Apriori_code.ipynb

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        "id": "atvBgUDCIg7z"
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      "source": [
        "\n",
        "# READING DATASET"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ukwumkcxIqDY"
      },
      "outputs": [],
      "source": [
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "5Tap-ZWmIuzM"
      },
      "outputs": [],
      "source": [
        "#reading dataset from url\n",
        "dataset = pd.read_csv('https://raw.githubusercontent.com/okzapradhana/simple-apriori-algorithm/master/dataset_apriori.csv')"
      ]
    },
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              "   tid                               items\n",
              "0    1                    Handphone,Laptop\n",
              "1    2            Handphone,Charger,Laptop\n",
              "2    3  Powerbank,Laptop,Charger,Handphone\n",
              "3    4             Tablet,Laptop,Handphone\n",
              "4    5            Handphone,Charger,Tablet\n",
              "5    6                    Tablet,Powerbank\n",
              "6    7     Handphone,Laptop,Tablet,Charger\n",
              "7    8                   Charger,Handphone\n",
              "8    9                 Handphone,Powerbank\n",
              "9   10            Laptop,Charger,Powerbank"
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              "      <td>Handphone,Laptop</td>\n",
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              "      <td>Handphone,Charger,Laptop</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>Powerbank,Laptop,Charger,Handphone</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>Tablet,Laptop,Handphone</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>Handphone,Charger,Tablet</td>\n",
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              "      <th>5</th>\n",
              "      <td>6</td>\n",
              "      <td>Tablet,Powerbank</td>\n",
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              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>7</td>\n",
              "      <td>Handphone,Laptop,Tablet,Charger</td>\n",
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              "    <tr>\n",
              "      <th>7</th>\n",
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      "source": [
        "dataset"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pY6aLSUhJFdc"
      },
      "source": [
        "# SPLITTING DATASET"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "0HmTa_dNI_bT"
      },
      "outputs": [],
      "source": [
        "#splitting tid and items columns of df into two different dataframe\n",
        "df_items = dataset['items']\n",
        "df_tid = dataset['tid']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0                      Handphone,Laptop\n",
              "1              Handphone,Charger,Laptop\n",
              "2    Powerbank,Laptop,Charger,Handphone\n",
              "3               Tablet,Laptop,Handphone\n",
              "4              Handphone,Charger,Tablet\n",
              "5                      Tablet,Powerbank\n",
              "6       Handphone,Laptop,Tablet,Charger\n",
              "7                     Charger,Handphone\n",
              "8                   Handphone,Powerbank\n",
              "9              Laptop,Charger,Powerbank\n",
              "Name: items, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ],
      "source": [
        "df_items"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "PQX3bduQJcww",
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          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6df19d4c-cc64-44b3-af92-1e7113518084"
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      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0     1\n",
              "1     2\n",
              "2     3\n",
              "3     4\n",
              "4     5\n",
              "5     6\n",
              "6     7\n",
              "7     8\n",
              "8     9\n",
              "9    10\n",
              "Name: tid, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ],
      "source": [
        "df_tid"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OZNYF8NaJsZL"
      },
      "source": [
        "# Convert Items to Number"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "v6whzEUoJnO_"
      },
      "outputs": [],
      "source": [
        "#assigning unique index for different unique items\n",
        "dictionaries = {'Handphone': 1, 'Laptop': 2, 'Charger': 3, 'Powerbank': 4, 'Tablet': 5 }"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jiUgv4E2J4w7"
      },
      "outputs": [],
      "source": [
        "comma_splitted_df = df_items.apply(lambda x: x.split(','))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
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        "colab": {
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        },
        "id": "VLkA81CSJ6-Q",
        "outputId": "5713347a-f283-4632-b897-39419e7e2b8c"
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      "outputs": [
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          "data": {
            "text/plain": [
              "0                        [Handphone, Laptop]\n",
              "1               [Handphone, Charger, Laptop]\n",
              "2    [Powerbank, Laptop, Charger, Handphone]\n",
              "3                [Tablet, Laptop, Handphone]\n",
              "4               [Handphone, Charger, Tablet]\n",
              "5                        [Tablet, Powerbank]\n",
              "6       [Handphone, Laptop, Tablet, Charger]\n",
              "7                       [Charger, Handphone]\n",
              "8                     [Handphone, Powerbank]\n",
              "9               [Laptop, Charger, Powerbank]\n",
              "Name: items, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ],
      "source": [
        "comma_splitted_df"
