KMYzRtn12fo672tdpsvMjnTSnCpSs2bNOl058FP/m6QvLZzZ+gAAANCxJXonKjsrWwH9A8yO4pRTmmwCba+4rlhKaP7cPmYUAAAA6KD6+PaRZkqXxl9qdhSnUKRczDd530gWKdw9XEHeQWbHAQAAAE6r9jp5HUXKxazIXSFJSvJOMjUHAAAAgOOjSLmQyvpKrSlYI6l5rCgAAAAA10SRciGrslap3lYvlUih7qFmxwEAAABwHBQpFzK221h9dNFH0sftd6woAAAA0BlQpFxMvF+8dMDsFAAAAABOhCIFAAAAAE4ytUh9/fXXuvTSSxUbGyuLxaKPPvrIYb1hGHryyScVExMjHx8fjRo1Snv27HHYpri4WDfeeKMCAwMVHBys22+/XZWVlWfwVQAAAADobEwtUlVVVTrrrLP0xhtvHHP9Sy+9pNdee00zZ87U2rVr5efnpzFjxqi2tta+zY033qjt27dryZIlWrRokb7++mvdddddZ+olAAAAAOiE3M188nHjxmncuHHHXGcYhl599VU98cQTuvzyyyVJ7777rqKiovTRRx/puuuu086dO7V48WKtW7dOgwYNkiS9/vrruvjii/XnP/9ZsbGxZ+y1AAAAAOg8XPYcqczMTOXm5mrUqFH2ZUFBQRoyZIhWr14tSVq9erWCg4PtJUqSRo0aJavVqrVr1x73sevq6lReXu5wAwAAAICT5bJFKjc3V5IUFRXlsDwqKsq+Ljc3V5GRkQ7r3d3dFRoaat/mWGbMmKGgoCD7LT4+vo3TAwAAAOjIXLZInU6PP/64ysrK7LdDhw6ZHQkAAABAO+KyRSo6OlqSlJeX57A8Ly/Pvi46Olr5+fkO6xsbG1VcXGzf5li8vLwUGBjocAMAAACAk+WyRSo5OVnR0dFaunSpfVl5ebnWrl2r9PR0SVJ6erpKS0u1YcMG+zbLli2TzWbTkCFDznhmAAAAAJ2DqbP2VVZWau/evfb7mZmZ2rRpk0JDQ5WQkKAHH3xQzz77rFJTU5WcnKzf//73io2N1YQJEyRJPXv21NixY3XnnXdq5syZamho0H333afrrruOGfsAAAAAnDamFqn169drxIgR9vvTp0+XJE2ePFmzZ8/Wb37zG1VVVemuu+5SaWmphg0bpsWLF8vb29v+NXPnztV9992nkSNHymq1auLEiXrttdfO+GsBAAAA0HmYWqQuvPBCGYZx3PUWi0V/+MMf9Ic//OG424SGhuq99947HfEAAAAA4Jhc9hwpAAAAAHBVFCkAAAAAcBJFCgAAAACcRJECAAAAACdRpAAAAADASRQpAAAAAHASRQoAAAAAnESRAgAAAAAnUaQAAAAAwEkUKQAAAABwEkUKAAAAAJxEkQIAAAAAJ1GkAAAAAMBJFCkAAAAAcBJFCgAAAACcRJECAAAAACdRpAAAAADASRQpAAAAAHASRQoAAAAAnESRAgAAAAAnUaQAAAAAwEkUKQAAAABwEkUKAAAAAJxEkQIAAAAAJ1GkAAAAAMBJFCkAAAAAcBJFCgAAAACcRJECAAAAACdRpAAAAADASRQpAAAAAHASRQoAAAAAnESRAgAAAAAnUaQAAAAAwEkUKQAAAABwEkUKAAAAAJxEkQIAAAAAJ1GkAAAAAMBJFCkAAAAAcBJFCgAAAACcRJECAAAAACdRpAAAAADASRQpAAAAAHASRQoAAAAAnESRAgAAAAAnUaQAAAAAwEkUKQAAAABwEkUKAAAAAJxEkQIAAAAAJ1GkAAAAAMBJFCkAAAAAcBJFCgAAAACcRJECAAAAACdRpAAAAADASRQpAAAAAHASRQoAAAAAnESRAgAAAAAnUaQAAAAAwEkUKQAAAABwEkUKAAAAAJxEkQIAAAAAJ1GkAAAAAMBJFCkAAAAAcBJFCgAAAACcRJECAAAAACdRpAAAAADASRQpAAAAAHASRQoAAAAAnESRAgAAAAAnUaQAAAAAwEkUKQAAAABwEkUKAAAAAJxEkQIAAAAAJ1GkAAAAAMBJFCkAAAAAcBJFCgAAAACcRJECAAAAACdRpAAAAADASRQpAAAAAHASRQoAAAAAnOTSRerpp5+WxWJxuKWlpdnX19bWaurUqQoLC5O/v78mTpyovLw8ExMDAAAA6AxcukhJUu/evZWTk2O/rVq1yr7uoYce0qeffqr58+dr5cqVys7O1pVXXmliWgAAAACdgbvZAX6Ju7u7oqOjj1peVlamt99+W++9954uuugiSdKsWbPUs2dPrVmzRueee+6ZjgoAAACgk3D5I1J79uxRbGysunbtqhtvvFFZWVmSpA0bNqihoUGjRo2yb5uWlqaEhAStXr36hI9ZV1en8vJyhxsAAAAAnCyXLlJDhgzR7NmztXjxYr311lvKzMzU8OHDVVFRodzcXHl6eio4ONjha6KiopSbm3vCx50xY4aCgoLst/j4+NP4KgAAAAB0NC49tG/cuHH2z/v166chQ4YoMTFRH3zwgXx8fFr9uI8//rimT59uv19eXk6ZAgAAAHDSXPqI1M8FBwere/fu2rt3r6Kjo1VfX6/S0lKHbfLy8o55TtVPeXl5KTAw0OEGAAAAACerXRWpyspK7du3TzExMRo4cKA8PDy0dOlS+/qMjAxlZWUpPT3dxJQAAAAAOjqXHtr3yCOP6NJLL1ViYqKys7P11FNPyc3NTddff72CgoJ0++23a/r06QoNDVVgYKDuv/9+paenM2MfAAAAgNPKpYvU4cOHdf3116uoqEgREREaNmyY1qxZo4iICEnS//t//09Wq1UTJ05UXV2dxowZozfffNPk1AAAAAA6OpcuUvPmzTvhem9vb73xxht64403zlAiAAAAAGhn50gBAAAAgCugSAEAAACAkyhSAAAAAOAkihQAAAAAOIkiBQAAAABOokgBAAAAgJMoUgAAAADgJIoUAAAAADiJIgUAAAAATqJIAQAAAICTKFIAAAAA4CSKFAAAAAA4iSIFAAAAAE6iSAEAAACAkyhSAAAAAOAkihQAAAAAOIkiBQAAAABOokgBAAAAgJMoUgAAAADgJIoUAAAAADiJIgUAAAAATqJIAQAAAICTKFIAAAAA4CSKFAAAAAA4iSIFAAAAAE6iSAEAAACAkyhSAAAAAOAkihQAAAAAOIkiBQAAAABOokgBAAAAgJMoUgAAAADgJIoUAAAAADiJIgUAAAAATqJIAQAAAICTKFIAAAAA4CSKFAAAAAA4iSIFAAAAAE6iSAEAAACAkyhSAAAAAOAkihQAAAAAOIkiBQAAAABOokgBAAAAgJMoUgAAAADgJIoUAAAAADiJIgUAAAAATqJIAQAAAICTKFIAAAAA4CSKFAAAAAA4iSIFAAAAAE6iSAEAAACAkyhSAAAAAOAkihQAAAAAOIkiBQAAAABOokgBAAAAgJMoUgAAAADgJIoUAAAAADiJIgUAAAAATqJIAQAAAICTKFIAAAAA4CSKFAAAAAA4iSIFAAAAAE6iSAEAAACAkyhSAAAAAOAkihQAAAAAOIkiBQAAAABOokgBAAAAgJMoUgAAAADgJIoUAAAAADiJIgUAAAAATqJIAQAAAICTKFIAAAAA4CSKFAAAAAA4iSIFAAAAAE6iSAEAAACAkyhSAAAAAOAkihQAAAAAOIkiBQAAAABOokgBAAAAgJMoUgAAAADgJIoUAAAAADipwxSpN954Q0lJSfL29taQIUP0/fffmx0JAAAAQAfVIYrU+++/r+nTp+upp57Sxo0bddZZZ2nMmDHKz883OxoAAACADqhDFKlXXnlFd955p2699Vb16tVLM2fOlK+vr9555x2zowEAAADogNzNDnCq6uvrtWHDBj3++OP2ZVarVaNGjdLq1auP+TV1dXWqq6uz3y8rK5MklZeXn96wJ6GyslKSlL07W/U19aZmKThY0Pwxs0AH/Q6S5SdcKQ9ZyOIsV8pDFtfPIrlWHrK4fhbJtfKQxfWzFB4qlNT8d7Ar/D3eksEwjBNuZzF+aQsXl52drS5duui7775Tenq6fflvfvMbrVy5UmvXrj3qa55++mk988wzZzImAAAAgHbk0KFDiouLO+76dn9EqjUef/xxTZ8+3X7fZrOpuLhYYWFhslgsJiY7s8rLyxUfH69Dhw4pMDDQ7DhwIewbOBH2DxwP+wZOhP0Dx+Nq+4ZhGKqoqFBsbOwJt2v3RSo8PFxubm7Ky8tzWJ6Xl6fo6Ohjfo2Xl5e8vLwclgUHB5+uiC4vMDDQJXZauB72DZwI+weOh30DJ8L+geNxpX0jKCjoF7dp95NNeHp6auDAgVq6dKl9mc1m09KlSx2G+gEAAABAW2n3R6Qkafr06Zo8ebIGDRqkc845R6+++qqqqqp06623mh0NAAAAQAfUIYrUtddeq4KCAj355JPKzc1V//79tXjxYkVFRZkdzaV5eXnpqaeeOmqYI8C+gRNh/8DxsG/gRNg/cDztdd9o97P2AQAAAMCZ1u7PkQIAAACAM40iBQAAAABOokgBAAAAgJMoUgAAAADgJIpUBzdjxgwNHjxYAQEBioyM1IQJE5SRkeGwTW1traZOnaqwsDD5+/tr4sSJR13gGB3TW2+9pX79+tkvgJeenq7PP//cvp59Ay1eeOEFWSwWPfjgg/Zl7B+d19NPPy2LxeJwS0tLs69n3+jcjhw5okmTJiksLEw+Pj7q27ev1q9fb19vGIaefPJJxcTEyMfHR6NGjdKePXtMTIwzJSkp6ajfHRaLRVOnTpXU/n53UKQ6uJUrV2rq1Klas2aNlixZooaGBo0ePVpVVVX2bR566CF9+umnmj9/vlauXKns7GxdeeWVJqbGmRIXF6cXXnhBGzZs0Pr163XRRRfp8ssv1/bt2yWxb6DZunXr9Le//U39+vVzWM7+0bn17t1bOTk59tuqVavs69g3Oq+SkhINHTpUHh4e+vzzz7Vjxw69/PLLCgkJsW/z0ksv6bXXXtPMmTO1du1a+fn5acyYMaqtrTUxOc6EdevWOfzeWLJkiSTp6quvltQOf3cY6FTy8/MNScbKlSsNwzCM0tJSw8PDw5g/f759m507dxqSjNWrV5sVEyYKCQkx/u///o99A4ZhGEZFRYWRmppqLFmyxLjggguMadOmGYbB747O7qmnnjLOOuusY65j3+jcHn30UWPYsGHHXW+z2Yzo6GjjT3/6k31ZaWmp4eXlZfz73/8+ExHhQqZNm2akpKQYNputXf7u4IhUJ1NWViZJCg0NlSRt2LBBDQ0NGjVqlH2btLQ0JSQkaPXq1aZkhDmampo0b948VVVVKT09nX0DkqSpU6dq/PjxDvuBxO8OSHv27FFsbKy6du2qG2+8UVlZWZLYNzq7Tz75RIMGDdLVV1+tyMhIDRgwQP/4xz/s6zMzM5Wbm+uwfwQFBWnIkCHsH51MfX29/vWvf+m2226TxWJpl787KFKdiM1m04MPPqihQ4eqT58+kqTc3Fx5enoqODjYYduoqCjl5uaakBJn2tatW+Xv7y8vLy/dc889WrhwoXr16sW+Ac2bN08bN27UjBkzjlrH/tG5DRkyRLNnz9bixYv11ltvKTMzU8OHD1dFRQX7Rie3f/9+vfXWW0pNTdUXX3yhKVOm6IEHHtCcOXMkyb4PREVFOXwd+0fn89FHH6m0tFS33HKLpPb5/4q72QFw5kydOlXbtm1zGMcO9OjRQ5s2bVJZWZn+85//aPLkyVq5cqXZsWCyQ4cOadq0aVqyZIm8vb3NjgMXM27cOPvn/fr105AhQ5SYmKgPPvhAPj4+JiaD2Ww2mwYNGqTnn39ekjRgwABt27ZNM2fO1OTJk01OB1fy9ttva9y4cYqNjTU7SqtxRKqTuO+++7Ro0SItX75ccXFx9uXR0dGqr69XaWmpw/Z5eXmKjo4+wylhBk9PT3Xr1k0DBw7UjBkzdNZZZ+kvf/kL+0Ynt2HDBuXn5+vss8+Wu7u73N3dtXLlSr322mtyd3dXVFQU+wfsgoOD1b17d+3du5ffHZ1cTEyMevXq5bCsZ8+e9qGfLfvAz2diY//oXA4ePKivvvpKd9xxh31Ze/zdQZHq4AzD0H333aeFCxdq2bJlSk5Odlg/cOBAeXh4aOnSpfZlGRkZysrKUnp6+pmOCxdgs9lUV1fHvtHJjRw5Ulu3btWmTZvst0GDBunGG2+0f87+gRaVlZXat2+fYmJi+N3RyQ0dOvSoy6zs3r1biYmJkqTk5GRFR0c77B/l5eVau3Yt+0cnMmvWLEVGRmr8+PH2Ze3yd4fZs13g9JoyZYoRFBRkrFixwsjJybHfqqur7dvcc889RkJCgrFs2TJj/fr1Rnp6upGenm5iapwpjz32mLFy5UojMzPT2LJli/HYY48ZFovF+PLLLw3DYN+Ao5/O2mcY7B+d2cMPP2ysWLHCyMzMNL799ltj1KhRRnh4uJGfn28YBvtGZ/b9998b7u7uxnPPPWfs2bPHmDt3ruHr62v861//sm/zwgsvGMHBwcbHH39sbNmyxbj88suN5ORko6amxsTkOFOampqMhIQE49FHHz1qXXv73UGR6uAkHfM2a9Ys+zY1NTXGvffea4SEhBi+vr7GFVdcYeTk5JgXGmfMbbfdZiQmJhqenp5GRESEMXLkSHuJMgz2DTj6eZFi/+i8rr32WiMmJsbw9PQ0unTpYlx77bXG3r177evZNzq3Tz/91OjTp4/h5eVlpKWlGX//+98d1ttsNuP3v/+9ERUVZXh5eRkjR440MjIyTEqLM+2LL74wJB3zZ97efndYDMMwTDwgBgAAAADtDudIAQAAAICTKFIAAAAA4CSKFAAAAAA4iSIFAAAAAE6iSAEAAACAkyhSAAAAAOAkihQAAAAAOIkiBQAAAABOokgBAAAAgJMoUgCADm/16tVyc3PT+PHjzY4CAOggLIZhGGaHAADgdLrjjjvk7++vt99+WxkZGYqNjTU7EgCgneOIFACgQ6usrNT777+vKVOmaPz48Zo9e7bD+k8++USpqany9vbWiBEjNGfOHFksFpWWltq3WbVqlYYPHy4fHx/Fx8frgQceUFVV1Zl9IQAAl0KRAgB0aB988IHS0tLUo0cPTZo0Se+8845aBmNkZmbqqquu0oQJE7R582bdfffd+t3vfufw9fv27dPYsWM1ceJEbdmyRe+//75WrVql++67z4yXAwBwEQztAwB0aEOHDtU111yjadOmqbGxUTExMZo/f74uvPBCPfbYY/rvf/+rrVu32rd/4okn9Nxzz6mkpETBwcG644475Obmpr/97W/2bVatWqULLrhAVVVV8vb2NuNlAQBMxhEpAECHlZGRoe+//17XX3+9JMnd3V3XXnut3n77bfv6wYMHO3zNOeec43B/8+bNmj17tvz9/e23MWPGyGazKTMz88y8EACAy3E3OwAAAKfL22+/rcbGRofJJQzDkJeXl/7617+e1GNUVlbq7rvv1gMPPHDUuoSEhDbLCgBoXyhSAIAOqbGxUe+++65efvlljR492mHdhAkT9O9//1s9evTQZ5995rBu3bp1DvfPPvts7dixQ926dTvtmQEA7QfnSAEAOqSPPvpI1157rfLz8xUUFOSw7tFHH9WyZcv0wQcfqEePHnrooYd0++23a9OmTXr44Yd1+PBhlZaWKigoSFu2bNG5556r2267TXfccYf8/Py0Y8cOLVmy5KSPagEAOh7OkQIAdEhvv/22Ro0adVSJkqSJEydq/fr1qqio0H/+8x8tWLBA/fr101tvvWWftc/Ly0uS1K9fP61cuVK7d+/W8OHDNWDAAD355JNciwoAOjmOSAEA8BPPPfecZs6cqUOHDpkdBQDgwjhHCgDQqb355psaPHiwwsLC9O233+pPf/oT14gCAPwiihQAoFPbs2ePnn32WRUXFyshIUEPP/ywHn/8cbNjAQBcHEP7AAAAAMBJTDYBAAAAAE6iSAEAAACAkyhSAAAAAOAkihQAAAAAOIkiBQAAAABOokgBAAAAgJMoUgAAAADgJIoUAAAAADjp/wOWCgIGN/VFAQAAAABJRU5ErkJggg==",
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Customer demographics - Age distribution\n",
        "plt.figure(figsize=(10, 6))\n",
        "sns.histplot(data['Age'], bins=20, kde=True, color='green')\n",
        "plt.title('Age Distribution of Customers')\n",
        "plt.xlabel('Age')\n",
        "plt.ylabel('Frequency')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 699
        },
        "id": "aCfghG6fSk5e",
