git_social_graphs_git_dataset.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Копия блокнота \"git_social_graphs_data.ipynb\"",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyM/9dVv+i3eVeKrGuGawVKV"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# **Подготовка данных**"
      ],
      "metadata": {
        "id": "2jZCfSHeoa--"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Для начала нам необходимо загрузить файлы в виде pandas DataFrame"
      ],
      "metadata": {
        "id": "XAw-L7KGofvF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Импорт модулей для работы с файлами в Google Colaboratory\n",
        "\n",
        "from google.colab import files\n",
        "import io\n",
        "from google.colab import drive\n",
        "drive.mount('drive')"
      ],
      "metadata": {
        "id": "rwrv4Ev1pW-C",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "546d1976-bdb5-4b79-882b-b3b68965b241"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at drive; to attempt to forcibly remount, call drive.mount(\"drive\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "iAlZGl-8Gcvm",
        "outputId": "6a5c421c-ad56-4015-e166-f7824ad2d387",
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": 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              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 109
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-d3c3bcbd-d913-4e8a-8ee5-3cfb09f1212a\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-d3c3bcbd-d913-4e8a-8ee5-3cfb09f1212a\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving musae_git_edges.csv to musae_git_edges (6).csv\n",
            "Saving musae_git_target.csv to musae_git_target (6).csv\n"
          ]
        }
      ],
      "source": [
        "# Загрузка локальных файлов\n",
        "\n",
        "uploaded = files.upload()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Импорт модуля pandas\n",
        "import pandas as pd\n",
        "\n",
        "# Чтение csv-файлов\n",
        "target = pd.read_csv(io.BytesIO(uploaded['musae_git_target.csv']))\n",
        "edges = pd.read_csv(io.BytesIO(uploaded['musae_git_edges.csv']))"
      ],
      "metadata": {
        "id": "idtVo7buYaJS"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Создадим функцию для рассчета характеристик параметров датасетов"
      ],
      "metadata": {
        "id": "1oyfHydoXIoe"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def scale_values(value):\n",
        "    uniq_values = sorted(value.unique())\n",
        "    shape_value = len(uniq_values)\n",
        "    if value.dtype == object:\n",
        "        min_value = \"-\"\n",
        "        max_value = \"-\"\n",
        "    else:\n",
        "        min_value = pd.Series(uniq_values).min()\n",
        "        max_value = pd.Series(uniq_values).max()\n",
        "\n",
        "    return value.dtype, shape_value, min_value, max_value, uniq_values"
      ],
      "metadata": {
        "id": "8AkEvKgqToL-"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Работа с узлами** *(musae_git_target.csv)*"
      ],
      "metadata": {
        "id": "4nzHa_YLoaMO"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Посмотрим характеристики набора"
      ],
      "metadata": {
        "id": "kUFeg7qrW7Nt"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "target.head()"
      ],
      "metadata": {
        "id": "M3F3_rwo8--d",
        "outputId": "ea3cdf98-3e20-4646-e4e5-d70ef37465d3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        }
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   id          name  ml_target\n",
              "0   0        Eiryyy          0\n",
              "1   1    shawflying          0\n",
              "2   2   JpMCarrilho          1\n",
              "3   3     SuhwanCha          0\n",
              "4   4  sunilangadi2          1"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-7f01934a-14b7-4037-84c9-e083d74b0a01\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>name</th>\n",
              "      <th>ml_target</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>Eiryyy</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>shawflying</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>JpMCarrilho</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>SuhwanCha</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>sunilangadi2</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7f01934a-14b7-4037-84c9-e083d74b0a01')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-7f01934a-14b7-4037-84c9-e083d74b0a01 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-7f01934a-14b7-4037-84c9-e083d74b0a01');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print('Количество записей: {}\\nКоличество признаков: {}'.format(target.shape[0], target.shape[1]))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cZOtKmShT5z5",
        "outputId": "01ffd02b-146d-47e2-980d-19d2aed4a0e1"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Количество записей: 5000\n",
            "Количество признаков: 3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "scale_values_target = target.apply(scale_values).transpose()\n",
        "scale_values_target.columns = [\"type\", \"shape\", \"min\", \"max\", \"uniq_values\"]\n",
        "scale_values_target"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "QGdxLuU2Taxw",
        "outputId": "6670775c-2c13-4468-cb05-3b878b94419c"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             type shape min   max  \\\n",
              "id          int64  5000   0  4999   \n",
              "name       object  5000   -     -   \n",
              "ml_target   int64     2   0     1   \n",
              "\n",
              "                                                 uniq_values  \n",
              "id         [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...  \n",
              "name       [07Gond, 0bman, 0x4f5da2, 0xHJK, 0xchamin, 100...  \n",
              "ml_target                                             [0, 1]  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e001e535-5442-4b06-8b07-99450a3262c0\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>type</th>\n",
              "      <th>shape</th>\n",
              "      <th>min</th>\n",
              "      <th>max</th>\n",
              "      <th>uniq_values</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>id</th>\n",
              "      <td>int64</td>\n",
              "      <td>5000</td>\n",
              "      <td>0</td>\n",
              "      <td>4999</td>\n",
              "      <td>[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>name</th>\n",
              "      <td>object</td>\n",
              "      <td>5000</td>\n",
              "      <td>-</td>\n",
              "      <td>-</td>\n",
              "      <td>[07Gond, 0bman, 0x4f5da2, 0xHJK, 0xchamin, 100...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ml_target</th>\n",
              "      <td>int64</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>[0, 1]</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e001e535-5442-4b06-8b07-99450a3262c0')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-e001e535-5442-4b06-8b07-99450a3262c0 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-e001e535-5442-4b06-8b07-99450a3262c0');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Для большего разнообразия добавим пользователям дополнительные характеристики: пол и возраст. Согласно данным из открытых источников, женщин и мужчин в IT 34% и 66% соответственно, тогда как возраст разработчиков:\n",
        "*   18-24 -> 19,8%\n",
        "*   25-34 -> 63,9%\n",
        "*   35-44 -> 14,1%\n",
        "*   45+ -> 2,2%\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "y9Uvd-qI6Ne4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import random\n",
        "\n",
        "target[\"sex\"] = random.choices([\"0\", \"1\"], weights=[0.66, 0.34], k=target.shape[0]) # Male = 0; Female = 1\n",
        "target"
      ],
      "metadata": {
        "id": "RvJtWxfw6N1n",
        "outputId": "f41712cd-4413-4bcc-d133-1d9c1456d897",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        }
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        id          name  ml_target sex\n",
              "0        0        Eiryyy          0   0\n",
              "1        1    shawflying          0   0\n",
              "2        2   JpMCarrilho          1   0\n",
              "3        3     SuhwanCha          0   1\n",
              "4        4  sunilangadi2          1   1\n",
              "...    ...           ...        ...  ..\n",
              "4995  4995        nicarq          0   1\n",
              "4996  4996  Hansiyuan131          1   1\n",
              "4997  4997     lamabiker          0   1\n",
              "4998  4998  nikos-glikis          0   0\n",
              "4999  4999  jeffstokes72          1   0\n",
              "\n",
              "[5000 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-2e8d578b-8291-4428-a178-cb4657deefe4\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>name</th>\n",
              "      <th>ml_target</th>\n",
              "      <th>sex</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>Eiryyy</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>shawflying</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>JpMCarrilho</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>SuhwanCha</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>sunilangadi2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4995</th>\n",
              "      <td>4995</td>\n",
              "      <td>nicarq</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4996</th>\n",
              "      <td>4996</td>\n",
              "      <td>Hansiyuan131</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4997</th>\n",
              "      <td>4997</td>\n",
              "      <td>lamabiker</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4998</th>\n",
              "      <td>4998</td>\n",
              "      <td>nikos-glikis</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4999</th>\n",
              "      <td>4999</td>\n",
              "      <td>jeffstokes72</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5000 rows × 4 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2e8d578b-8291-4428-a178-cb4657deefe4')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-2e8d578b-8291-4428-a178-cb4657deefe4 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-2e8d578b-8291-4428-a178-cb4657deefe4');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "target[\"age\"] = [random.choices([random.randint(18, 24), random.randint(25, 34), random.randint(35, 44), random.randint(45, 80)], weights=[0.198, 0.639, 0.141, 0.22])[0] for _ in range(target.shape[0])]\n",
        "target"
      ],
      "metadata": {
        "id": "2erj87AzbeXS",
        "outputId": "3b311328-89db-463f-a57b-74e032bd716a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        }
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        id          name  ml_target sex  age\n",
              "0        0        Eiryyy          0   0   58\n",
              "1        1    shawflying          0   0   23\n",
              "2        2   JpMCarrilho          1   0   31\n",
              "3        3     SuhwanCha          0   1   26\n",
              "4        4  sunilangadi2          1   1   26\n",
              "...    ...           ...        ...  ..  ...\n",
              "4995  4995        nicarq          0   1   31\n",
              "4996  4996  Hansiyuan131          1   1   18\n",
              "4997  4997     lamabiker          0   1   50\n",