      ]
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        "id": "Y_uKZMs_J_GS",
        "outputId": "3477fb57-abfe-4488-e340-1fd65432e1ad"
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          "data": {
            "text/plain": [
              "[[1, 2],\n",
              " [1, 2, 3],\n",
              " [1, 2, 3, 4],\n",
              " [1, 2, 5],\n",
              " [1, 3, 5],\n",
              " [4, 5],\n",
              " [1, 2, 3, 5],\n",
              " [1, 3],\n",
              " [1, 4],\n",
              " [2, 3, 4]]"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ],
      "source": [
        "numbered_col = []\n",
        "for i in range(len(comma_splitted_df)):\n",
        "    list_numbered = list(map(lambda x: dictionaries[x], comma_splitted_df[i]))\n",
        "    sort_numbered = sorted(list_numbered)\n",
        "    numbered_col.append(sort_numbered)\n",
        "\n",
        "numbered_col"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sxa8YAWsKEAe"
      },
      "source": [
        "# Create Dataframe from Numbered Items"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "6OALvQPhKADN"
      },
      "outputs": [],
      "source": [
        "#creating dataframe of numbered_col\n",
        "dict_data = {'items': numbered_col}\n",
        "df = pd.DataFrame.from_dict(dict_data)"
      ]
    },
    {
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              "          items\n",
              "0        [1, 2]\n",
              "1     [1, 2, 3]\n",
              "2  [1, 2, 3, 4]\n",
              "3     [1, 2, 5]\n",
              "4     [1, 3, 5]\n",
              "5        [4, 5]\n",
              "6  [1, 2, 3, 5]\n",
              "7        [1, 3]\n",
              "8        [1, 4]\n",
              "9     [2, 3, 4]"
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              "            '<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
        }
      ],
      "source": [
        "df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cZyDIqn1KNgI",
        "outputId": "02a6fc3d-c6ed-4212-a8a3-927f53ed6c66"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   tid         items\n",
              "0    1        [1, 2]\n",
              "1    2     [1, 2, 3]\n",
              "2    3  [1, 2, 3, 4]\n",
              "3    4     [1, 2, 5]\n",
              "4    5     [1, 3, 5]\n",
              "5    6        [4, 5]\n",
              "6    7  [1, 2, 3, 5]\n",
              "7    8        [1, 3]\n",
              "8    9        [1, 4]\n",
              "9   10     [2, 3, 4]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-1758dd03-9998-4214-9bbb-a9dd182dcfff\">\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>tid</th>\n",
              "      <th>items</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>[1, 2]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>[1, 2, 3]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>[1, 2, 3, 4]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>[1, 2, 5]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>[1, 3, 5]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>6</td>\n",
              "      <td>[4, 5]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>7</td>\n",
              "      <td>[1, 2, 3, 5]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>8</td>\n",
              "      <td>[1, 3]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>9</td>\n",
              "      <td>[1, 4]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>10</td>\n",
              "      <td>[2, 3, 4]</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1758dd03-9998-4214-9bbb-a9dd182dcfff')\"\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",
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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",
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              "\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-1758dd03-9998-4214-9bbb-a9dd182dcfff 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-1758dd03-9998-4214-9bbb-a9dd182dcfff');\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": 13
        }
      ],
      "source": [
        "pd.concat([df_tid, df], axis=1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DitFDerrKn8T",
        "outputId": "c2a906de-0d88-4ea0-889a-5569a12a71dc"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[1,\n",
              " 2,\n",
              " 1,\n",
              " 2,\n",
              " 3,\n",
              " 1,\n",
              " 2,\n",
              " 3,\n",
              " 4,\n",
              " 1,\n",
              " 2,\n",
              " 5,\n",
              " 1,\n",
              " 3,\n",
              " 5,\n",
              " 4,\n",
              " 5,\n",
              " 1,\n",
              " 2,\n",
              " 3,\n",
              " 5,\n",
              " 1,\n",
              " 3,\n",
              " 1,\n",
              " 4,\n",
              " 2,\n",
              " 3,\n",
              " 4]"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ],
      "source": [
        "items = []\n",
        "for i in range(len(df)):\n",
        "    for j in range(len(df['items'][i])):\n",
        "        items.append(df['items'][i][j])\n",
        "items"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "j9HQ2_f7Kr2E"
      },
      "source": [
        "# Creating First Candidate (C1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OnAYrPluKu0z",
        "outputId": "ec989de5-e663-4a22-c13b-6a9e3c61dc16"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{1, 2, 3, 4, 5}"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ],
      "source": [
        "#Get unique element from list/array\n",
        "unique_item = set(items)\n",
        "unique_item"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tpHH8k5HKu6z",
        "outputId": "9ef32f9f-6e4a-4ba4-9258-28d1789da079"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[1, 2, 3, 4, 5]"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ],