        "outputId": "77416fd5-ef7e-49db-88c0-9152796c7d89"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1200x800 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Explore correlations between different variables (excluding categorical variables)\n",
        "numerical_columns = data.select_dtypes(include=['int64', 'float64']).columns\n",
        "correlation_matrix = data[numerical_columns].corr()\n",
        "\n",
        "plt.figure(figsize=(12, 8))\n",
        "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', fmt=\".2f\")\n",
        "plt.title('Correlation Matrix')\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "b2fQYGJKSk5e",
        "outputId": "ec3f0344-84bc-489d-f08d-e80b178af727"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Summary Statistics:\n",
            "        Customer ID          Age  Purchase Amount (USD)  Review Rating  \\\n",
            "count  3900.000000  3900.000000            3900.000000    3900.000000   \n",
            "mean   1950.500000    44.068462              59.764359       3.749949   \n",
            "std    1125.977353    15.207589              23.685392       0.716223   \n",
            "min       1.000000    18.000000              20.000000       2.500000   \n",
            "25%     975.750000    31.000000              39.000000       3.100000   \n",
            "50%    1950.500000    44.000000              60.000000       3.700000   \n",
            "75%    2925.250000    57.000000              81.000000       4.400000   \n",
            "max    3900.000000    70.000000             100.000000       5.000000   \n",
            "\n",
            "       Previous Purchases  \n",
            "count         3900.000000  \n",
            "mean            25.351538  \n",
            "std             14.447125  \n",
            "min              1.000000  \n",
            "25%             13.000000  \n",
            "50%             25.000000  \n",
            "75%             38.000000  \n",
            "max             50.000000  \n"
          ]
        }
      ],
      "source": [
        "summary_statistics = data.describe()\n",
        "print(\"Summary Statistics:\\n\", summary_statistics)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "H2AqjhGySk5f"
      },
      "outputs": [],
      "source": [
        "product_sales = data.groupby('Item Purchased')['Purchase Amount (USD)'].sum().sort_values(ascending=False)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LolFu8qRSk5f",
        "outputId": "e8f685d7-d76e-440b-cf1c-b6e8205b08b8"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Top Selling Products:\n",
            " Item Purchased\n",
            "Blouse        10410\n",
            "Shirt         10332\n",
            "Dress         10320\n",
            "Pants         10090\n",
            "Jewelry       10010\n",
            "Sunglasses     9649\n",
            "Belt           9635\n",