              "4998  4998  nikos-glikis          0   0   34\n",
              "4999  4999  jeffstokes72          1   0   28\n",
              "\n",
              "[5000 rows x 5 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b67d09c5-ec0b-40ed-a23d-1034fc54515c\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>name</th>\n",
              "      <th>ml_target</th>\n",
              "      <th>sex</th>\n",
              "      <th>age</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>Eiryyy</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>58</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>shawflying</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>JpMCarrilho</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>SuhwanCha</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>sunilangadi2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4995</th>\n",
              "      <td>4995</td>\n",
              "      <td>nicarq</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4996</th>\n",
              "      <td>4996</td>\n",
              "      <td>Hansiyuan131</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4997</th>\n",
              "      <td>4997</td>\n",
              "      <td>lamabiker</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4998</th>\n",
              "      <td>4998</td>\n",
              "      <td>nikos-glikis</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>34</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4999</th>\n",
              "      <td>4999</td>\n",
              "      <td>jeffstokes72</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>28</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5000 rows × 5 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b67d09c5-ec0b-40ed-a23d-1034fc54515c')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "      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",
              "    [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-b67d09c5-ec0b-40ed-a23d-1034fc54515c 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-b67d09c5-ec0b-40ed-a23d-1034fc54515c');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Проверяем, что все данные заполнены."
      ],
      "metadata": {
        "id": "ngjFK6FLe1jv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "target.isna().sum()"
      ],
      "metadata": {
        "id": "PmRXpb77eocJ",
        "outputId": "ca39e9d6-8387-4584-dbb1-9d14e944c61f",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id           0\n",
              "name         0\n",
              "ml_target    0\n",
              "sex          0\n",
              "age          0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Сохраняем данные в csv-файл"
      ],
      "metadata": {
        "id": "iYiE3kjlrIv6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "target.to_csv('/content/drive/My Drive/Colab Notebooks/ml_social_graphs/ml_target.csv')"
      ],
      "metadata": {
        "id": "JhemjKt3mqKB"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Работа со связями** *(musae_git_edges.csv)*"
      ],
      "metadata": {
        "id": "qYE3zanvw2ji"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Посмотрим характеристики набора"
      ],
      "metadata": {
        "id": "2IdlqdOqYF4p"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "edges.head()"
      ],
      "metadata": {
        "id": "y1pHQUfECGe-",
        "outputId": "bdde4e3f-2b8a-4cf2-c232-67b4e4834344",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        }
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   id_1  id_2\n",
              "0     1   237\n",
              "1     1  2383\n",
              "2     3   495\n",
              "3     3  3358\n",
              "4     4  2865"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-da17387c-8daf-4c48-bd16-711cfba896fd\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id_1</th>\n",
              "      <th>id_2</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
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              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>237</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>2383</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>495</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>3358</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>2865</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-da17387c-8daf-4c48-bd16-711cfba896fd')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      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",
              "    [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-da17387c-8daf-4c48-bd16-711cfba896fd 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-da17387c-8daf-4c48-bd16-711cfba896fd');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print('Количество записей: {}\\nКоличество признаков: {}'.format(edges.shape[0], edges.shape[1]))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3705d61f-0cc0-4d91-b330-b3fbcdadfae6",
        "id": "SejEiyY5X5Ms"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Количество записей: 10592\n",
            "Количество признаков: 2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "scale_values_edges = edges.apply(scale_values).transpose()\n",
        "scale_values_edges.columns = [\"type\", \"shape\", \"min\", \"max\", \"uniq_values\"]\n",
        "scale_values_edges"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "outputId": "9c559fd5-f48e-49dd-868c-ff23cf0cb426",
        "id": "GgITQIp0X5M0"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       type shape min   max                                        uniq_values\n",
              "id_1  int64  3027   1  4998  [1, 2, 3, 4, 6, 8, 10, 11, 12, 14, 15, 19, 20,...\n",
              "id_2  int64  2730   1  4994  [1, 5, 6, 7, 8, 9, 11, 12, 18, 19, 21, 22, 23,..."