      "source": [
        "#Convert it to list\n",
        "list_unique_item = list(unique_item)\n",
        "list_unique_item"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lVt5q4CSK1s_",
        "outputId": "9d2e601f-f280-45c8-e17b-ff68282e4996"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[(1, 8), (2, 6), (3, 6), (4, 4), (5, 4)]"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ],
      "source": [
        "#counting frequency of every unique items\n",
        "count_unique = []\n",
        "for value in (list_unique_item):\n",
        "    count_unique.append((value, items.count(value)))\n",
        "count_unique"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "5aZguSyvK2VB"
      },
      "outputs": [],
      "source": [
        "candidate1_df = pd.DataFrame(count_unique, columns=[\"itemset\", \"sup\"])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "m2uGWvHtK74K",
        "outputId": "e5b5adc1-505c-4af4-e81e-0381877615ed"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   itemset  sup\n",
              "0        1    8\n",
              "1        2    6\n",
              "2        3    6\n",
              "3        4    4\n",
              "4        5    4"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-d6638358-a90f-47be-91f1-14c8440554a0\">\n",
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "      <th></th>\n",
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              "      <th>sup</th>\n",
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              "  <tbody>\n",
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              "      <th>0</th>\n",
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              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>6</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d6638358-a90f-47be-91f1-14c8440554a0')\"\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",
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              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
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              "    .colab-df-container {\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "\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-d6638358-a90f-47be-91f1-14c8440554a0 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-d6638358-a90f-47be-91f1-14c8440554a0');\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": 19
        }
      ],
      "source": [
        "candidate1_df"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MiRw5GuXLAtj"
      },
      "source": [
        "# Creating first Frequent Itemset (L1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "YL9odS_kK9YE"
      },
      "outputs": [],
      "source": [
        "#filtering items having minimum support count 2\n",
        "def filter_sup(candidate):\n",
        "    minimum_sup = 2\n",
        "    filtering = candidate['sup'] > minimum_sup\n",
        "    freq = candidate[filtering]\n",
        "    return freq"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "rnoyj_WeLIyp"
      },
      "outputs": [],
      "source": [
        "freq_itemset1 = filter_sup(candidate1_df)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ymucOAqCLLwH",
        "outputId": "473a3d45-a43d-4842-aaaa-cce456cff0b3"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   itemset  sup\n",
              "0        1    8\n",
              "1        2    6\n",
              "2        3    6\n",
              "3        4    4\n",
              "4        5    4"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-dc8e2d82-7459-49c1-80f3-9a54b8d130f7\">\n",
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "      <th></th>\n",
              "      <th>itemset</th>\n",
              "      <th>sup</th>\n",
              "    </tr>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-dc8e2d82-7459-49c1-80f3-9a54b8d130f7')\"\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",
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              "    <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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              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "    }\n",
              "\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-dc8e2d82-7459-49c1-80f3-9a54b8d130f7 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-dc8e2d82-7459-49c1-80f3-9a54b8d130f7');\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
        }
      ],
      "source": [
        "freq_itemset1"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sU5sUCMwLU23"
      },
      "source": [
        "# Create the Second Candidate (C2)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sjMUMbD7-lvk"
      },
      "source": [
        "**SELF JOIN**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "blVQalZmLXlL"
      },
      "outputs": [],
      "source": [
        "import numpy\n",
        "def self_join(prev_freq_itemset):\n",
        "    self_join_candidate = []\n",
        "    for i in range(len(prev_freq_itemset['itemset'])):\n",
        "        for j in range((i+1), len(prev_freq_itemset['itemset'])):\n",
        "            itemset_i = prev_freq_itemset['itemset'][i]\n",
        "            itemset_j = prev_freq_itemset['itemset'][j]\n",
        "            if(type(itemset_i) == numpy.int64 and type(itemset_j) == numpy.int64):\n",
        "                itemset_i = {itemset_i}\n",
        "                itemset_j = {itemset_j}\n",
        "            union_candidate = itemset_i.union(itemset_j)\n",
        "\n",
        "            if union_candidate not in self_join_candidate:\n",
        "                self_join_candidate.append(union_candidate)\n",
        "    return self_join_candidate"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "OruCnauELkwF"
      },
      "outputs": [],
      "source": [
        "candidate2_list = self_join(freq_itemset1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LEg0HTqvLpkS",