            "Scarf          9561\n",
            "Sweater        9462\n",
            "Shorts         9433\n",
            "Name: Purchase Amount (USD), dtype: int64\n"
          ]
        }
      ],
      "source": [
        "top_selling_products = product_sales.head(10)\n",
        "print(\"Top Selling Products:\\n\", top_selling_products)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aD0AAKbbSk5f",
        "outputId": "ec0d1107-3da0-4522-c596-9d981d6210af"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Categories of Top Selling Products: ['Clothing' 'Accessories']\n"
          ]
        }
      ],
      "source": [
        "top_selling_categories = data[data['Item Purchased'].isin(top_selling_products.index)]['Category'].unique()\n",
        "print(\"Categories of Top Selling Products:\", top_selling_categories)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "mRJoQLPwSk5f"
      },
      "outputs": [],
      "source": [
        "category_sales = data.groupby('Category')['Purchase Amount (USD)'].sum().sort_values(ascending=False)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Zcc2rn84Sk5f",
        "outputId": "f7e10380-23db-4e00-8b73-b347b12ecf68"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Top Selling Categories:\n",
            " Category\n",
            "Clothing       104264\n",
            "Accessories     74200\n",
            "Footwear        36093\n",
            "Outerwear       18524\n",
            "Name: Purchase Amount (USD), dtype: int64\n"
          ]
        }
      ],
      "source": [
        "top_selling_categories = category_sales.head(5)\n",
        "print(\"Top Selling Categories:\\n\", top_selling_categories)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 724
        },
        "id": "7oppV4tjSk5g",
        "outputId": "e05a41a7-7c25-416a-9518-2bc8b41cc943"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "<ipython-input-23-96ec538765e1>:2: FutureWarning: \n",
            "\n",
            "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
            "\n",
            "  sns.barplot(x=top_selling_categories.index, y=top_selling_categories.values, palette='pastel')\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plt.figure(figsize=(10, 6))\n",
        "sns.barplot(x=top_selling_categories.index, y=top_selling_categories.values, palette='pastel')\n",
        "plt.title('Top Selling Categories')\n",
        "plt.xlabel('Category')\n",
        "plt.ylabel('Total Sales (USD)')\n",
        "plt.xticks(rotation=45)\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 517
        },
        "id": "ZU2dzBLySk5g",
        "outputId": "736dadab-f51a-4cd7-b23a-7fbb975d0f18"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "<ipython-input-24-757bb784ab0a>:2: FutureWarning: \n",
            "\n",