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-de32709e-6df7-4012-8088-42a79e558eaa\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>type</th>\n",
              "      <th>shape</th>\n",
              "      <th>min</th>\n",
              "      <th>max</th>\n",
              "      <th>uniq_values</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>id_1</th>\n",
              "      <td>int64</td>\n",
              "      <td>3027</td>\n",
              "      <td>1</td>\n",
              "      <td>4998</td>\n",
              "      <td>[1, 2, 3, 4, 6, 8, 10, 11, 12, 14, 15, 19, 20,...</td>\n",
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              "      <th>id_2</th>\n",
              "      <td>int64</td>\n",
              "      <td>2730</td>\n",
              "      <td>1</td>\n",
              "      <td>4994</td>\n",
              "      <td>[1, 5, 6, 7, 8, 9, 11, 12, 18, 19, 21, 22, 23,...</td>\n",
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              "            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",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Исходя из описания данных, связи представляют собой подписки пользователей друг на друга, то есть - ребра неориентированного графа. Так как в дальнейшем эти данные будут использоваться для построения ориентированного графа, необходимо добавить несколько строк, обратных имеющимся, чтобы отобразить взаимную подписку пользователей друг на друга. Возьмем 25% строк случайным образом и поменяем названия колонок местами."
      ],
      "metadata": {
        "id": "M0Pt67W6xL_-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "reverse_edges = edges.sample(frac=0.25, random_state=1).rename(columns={\"id_1\": \"id_2\", \"id_2\": \"id_1\"})\n",
        "reverse_edges.tail()"
      ],
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          "height": 206
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        "id": "8vxOt_ILZZor",
        "outputId": "a64d89b7-2803-4596-a44e-bf7f8a13f2e9"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      id_2  id_1\n",
              "4968  2273  3139\n",
              "2615  1144  3712\n",
              "5065  2281   625\n",
              "7745  3761  3474\n",
              "9247  4664  1701"
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              "\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "  </style>\n",
              "\n",
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              "          const element = document.querySelector('#df-86f261ac-11cd-49a5-9f1c-8578e0f6356f');\n",
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              "            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",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Добавим полученные строки в конец DataFrame"
      ],
      "metadata": {
        "id": "sTYocDEO1eYd"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "edges = pd.concat([edges, reverse_edges], ignore_index=True)\n",
        "edges.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "aBBd9AyDUBBe",
        "outputId": "38fc6e13-7d8d-4a66-c5ca-6365106b3a9e"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   id_1  id_2\n",
              "0     1   237\n",
              "1     1  2383\n",
              "2     3   495\n",
              "3     3  3358\n",
              "4     4  2865"
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              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-074a44ba-1d6e-4209-a76e-c53c806b974a')\"\n",
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              "          const element = document.querySelector('#df-074a44ba-1d6e-4209-a76e-c53c806b974a');\n",
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              "            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",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
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              "    </div>\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "edges.tail()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "rAbpdTPzSqUY",
        "outputId": "7c7280b8-d576-4a77-eea7-bd7541611882"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       id_1  id_2\n",
              "13235  3139  2273\n",
              "13236  3712  1144\n",
              "13237   625  2281\n",
              "13238  3474  3761\n",
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              "      <td>3474</td>\n",
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              "      <td>1701</td>\n",
              "      <td>4664</td>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-89704ab5-9f5d-46a8-b713-f13c93cbcae9')\"\n",
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              "\n",
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              "      background-color: #E2EBFA;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
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              "\n",
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              "          const element = document.querySelector('#df-89704ab5-9f5d-46a8-b713-f13c93cbcae9');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Начало таблицы осталось прежним, а окончание совпадает с последними строками reverse_edges."