        "outputId": "26640ff9-dd0b-469f-d0ab-624514ae32cf"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{1, 2},\n",
              " {1, 3},\n",
              " {1, 4},\n",
              " {1, 5},\n",
              " {2, 3},\n",
              " {2, 4},\n",
              " {2, 5},\n",
              " {3, 4},\n",
              " {3, 5},\n",
              " {4, 5}]"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ],
      "source": [
        "candidate2_list"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6iRpnpIUOKsX",
        "outputId": "0009b135-8a6f-409b-f3af-ac39f19588ce"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[({1, 2}, 0),\n",
              " ({1, 3}, 0),\n",
              " ({1, 4}, 0),\n",
              " ({1, 5}, 0),\n",
              " ({2, 3}, 0),\n",
              " ({2, 4}, 0),\n",
              " ({2, 5}, 0),\n",
              " ({3, 4}, 0),\n",
              " ({3, 5}, 0),\n",
              " ({4, 5}, 0)]"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ],
      "source": [
        "count_candidate2 = []\n",
        "\n",
        "#Set the Initial value of Second Count Candidate (C2)\n",
        "for i in range(len(candidate2_list)):\n",
        "    count_candidate2.append((candidate2_list[i], 0))\n",
        "\n",
        "count_candidate2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "uFlSQrb0OL5w"
      },
      "outputs": [],
      "source": [
        "initial_df_candidate = pd.DataFrame(count_candidate2, columns=['itemset', 'sup'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "FmXAW1B3OPn2",
        "outputId": "b5f0d7d7-5726-4a03-c9e6-1df042144a88"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  itemset  sup\n",
              "0  {1, 2}    0\n",
              "1  {1, 3}    0\n",
              "2  {1, 4}    0\n",
              "3  {1, 5}    0\n",
              "4  {2, 3}    0\n",
              "5  {2, 4}    0\n",
              "6  {2, 5}    0\n",
              "7  {3, 4}    0\n",
              "8  {3, 5}    0\n",
              "9  {4, 5}    0"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-4492788a-5342-4cda-82fd-f1adf997bb31\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "        text-align: right;\n",
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              "</style>\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>itemset</th>\n",
              "      <th>sup</th>\n",
              "    </tr>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>{1, 2}</td>\n",
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              "      <td>{3, 5}</td>\n",
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              "      <th>9</th>\n",
              "      <td>{4, 5}</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4492788a-5342-4cda-82fd-f1adf997bb31')\"\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",
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              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "\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-4492788a-5342-4cda-82fd-f1adf997bb31 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-4492788a-5342-4cda-82fd-f1adf997bb31');\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
        }
      ],
      "source": [
        "initial_df_candidate"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "SeaTNDnQOWKG",
        "outputId": "7c42ec16-697f-43ae-c087-499a1578072f"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          items\n",
              "0        [1, 2]\n",
              "1     [1, 2, 3]\n",
              "2  [1, 2, 3, 4]\n",
              "3     [1, 2, 5]\n",
              "4     [1, 3, 5]\n",
              "5        [4, 5]\n",
              "6  [1, 2, 3, 5]\n",
              "7        [1, 3]\n",
              "8        [1, 4]\n",
              "9     [2, 3, 4]"
            ],
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              "\n",
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              "      <td>[1, 2]</td>\n",
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              "      <td>[1, 2, 3]</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>[1, 2, 3, 4]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>[1, 2, 5]</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>[1, 3, 5]</td>\n",
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              "      <th>6</th>\n",
              "      <td>[1, 2, 3, 5]</td>\n",
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              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>[1, 3]</td>\n",
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              "      <th>8</th>\n",
              "      <td>[1, 4]</td>\n",
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              "      <th>9</th>\n",
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              "              style=\"display:none;\">\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [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-80b9faf0-2fc8-4160-9529-6d913e4aeb03 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-80b9faf0-2fc8-4160-9529-6d913e4aeb03');\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
        }
      ],
      "source": [
        "df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "xYcPm3HeOV_M"
      },
      "outputs": [],
      "source": [
        "#Let's add it with 1 whenever we found every candidate is a subset from Database D\n",
        "\n",
        "\n",
        "def count_support(database_dataframe, prev_candidate_list):\n",
        "    #initial_df_candidate['sup'] = 0 #set All value into 0 only for initial value for consistency value when running this cell everytime.\n",
        "    count_prev_candidate = []\n",
        "\n",
        "    #Set the Initial value of Previous Candidate\n",
        "    for i in range(len(prev_candidate_list)):\n",
        "        count_prev_candidate.append((prev_candidate_list[i], 0))\n",
        "    \n",
        "    df_candidate = pd.DataFrame(count_prev_candidate, columns=['itemset', 'sup'])\n",