            "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
            "\n",
            "  sns.countplot(x='Gender', data=data, palette='pastel')\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 600x400 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plt.figure(figsize=(6, 4))\n",
        "sns.countplot(x='Gender', data=data, palette='pastel')\n",
        "plt.title('Distribution of Customer Gender')\n",
        "plt.xlabel('Gender')\n",
        "plt.ylabel('Count')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 735
        },
        "id": "_6jwsBhCSk5g",
        "outputId": "2a5ebc2b-3402-4a4d-9ac8-9ddf2adea6c7"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "<ipython-input-25-99cfea770e7e>:3: FutureWarning: \n",
            "\n",
            "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
            "\n",
            "  sns.countplot(x='Payment Method', data=data, palette='pastel')\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Preferred payment methods\n",
        "plt.figure(figsize=(8, 6))\n",
        "sns.countplot(x='Payment Method', data=data, palette='pastel')\n",
        "plt.title('Preferred Payment Methods')\n",
        "plt.xlabel('Payment Method')\n",
        "plt.ylabel('Count')\n",
        "plt.xticks(rotation=45)\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "N5UYGaIeSk5g"
      },
      "outputs": [],
      "source": [
        "average_age = data['Age'].mean()\n",
        "most_common_payment_method = data['Payment Method'].mode()[0]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0YML1ERjSk5h",
        "outputId": "96456bfa-d96e-4e70-bda9-55bee223ef3c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Average Age of Customers: 44.06846153846154\n",
            "Most Common Payment Method: PayPal\n"
          ]
        }
      ],
      "source": [
        "print(\"Average Age of Customers:\", average_age)\n",
        "print(\"Most Common Payment Method:\", most_common_payment_method)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DXBm-bGGSk5h",
        "outputId": "97261702-5013-403f-c3ae-30ca7e1b432d"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0       False\n",
              "1       False\n",
              "2       False\n",
              "3       False\n",
              "4       False\n",
              "        ...  \n",
              "3895    False\n",
              "3896    False\n",
              "3897    False\n",
              "3898    False\n",
              "3899    False\n",
              "Length: 3900, dtype: bool"
            ]
          },
          "execution_count": 28,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "data.duplicated()"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "base",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.12.1"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}