      ],
      "metadata": {
        "id": "DbGCwrfk1zHX"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Далее необходимо создать матрицу смежности в виде DataFrame, в котором строки содержат id пользователя-подписчика, id пользователя, на которого подписались, и значение типа bool в зависимости от того, существует ли такая подписка или нет. Для этого добавим в DataFrame существующих связей колонку edge, заполнив ее единицами."
      ],
      "metadata": {
        "id": "tTYyNjGJ2E4F"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "edges[\"edge\"] = 1\n",
        "edges"
      ],
      "metadata": {
        "id": "xLZzP4KqzzvF",
        "outputId": "60a83069-e6a9-41b8-a95f-94f48a7fe5a3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        }
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       id_1  id_2  edge\n",
              "0         1   237     1\n",
              "1         1  2383     1\n",
              "2         3   495     1\n",
              "3         3  3358     1\n",
              "4         4  2865     1\n",
              "...     ...   ...   ...\n",
              "13235  3139  2273     1\n",
              "13236  3712  1144     1\n",
              "13237   625  2281     1\n",
              "13238  3474  3761     1\n",
              "13239  1701  4664     1\n",
              "\n",
              "[13240 rows x 3 columns]"
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              "<p>13240 rows × 3 columns</p>\n",
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              "          const element = document.querySelector('#df-951991e7-eadc-43d2-b09c-632e0a7aca2a');\n",
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              "            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",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Создадим матрицу смежности в виде DataFrame из всех возможных пар пользователей."
      ],
      "metadata": {
        "id": "DvVKbQT43G2K"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "adjacency = pd.DataFrame(target[\"id\"])\n",
        "adjacency = adjacency.merge(adjacency, how=\"cross\")\n",
        "adjacency"
      ],
      "metadata": {
        "id": "z48yiKp41g9N",
        "outputId": "c0732b52-aca7-47f5-aeff-a2a227d78c11",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        }
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          id_x  id_y\n",
              "0            0     0\n",
              "1            0     1\n",
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              "4            0     4\n",
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              "[25000000 rows x 2 columns]"
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-ae7a7efd-26bc-4bb1-a9a8-b0834e4297d3');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "И объединим новую таблицу с таблицей существующих связей, взяв от результата merge список всех пар id и связи."
      ],
      "metadata": {
        "id": "4xeE5iuo3U0S"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "adjacency = adjacency.merge(edges, how=\"left\", left_on=[\"id_x\", \"id_y\"], right_on=[\"id_1\", \"id_2\"], copy=False)\n",
        "adjacency = adjacency[['id_x', 'id_y', 'edge']]\n",
        "adjacency"
      ],
      "metadata": {
        "id": "-47m0D0zVkzd",
        "outputId": "d7d0af1c-4809-4806-dda6-4aad1cd788ad",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        }
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          id_x  id_y  edge\n",
              "0            0     0   NaN\n",
              "1            0     1   NaN\n",
              "2            0     2   NaN\n",
              "3            0     3   NaN\n",
              "4            0     4   NaN\n",
              "...        ...   ...   ...\n",
              "25000010  4999  4995   NaN\n",
              "25000011  4999  4996   NaN\n",
              "25000012  4999  4997   NaN\n",
              "25000013  4999  4998   NaN\n",
              "25000014  4999  4999   NaN\n",
              "\n",
              "[25000015 rows x 3 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-7165b88d-ed51-42b1-8357-2432535f8ddc\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
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              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id_x</th>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
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              "      <td>2</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>NaN</td>\n",
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              "      <th>4</th>\n",
              "      <td>0</td>\n",
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              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>25000010</th>\n",
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              "      <td>4995</td>\n",
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              "    <tr>\n",
              "      <th>25000011</th>\n",
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              "      <td>4996</td>\n",
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              "    <tr>\n",
              "      <th>25000012</th>\n",
              "      <td>4999</td>\n",
              "      <td>4997</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25000013</th>\n",
              "      <td>4999</td>\n",
              "      <td>4998</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>25000014</th>\n",
              "      <td>4999</td>\n",
              "      <td>4999</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>25000015 rows × 3 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7165b88d-ed51-42b1-8357-2432535f8ddc')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
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              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "\n",
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              "      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",
              "    [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-7165b88d-ed51-42b1-8357-2432535f8ddc 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-7165b88d-ed51-42b1-8357-2432535f8ddc');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "У пар, данных о которых не было в исходном файле связей, образовалось значение NaN. Его необходимо заменить на 0."