        "    print('Database D dataframe\\n', database_dataframe)\n",
        "    print('(Initial) Dataframe from Candidate with All zeros sup\\n', df_candidate)\n",
        "    \n",
        "    for i in range(len(database_dataframe)):\n",
        "        for j in range(len(count_prev_candidate)):\n",
        "            #using issubset() function to check whether every itemset is a subset of Database or not\n",
        "            if (df_candidate['itemset'][j]).issubset(set(database_dataframe['items'][i])): \n",
        "                df_candidate.loc[j, 'sup'] += 1\n",
        "            \n",
        "    return df_candidate"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Uhl6KzHmOVFl",
        "outputId": "5a4477aa-9d05-43d1-bf60-2c219a2989be"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Database D dataframe\n",
            "           items\n",
            "0        [1, 2]\n",
            "1     [1, 2, 3]\n",
            "2  [1, 2, 3, 4]\n",
            "3     [1, 2, 5]\n",
            "4     [1, 3, 5]\n",
            "5        [4, 5]\n",
            "6  [1, 2, 3, 5]\n",
            "7        [1, 3]\n",
            "8        [1, 4]\n",
            "9     [2, 3, 4]\n",
            "(Initial) Dataframe from Candidate with All zeros sup\n",
            "   itemset  sup\n",
            "0  {1, 2}    0\n",
            "1  {1, 3}    0\n",
            "2  {1, 4}    0\n",
            "3  {1, 5}    0\n",
            "4  {2, 3}    0\n",
            "5  {2, 4}    0\n",
            "6  {2, 5}    0\n",
            "7  {3, 4}    0\n",
            "8  {3, 5}    0\n",
            "9  {4, 5}    0\n"
          ]
        }
      ],
      "source": [
        "count_candidate2_df = count_support(df, candidate2_list)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "bnNeWQt9OnBY",
        "outputId": "0eb694ab-ba21-41a3-df74-649e3529c896"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  itemset  sup\n",
              "0  {1, 2}    5\n",
              "1  {1, 3}    5\n",
              "2  {1, 4}    2\n",
              "3  {1, 5}    3\n",
              "4  {2, 3}    4\n",
              "5  {2, 4}    2\n",
              "6  {2, 5}    2\n",
              "7  {3, 4}    2\n",
              "8  {3, 5}    2\n",
              "9  {4, 5}    1"
            ],
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              "\n",
              "  <div id=\"df-a4d23e68-74e8-4faa-8046-4552db349e26\">\n",
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              "<style scoped>\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>itemset</th>\n",
              "      <th>sup</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>{1, 2}</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>{1, 3}</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>{1, 4}</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>{1, 5}</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>{2, 3}</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>{2, 4}</td>\n",
              "      <td>2</td>\n",
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              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>{2, 5}</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>{3, 4}</td>\n",
              "      <td>2</td>\n",
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              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>{3, 5}</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>{4, 5}</td>\n",
              "      <td>1</td>\n",
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              "  </style>\n",
              "\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a4d23e68-74e8-4faa-8046-4552db349e26');\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",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ],
      "source": [
        "count_candidate2_df"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dhDcp3NtOsG7"
      },
      "source": [
        "# Creating Second Frequent Itemset (L2)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ZRuXhPfOOn-K"
      },
      "outputs": [],
      "source": [
        "#Filter the itemset based on minimum support (occurences of items)\n",
        "freq_itemset2 = filter_sup(count_candidate2_df)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "HjZ591GUOoTV",
        "outputId": "b726925a-ef1b-4311-e0f7-3ed9396877e8"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  itemset  sup\n",
              "0  {1, 2}    5\n",
              "1  {1, 3}    5\n",
              "3  {1, 5}    3\n",
              "4  {2, 3}    4"
            ],
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              "\n",
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              "      <div>\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>itemset</th>\n",
              "      <th>sup</th>\n",
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              "      <th>0</th>\n",
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              "      <th>4</th>\n",
              "      <td>{2, 3}</td>\n",
              "      <td>4</td>\n",
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              "      background-color: #E2EBFA;\n",
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              "      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-c6b615ee-db4b-44ca-b7f2-2effc3b27810 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-c6b615ee-db4b-44ca-b7f2-2effc3b27810');\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": 34
        }
      ],
      "source": [
        "freq_itemset2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "qgyFDm9rO471"
      },
      "outputs": [],
      "source": [
        "freq_itemset2_reset = freq_itemset2.reset_index(drop=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "WdmNTFPiv0ZK",
        "outputId": "36c19562-a49a-44e6-f67b-64a22b37dc2d"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  itemset  sup\n",
              "0  {1, 2}    5\n",
              "1  {1, 3}    5\n",
