02-ML/03-Clustering/Lab/ML_Seminar_Clustering_Problem.ipynb

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      "source": [
        "## Кластеризация: самостоятельное задание\n",
        "\n",
        "Рассмотрим следующий датасет покупателей:"
      ],
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              "         ID  Year_Birth   Education Marital_Status   Income  Kidhome  \\\n",
              "0      5524        1957  Graduation         Single  58138.0        0   \n",
              "1      2174        1954  Graduation         Single  46344.0        1   \n",
              "2      4141        1965  Graduation       Together  71613.0        0   \n",
              "3      6182        1984  Graduation       Together  26646.0        1   \n",
              "4      5324        1981         PhD        Married  58293.0        1   \n",
              "...     ...         ...         ...            ...      ...      ...   \n",
              "2235  10870        1967  Graduation        Married  61223.0        0   \n",
              "2236   4001        1946         PhD       Together  64014.0        2   \n",
              "2237   7270        1981  Graduation       Divorced  56981.0        0   \n",
              "2238   8235        1956      Master       Together  69245.0        0   \n",
              "2239   9405        1954         PhD        Married  52869.0        1   \n",
              "\n",
              "      Teenhome Dt_Customer  Recency  MntWines  ...  NumWebVisitsMonth  \\\n",
              "0            0  04-09-2012       58       635  ...                  7   \n",
              "1            1  08-03-2014       38        11  ...                  5   \n",
              "2            0  21-08-2013       26       426  ...                  4   \n",
              "3            0  10-02-2014       26        11  ...                  6   \n",
              "4            0  19-01-2014       94       173  ...                  5   \n",
              "...        ...         ...      ...       ...  ...                ...   \n",
              "2235         1  13-06-2013       46       709  ...                  5   \n",
              "2236         1  10-06-2014       56       406  ...                  7   \n",
              "2237         0  25-01-2014       91       908  ...                  6   \n",
              "2238         1  24-01-2014        8       428  ...                  3   \n",
              "2239         1  15-10-2012       40        84  ...                  7   \n",
              "\n",
              "      AcceptedCmp3  AcceptedCmp4  AcceptedCmp5  AcceptedCmp1  AcceptedCmp2  \\\n",
              "0                0             0             0             0             0   \n",
              "1                0             0             0             0             0   \n",
              "2                0             0             0             0             0   \n",
              "3                0             0             0             0             0   \n",
              "4                0             0             0             0             0   \n",
              "...            ...           ...           ...           ...           ...   \n",
              "2235             0             0             0             0             0   \n",
              "2236             0             0             0             1             0   \n",
              "2237             0             1             0             0             0   \n",
              "2238             0             0             0             0             0   \n",
              "2239             0             0             0             0             0   \n",
              "\n",
              "      Complain  Z_CostContact  Z_Revenue  Response  \n",
              "0            0              3         11         1  \n",
              "1            0              3         11         0  \n",
              "2            0              3         11         0  \n",
              "3            0              3         11         0  \n",
              "4            0              3         11         0  \n",
              "...        ...            ...        ...       ...  \n",
              "2235         0              3         11         0  \n",
              "2236         0              3         11         0  \n",
              "2237         0              3         11         0  \n",
              "2238         0              3         11         0  \n",
              "2239         0              3         11         1  \n",
              "\n",
              "[2240 rows x 29 columns]"
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              "      <td>04-09-2012</td>\n",
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              "      <td>Together</td>\n",
              "      <td>71613.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>21-08-2013</td>\n",
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              "      <td>1984</td>\n",
              "      <td>Graduation</td>\n",
              "      <td>Together</td>\n",
              "      <td>26646.0</td>\n",
              "      <td>1</td>\n",
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              "      <td>10-02-2014</td>\n",
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          },
          "metadata": {},
          "execution_count": 2
        }
      ],
      "source": [
        "import pandas as pd \n",
        "\n",
        "df = pd.read_csv('http://www.soshnikov.com/temp/data/marketing_campaign.zip',sep='\\t')\n",
        "df"
      ]
    },
    {
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      "source": [
        "Датасет содержит следующие поля:\n",
        "\n",
        "* `ID`: уникальный идентификатор\n",
        "* `Year_Birth`: год рождения\n",
        "* `Education`: уровень образования\n",
        "* `Marital_Status`: семейное положение\n",
        "* `Income`: годовой доход семьи\n",
        "* `Kidhome`: число детей в семье\n",
        "* `Teenhome`: число подростков в семье\n",
        "* `Dt_Customer`: дата начала обслуживания в компании\n",
        "* `Recency`: число дней с последней покупки\n",
        "* `Complain`: 1, если за последние 2 года от клиента были жалобы, иначе 0 \n",
        "* `MntWines`: сколько потрачено на вина за последние 2 года\n",
        "* `MntFruits`: сколько потрачено на фрукты за последние 2 года\n",
        "* `MntMeatProducts`: сколько потрачено на мясо за последние 2 года\n",
        "* `MntFishProducts`: сколько потрачено на рыбу за последние 2 года\n",
        "* `MntSweetProducts`: сколько потрачено на сладкое за последние 2 года\n",
        "* `MntGoldProds`: сколько потрачено на золото за последние 2 года\n",
        "* `NumDealsPurchases`: число покупок, сделанных со скидкой\n",
        "* `AcceptedCmp1` ... `AcceptedCmp5`: 1, если клиент принял участие в соответствующей рекламной кампании (от 1 до 5), иначе 0 \n",
        "* `Response`: 1 если клиент принял предложение последней рекламной кампании, иначе 0\n",
        "* `NumWebPurchases`: число покупок через веб-сайт\n",
        "* `NumCatalogPurchases`: число покупок по каталогу\n",
        "* `NumStorePurchases`: число покупок в магазине\n",
        "* `NumWebVisitsMonth`: число заходов на веб-сайт за последний месяц"
      ],
      "metadata": {
        "id": "ok1LGw8sLLSs"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Ваша цель:\n",
        "\n",
        "Провести осмысленную кластеризацию клиентов и выделить основные группы. Визуально подтвердить, что имеет место некоторая кластеризация клиентов.\n",
        "\n",
        "Что надо не забыть сделать:\n",
        "* Предобработка данных, включая приведение полей к числовым\n",
        "* Выбор оптимального количества кластеров\n",
        "* Какие поля учитывать при кластеризации, и нужно ли вычислить дополнительные\n",
        "* Как визуализировать кластеры\n",
        "\n",
        "Также проверьте следующие гипотезы:\n",
        "* Образованные клиенты меньше пьют\n",
        "* Молодые предпочитают покупать онлайн\n",
        "* Семьи с детьми покупают больше сладкого\n"
      ],
      "metadata": {
        "id": "iKH4WRH7L2OS"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "21-9aMswk9qh"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}