      ],
      "metadata": {
        "id": "sSN1cbYn35Uk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "adjacency[\"edge\"] = adjacency[\"edge\"].fillna(0)\n",
        "adjacency"
      ],
      "metadata": {
        "id": "MofcDdoT0faa",
        "outputId": "3a0143a3-7c66-45fc-928e-803648464ec7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        }
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          id_x  id_y  edge\n",
              "0            0     0   0.0\n",
              "1            0     1   0.0\n",
              "2            0     2   0.0\n",
              "3            0     3   0.0\n",
              "4            0     4   0.0\n",
              "...        ...   ...   ...\n",
              "25000010  4999  4995   0.0\n",
              "25000011  4999  4996   0.0\n",
              "25000012  4999  4997   0.0\n",
              "25000013  4999  4998   0.0\n",
              "25000014  4999  4999   0.0\n",
              "\n",
              "[25000015 rows x 3 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-99f5f289-77ce-4ca3-9ecf-e7ad3147f1da\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id_x</th>\n",
              "      <th>id_y</th>\n",
              "      <th>edge</th>\n",
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              "  <tbody>\n",
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              "      <th>0</th>\n",
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              "    <tr>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25000010</th>\n",
              "      <td>4999</td>\n",
              "      <td>4995</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>25000011</th>\n",
              "      <td>4999</td>\n",
              "      <td>4996</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25000012</th>\n",
              "      <td>4999</td>\n",
              "      <td>4997</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25000013</th>\n",
              "      <td>4999</td>\n",
              "      <td>4998</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25000014</th>\n",
              "      <td>4999</td>\n",
              "      <td>4999</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>25000015 rows × 3 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-99f5f289-77ce-4ca3-9ecf-e7ad3147f1da')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "      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",
              "    [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-99f5f289-77ce-4ca3-9ecf-e7ad3147f1da 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-99f5f289-77ce-4ca3-9ecf-e7ad3147f1da');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Проверяем, что количество единиц в полученном DataFrame совпадает с числом существующих связей в edges."
      ],
      "metadata": {
        "id": "Qr_balPE4D8J"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "adjacency[\"edge\"].value_counts()[1] == edges.shape[0]"
      ],
      "metadata": {
        "id": "INWPFsWs4aIE",
        "outputId": "9adf5685-344c-48d9-b031-5d644a9ac733",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Проверяем, что все данные заполнены."
      ],
      "metadata": {
        "id": "WEjHZqtPfIlx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "adjacency.isna().sum()"
      ],
      "metadata": {
        "id": "0Ent3TUxnQW6",
        "outputId": "fd34093f-696e-4b5b-a31b-e8e96bcec4f1",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id_x    0\n",
              "id_y    0\n",
              "edge    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Сохраняем данные в csv-файл"
      ],
      "metadata": {
        "id": "dJBrZ1tRrDgC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "adjacency.to_csv('/content/drive/My Drive/Colab Notebooks/ml_social_graphs/ml_adjacency.csv')"
      ],
      "metadata": {
        "id": "RH2ROJyCpmzX"
      },
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Объединение таблиц в один файл**"
      ],
      "metadata": {
        "id": "bmr2rCwoSEFY"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Объединим данные пользователей с таблицей связей для дальнейшего обучения"
      ],
      "metadata": {
        "id": "uyFYcPfLqh-a"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = adjacency.merge(target, how='left', left_on='id_x', right_on='id', copy=False)\n",
        "df = df.drop('id', axis=1)\n",
        "df = df.rename(columns={label:label+'_x' for label in target.columns})\n",
        "df"
      ],
      "metadata": {
        "id": "rnv3qveoS2B1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "outputId": "d2ad11be-323f-403d-ac93-50a6c8b9d897"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "          id_x  id_y  edge        name_x  ml_target_x sex_x  age_x\n",
              "0            0     0   0.0        Eiryyy            0     0     58\n",
              "1            0     1   0.0        Eiryyy            0     0     58\n",
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              "4            0     4   0.0        Eiryyy            0     0     58\n",
              "...        ...   ...   ...           ...          ...   ...    ...\n",
              "25000010  4999  4995   0.0  jeffstokes72            1     0     28\n",
              "25000011  4999  4996   0.0  jeffstokes72            1     0     28\n",
              "25000012  4999  4997   0.0  jeffstokes72            1     0     28\n",
              "25000013  4999  4998   0.0  jeffstokes72            1     0     28\n",
              "25000014  4999  4999   0.0  jeffstokes72            1     0     28\n",
              "\n",
              "[25000015 rows x 7 columns]"
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              "<p>25000015 rows × 7 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8d95f7e9-a67e-452c-b4df-13230e221f53')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "      border-radius: 50%;\n",