              "2  {1, 5}    3\n",
              "3  {2, 3}    4"
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              "    }\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>itemset</th>\n",
              "      <th>sup</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>{1, 2}</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>{1, 3}</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>{1, 5}</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>{2, 3}</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c3ae3e9c-13b1-4fe3-aa48-97a03e045c9a')\"\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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              "      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-c3ae3e9c-13b1-4fe3-aa48-97a03e045c9a 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-c3ae3e9c-13b1-4fe3-aa48-97a03e045c9a');\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": 36
        }
      ],
      "source": [
        "#We need to reset the index, because need to access the index later.\n",
        "freq_itemset2_reset"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UbtbEeesO-sI"
      },
      "source": [
        "# Creating the Third Candidate (C3) - Using the Candidate Forming Technique"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sFjKs7d9PIL0"
      },
      "source": [
        "**SELF JOIN**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HmXyVR9iO4vy",
        "outputId": "6a794f9f-e7f7-424a-ec9b-86fdcdfbf08c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "  itemset  sup\n",
            "0  {1, 2}    5\n",
            "1  {1, 3}    5\n",
            "2  {1, 5}    3\n",
            "3  {2, 3}    4\n",
            "self join result\n",
            "[{1, 2, 3}, {1, 2, 5}, {1, 3, 5}, {1, 2, 3, 5}]\n"
          ]
        }
      ],
      "source": [
        "print(freq_itemset2_reset)\n",
        "self_join_result = self_join(freq_itemset2_reset)\n",
        "print('self join result')\n",
        "print(self_join_result)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "i01u_ogOPYGc"
      },
      "source": [
        "**PRUNING**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "t22MCoWdO4KK"
      },
      "outputs": [],
      "source": [
        "def get_subset(candidate):\n",
        "    temp = []\n",
        "    final = []\n",
        "    for i in range(len(candidate)):\n",
        "        for j in range(len(candidate)):\n",
        "            if i != j:\n",
        "                temp.append(candidate[j])\n",
        "        temp_set = set(temp)\n",
        "        final.append(temp_set)\n",
        "        temp.clear()\n",
        "    print('Subset from {} : {}'.format(candidate, final))\n",
        "    return final\n",
        "\n",
        "def pruning(candidate_set, prev_freq_itemset):\n",
        "    print('Candidate set', candidate_set)\n",
        "    temp = []\n",
        "    \n",
        "    for idx, value in enumerate(candidate_set):\n",
        "        list_candidate = list(value)\n",
        "        temp_candidate = (get_subset(list_candidate))\n",
        "        \n",
        "        for temp_item in temp_candidate:\n",
        "            print('Temp item', temp_item)\n",
        "            check = temp_item == prev_freq_itemset['itemset']\n",
        "            print('\\nCheck candidate from Previous Frequent Itemset\\n', check)\n",
        "            \n",
        "            if any(check) == False:\n",
        "                print(any(check))\n",
        "                print('Val', value)\n",
        "            else:\n",
        "                print('\\nAll of {} subset contained in \\n{}'.format(candidate_set, prev_freq_itemset))\n",
        "                if value not in temp:\n",
        "                    temp.append(value)\n",
        "                \n",
        "    return temp"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "KQbOkOo6PePf",
        "outputId": "530f3b86-22a9-4f21-d72a-af86e43ba873"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  itemset  sup\n",
              "0  {1, 2}    5\n",
              "1  {1, 3}    5\n",
              "2  {1, 5}    3\n",
              "3  {2, 3}    4"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-8abbdab9-2c1e-4054-a34d-cc4e337db684\">\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>itemset</th>\n",
              "      <th>sup</th>\n",
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              "      <th>0</th>\n",
              "      <td>{1, 2}</td>\n",
              "      <td>5</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>{1, 3}</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>{1, 5}</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>{2, 3}</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8abbdab9-2c1e-4054-a34d-cc4e337db684')\"\n",
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              "              style=\"display:none;\">\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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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
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              "    }\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-8abbdab9-2c1e-4054-a34d-cc4e337db684 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-8abbdab9-2c1e-4054-a34d-cc4e337db684');\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": 39
        }
      ],
      "source": [
        "freq_itemset2_reset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "1oPF7yibPidW"
      },
      "outputs": [],
      "source": [
        "subset = [{2, 3}, {1, 3}, {1, 2}]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "l7HxUmbfPigc",
        "outputId": "4d057fb5-8dea-422c-bc69-9b3d8e61546f"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{1, 2, 3}, {1, 2, 5}, {1, 3, 5}, {1, 2, 3, 5}]"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ],
      "source": [
        "self_join_result"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7ac0UQB3PijG",