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              "      display: none;\n",
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              "      width: 32px;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-8d95f7e9-a67e-452c-b4df-13230e221f53 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-8d95f7e9-a67e-452c-b4df-13230e221f53');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = df.merge(target, how='left', left_on='id_y', right_on='id', copy=False)\n",
        "df = df.drop('id', axis=1)\n",
        "df = df.rename(columns={label:label+'_y' for label in target.columns})\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
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        "id": "og5PAwECf5X_",
        "outputId": "3b6a21a1-fb63-4bb6-d5d9-5d574bf0a891"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          id_x  id_y  edge        name_x  ml_target_x sex_x  age_x  \\\n",
              "0            0     0   0.0        Eiryyy            0     0     58   \n",
              "1            0     1   0.0        Eiryyy            0     0     58   \n",
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              "4            0     4   0.0        Eiryyy            0     0     58   \n",
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              "25000010  4999  4995   0.0  jeffstokes72            1     0     28   \n",
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              "25000012  4999  4997   0.0  jeffstokes72            1     0     28   \n",
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              "25000014  4999  4999   0.0  jeffstokes72            1     0     28   \n",
              "\n",
              "                name_y  ml_target_y sex_y  age_y  \n",
              "0               Eiryyy            0     0     58  \n",
              "1           shawflying            0     0     23  \n",
              "2          JpMCarrilho            1     0     31  \n",
              "3            SuhwanCha            0     1     26  \n",
              "4         sunilangadi2            1     1     26  \n",
              "...                ...          ...   ...    ...  \n",
              "25000010        nicarq            0     1     31  \n",
              "25000011  Hansiyuan131            1     1     18  \n",
              "25000012     lamabiker            0     1     50  \n",
              "25000013  nikos-glikis            0     0     34  \n",
              "25000014  jeffstokes72            1     0     28  \n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6ffee641-a5f2-46bb-87c5-4a68aec844c8')\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      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",
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              "      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",
              "    [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-6ffee641-a5f2-46bb-87c5-4a68aec844c8 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-6ffee641-a5f2-46bb-87c5-4a68aec844c8');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Имя пользователя не влияет на подписки, для вывода результатов же мы можем получить его по id, поэтому удаляем name_x и name_y"
      ],
      "metadata": {
        "id": "CdKerK8yqrnR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = df.drop(['name_x', 'name_y'], axis=1)\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "DxHZziNDqQ-t",
        "outputId": "727ec7de-bef3-4032-b95b-409295a843ed"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   id_x  id_y  edge  ml_target_x sex_x  age_x  ml_target_y sex_y  age_y\n",
              "0     0     0   0.0            0     0     58            0     0     58\n",
              "1     0     1   0.0            0     0     58            0     0     23\n",
              "2     0     2   0.0            0     0     58            1     0     31\n",
              "3     0     3   0.0            0     0     58            0     1     26\n",
              "4     0     4   0.0            0     0     58            1     1     26"
            ],
            "text/html": [
              "\n",
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              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
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              "\n",
              "    .dataframe thead th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
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              "      <th>id_x</th>\n",
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              "      <th>edge</th>\n",
              "      <th>ml_target_x</th>\n",
              "      <th>sex_x</th>\n",
              "      <th>age_x</th>\n",
              "      <th>ml_target_y</th>\n",
              "      <th>sex_y</th>\n",
              "      <th>age_y</th>\n",
              "    </tr>\n",
              "  </thead>\n",
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              "      <th>0</th>\n",
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              "      <td>26</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-70516b9d-c7a5-4245-8119-24e26e1660e6')\"\n",
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              "              style=\"display:none;\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
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              "    .colab-df-convert {\n",
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              "\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "    [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-70516b9d-c7a5-4245-8119-24e26e1660e6 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-70516b9d-c7a5-4245-8119-24e26e1660e6');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Проверяем, что все данные заполнены."