        "outputId": "5e362fc4-9fb6-40b3-aa22-06a7334a1c1e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Subset from [1, 2, 3] : [{2, 3}, {1, 3}, {1, 2}]\n",
            "Subset from [1, 2, 5] : [{2, 5}, {1, 5}, {1, 2}]\n",
            "Subset from [1, 3, 5] : [{3, 5}, {1, 5}, {1, 3}]\n",
            "Subset from [1, 2, 3, 5] : [{2, 3, 5}, {1, 3, 5}, {1, 2, 5}, {1, 2, 3}]\n"
          ]
        }
      ],
      "source": [
        "for i in range(len(self_join_result)):\n",
        "    get_subset(list(self_join_result[i]))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "uX8z4T0QPimp",
        "outputId": "e10fdbc4-c002-48d7-fa24-60441af60b12"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  itemset  sup\n",
              "0  {1, 2}    5\n",
              "1  {1, 3}    5\n",
              "2  {1, 5}    3\n",
              "3  {2, 3}    4"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5a69bade-7400-4cc6-8cc9-168c50662e52\">\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>itemset</th>\n",
              "      <th>sup</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>{1, 2}</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>{1, 3}</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>{1, 5}</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>{2, 3}</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5a69bade-7400-4cc6-8cc9-168c50662e52')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\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",
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              "      padding: 0 0 0 0;\n",
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              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      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-5a69bade-7400-4cc6-8cc9-168c50662e52 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-5a69bade-7400-4cc6-8cc9-168c50662e52');\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": 43
        }
      ],
      "source": [
        "freq_itemset2_reset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "a2e-UEZyPeZ9",
        "outputId": "5f3711c2-763e-4116-cf86-332005aac3f5"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{2, 3}\n",
            "Check True\n",
            "{1, 3}\n",
            "Check True\n",
            "{1, 2}\n",
            "Check True\n"
          ]
        }
      ],
      "source": [
        "for item in subset:\n",
        "    print(item)\n",
        "    check = item == freq_itemset2_reset['itemset']\n",
        "    print('Check', any(check))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1Ebrzwe7PzSE",
        "outputId": "023e03dd-2e2f-400b-bd6b-013255c86ecd"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{1, 2, 3}, {1, 2, 5}, {1, 3, 5}, {1, 2, 3, 5}]"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ],
      "source": [
        "self_join_result"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GNM8mqeKPzVf",
        "outputId": "8a724c5a-b7b2-406e-e50f-5d629addb87a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Candidate set [{1, 2, 3}, {1, 2, 5}, {1, 3, 5}, {1, 2, 3, 5}]\n",
            "Subset from [1, 2, 3] : [{2, 3}, {1, 3}, {1, 2}]\n",
            "Temp item {2, 3}\n",
            "\n",
            "Check candidate from Previous Frequent Itemset\n",
            " 0    False\n",
            "1    False\n",
            "2    False\n",
            "3     True\n",
            "Name: itemset, dtype: bool\n",
            "\n",
            "All of [{1, 2, 3}, {1, 2, 5}, {1, 3, 5}, {1, 2, 3, 5}] subset contained in \n",
            "  itemset  sup\n",
            "0  {1, 2}    5\n",
            "1  {1, 3}    5\n",
            "2  {1, 5}    3\n",
            "3  {2, 3}    4\n",
            "Temp item {1, 3}\n",
            "\n",
            "Check candidate from Previous Frequent Itemset\n",
            " 0    False\n",
            "1     True\n",
            "2    False\n",
            "3    False\n",
            "Name: itemset, dtype: bool\n",
            "\n",
            "All of [{1, 2, 3}, {1, 2, 5}, {1, 3, 5}, {1, 2, 3, 5}] subset contained in \n",
            "  itemset  sup\n",
            "0  {1, 2}    5\n",
            "1  {1, 3}    5\n",
            "2  {1, 5}    3\n",
            "3  {2, 3}    4\n",
            "Temp item {1, 2}\n",
            "\n",
            "Check candidate from Previous Frequent Itemset\n",
            " 0     True\n",
            "1    False\n",
            "2    False\n",
            "3    False\n",
            "Name: itemset, dtype: bool\n",
            "\n",
            "All of [{1, 2, 3}, {1, 2, 5}, {1, 3, 5}, {1, 2, 3, 5}] subset contained in \n",
            "  itemset  sup\n",
            "0  {1, 2}    5\n",
            "1  {1, 3}    5\n",
            "2  {1, 5}    3\n",
            "3  {2, 3}    4\n",
            "Subset from [1, 2, 5] : [{2, 5}, {1, 5}, {1, 2}]\n",
            "Temp item {2, 5}\n",
            "\n",
            "Check candidate from Previous Frequent Itemset\n",
            " 0    False\n",
            "1    False\n",
            "2    False\n",
            "3    False\n",
            "Name: itemset, dtype: bool\n",
            "False\n",
            "Val {1, 2, 5}\n",
            "Temp item {1, 5}\n",
            "\n",
            "Check candidate from Previous Frequent Itemset\n",
            " 0    False\n",
            "1    False\n",
            "2     True\n",
            "3    False\n",
            "Name: itemset, dtype: bool\n",
            "\n",
            "All of [{1, 2, 3}, {1, 2, 5}, {1, 3, 5}, {1, 2, 3, 5}] subset contained in \n",
            "  itemset  sup\n",
            "0  {1, 2}    5\n",
            "1  {1, 3}    5\n",
            "2  {1, 5}    3\n",
            "3  {2, 3}    4\n",
            "Temp item {1, 2}\n",
            "\n",
            "Check candidate from Previous Frequent Itemset\n",
            " 0     True\n",
            "1    False\n",
            "2    False\n",
            "3    False\n",