      ],
      "metadata": {
        "id": "mxIFv87RrAaM"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.isna().sum()"
      ],
      "metadata": {
        "outputId": "27d6f4d7-c06e-4d7b-ebc8-d672ae154593",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vbLVUOJCrAaN"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id_x           0\n",
              "id_y           0\n",
              "edge           0\n",
              "ml_target_x    0\n",
              "sex_x          0\n",
              "age_x          0\n",
              "ml_target_y    0\n",
              "sex_y          0\n",
              "age_y          0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Посмотрим характеристики набора"
      ],
      "metadata": {
        "id": "RlYZa9J6rg20"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print('Количество записей: {}\\nКоличество признаков: {}'.format(df.shape[0], df.shape[1]))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "10571ca8-a881-431a-ba2a-c13d0aa3a362",
        "id": "yUDxeSJyrMLk"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Количество записей: 25000015\n",
            "Количество признаков: 9\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "scale_values_df = df.apply(scale_values).transpose()\n",
        "scale_values_df.columns = [\"type\", \"shape\", \"min\", \"max\", \"uniq_values\"]\n",
        "scale_values_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 331
        },
        "outputId": "701540f1-6ad6-4c8d-f8bf-b995b6d6721b",
        "id": "qW7QCeMprMLr"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                type shape  min   max  \\\n",
              "id_x           int64  5000    0  4999   \n",
              "id_y           int64  5000    0  4999   \n",
              "edge         float64     2  0.0   1.0   \n",
              "ml_target_x    int64     2    0     1   \n",
              "sex_x         object     2    -     -   \n",
              "age_x          int64    63   18    80   \n",
              "ml_target_y    int64     2    0     1   \n",
              "sex_y         object     2    -     -   \n",
              "age_y          int64    63   18    80   \n",
              "\n",
              "                                                   uniq_values  \n",
              "id_x         [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...  \n",
              "id_y         [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...  \n",
              "edge                                                [0.0, 1.0]  \n",
              "ml_target_x                                             [0, 1]  \n",
              "sex_x                                                   [0, 1]  \n",
              "age_x        [18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 2...  \n",
              "ml_target_y                                             [0, 1]  \n",
              "sex_y                                                   [0, 1]  \n",
              "age_y        [18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 2...  "
            ],
            "text/html": [
              "\n",
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              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>type</th>\n",
              "      <th>shape</th>\n",
              "      <th>min</th>\n",
              "      <th>max</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>id_x</th>\n",
              "      <td>int64</td>\n",
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              "      <td>[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...</td>\n",
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              "      <th>id_y</th>\n",
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              "    </tr>\n",
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              "      <td>[0.0, 1.0]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ml_target_x</th>\n",
              "      <td>int64</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex_x</th>\n",
              "      <td>object</td>\n",
              "      <td>2</td>\n",
              "      <td>-</td>\n",
              "      <td>-</td>\n",
              "      <td>[0, 1]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>age_x</th>\n",
              "      <td>int64</td>\n",
              "      <td>63</td>\n",
              "      <td>18</td>\n",
              "      <td>80</td>\n",
              "      <td>[18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 2...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ml_target_y</th>\n",
              "      <td>int64</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>[0, 1]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex_y</th>\n",
              "      <td>object</td>\n",
              "      <td>2</td>\n",
              "      <td>-</td>\n",
              "      <td>-</td>\n",
              "      <td>[0, 1]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>age_y</th>\n",
              "      <td>int64</td>\n",
              "      <td>63</td>\n",
              "      <td>18</td>\n",
              "      <td>80</td>\n",
              "      <td>[18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 2...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-cdb84894-85d8-488f-bb86-2e6ba2d04114')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-cdb84894-85d8-488f-bb86-2e6ba2d04114 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-cdb84894-85d8-488f-bb86-2e6ba2d04114');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "        }\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Сохраняем данные в csv-файл"
      ],
      "metadata": {
        "id": "MVLf6YIkrAaN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.to_csv('/content/drive/My Drive/Colab Notebooks/ml_social_graphs/dataframe.csv')"
      ],
      "metadata": {
        "id": "KBeZXf-vnTEl"
      },
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "t0qu32w3neAg"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}