            "Name: itemset, dtype: bool\n",
            "\n",
            "All of [{1, 2, 3}, {1, 2, 5}, {1, 3, 5}, {1, 2, 3, 5}] subset contained in \n",
            "  itemset  sup\n",
            "0  {1, 2}    5\n",
            "1  {1, 3}    5\n",
            "2  {1, 5}    3\n",
            "3  {2, 3}    4\n",
            "Subset from [1, 3, 5] : [{3, 5}, {1, 5}, {1, 3}]\n",
            "Temp item {3, 5}\n",
            "\n",
            "Check candidate from Previous Frequent Itemset\n",
            " 0    False\n",
            "1    False\n",
            "2    False\n",
            "3    False\n",
            "Name: itemset, dtype: bool\n",
            "False\n",
            "Val {1, 3, 5}\n",
            "Temp item {1, 5}\n",
            "\n",
            "Check candidate from Previous Frequent Itemset\n",
            " 0    False\n",
            "1    False\n",
            "2     True\n",
            "3    False\n",
            "Name: itemset, dtype: bool\n",
            "\n",
            "All of [{1, 2, 3}, {1, 2, 5}, {1, 3, 5}, {1, 2, 3, 5}] subset contained in \n",
            "  itemset  sup\n",
            "0  {1, 2}    5\n",
            "1  {1, 3}    5\n",
            "2  {1, 5}    3\n",
            "3  {2, 3}    4\n",
            "Temp item {1, 3}\n",
            "\n",
            "Check candidate from Previous Frequent Itemset\n",
            " 0    False\n",
            "1     True\n",
            "2    False\n",
            "3    False\n",
            "Name: itemset, dtype: bool\n",
            "\n",
            "All of [{1, 2, 3}, {1, 2, 5}, {1, 3, 5}, {1, 2, 3, 5}] subset contained in \n",
            "  itemset  sup\n",
            "0  {1, 2}    5\n",
            "1  {1, 3}    5\n",
            "2  {1, 5}    3\n",
            "3  {2, 3}    4\n",
            "Subset from [1, 2, 3, 5] : [{2, 3, 5}, {1, 3, 5}, {1, 2, 5}, {1, 2, 3}]\n",
            "Temp item {2, 3, 5}\n",
            "\n",
            "Check candidate from Previous Frequent Itemset\n",
            " 0    False\n",
            "1    False\n",
            "2    False\n",
            "3    False\n",
            "Name: itemset, dtype: bool\n",
            "False\n",
            "Val {1, 2, 3, 5}\n",
            "Temp item {1, 3, 5}\n",
            "\n",
            "Check candidate from Previous Frequent Itemset\n",
            " 0    False\n",
            "1    False\n",
            "2    False\n",
            "3    False\n",
            "Name: itemset, dtype: bool\n",
            "False\n",
            "Val {1, 2, 3, 5}\n",
            "Temp item {1, 2, 5}\n",
            "\n",
            "Check candidate from Previous Frequent Itemset\n",
            " 0    False\n",
            "1    False\n",
            "2    False\n",
            "3    False\n",
            "Name: itemset, dtype: bool\n",
            "False\n",
            "Val {1, 2, 3, 5}\n",
            "Temp item {1, 2, 3}\n",
            "\n",
            "Check candidate from Previous Frequent Itemset\n",
            " 0    False\n",
            "1    False\n",
            "2    False\n",
            "3    False\n",
            "Name: itemset, dtype: bool\n",
            "False\n",
            "Val {1, 2, 3, 5}\n"
          ]
        }
      ],
      "source": [
        "candidate3_list = pruning(self_join_result, freq_itemset2_reset)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cI4HX3sCPzYn",
        "outputId": "38c57d66-bc23-4376-ae84-cdc71bbc7853"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{1, 2, 3}, {1, 2, 5}, {1, 3, 5}]"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ],
      "source": [
        "candidate3_list"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7jh-tp6UQVNH"
      },
      "source": [
        "# Creating the Third Frequent Itemset (L3)"
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "VlDSP6LdQBUi"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "y2HIp50zPzbg",
        "outputId": "64977852-e6d6-450f-cd49-bfd6754d0d9a"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          items\n",
              "0        [1, 2]\n",
              "1     [1, 2, 3]\n",
              "2  [1, 2, 3, 4]\n",
              "3     [1, 2, 5]\n",
              "4     [1, 3, 5]\n",
              "5        [4, 5]\n",
              "6  [1, 2, 3, 5]\n",
              "7        [1, 3]\n",
              "8        [1, 4]\n",
              "9     [2, 3, 4]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b1cad363-d9ea-4c40-8945-af4230cec74a\">\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>items</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>[1, 2]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>[1, 2, 3]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>[1, 2, 3, 4]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>[1, 2, 5]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>[1, 3, 5]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>[4, 5]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>[1, 2, 3, 5]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>[1, 3]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>[1, 4]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>[2, 3, 4]</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b1cad363-d9ea-4c40-8945-af4230cec74a')\"\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",
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              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\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-b1cad363-d9ea-4c40-8945-af4230cec74a 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-b1cad363-d9ea-4c40-8945-af4230cec74a');\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": 48
        }
      ],
      "source": [
        "#Let's see the database again\n",
        "df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xF_DmJVBPze7",
        "outputId": "8a0cb900-1dba-49b3-da20-102e3b7f876f"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{1, 2, 3}, {1, 2, 5}, {1, 3, 5}]"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ],
      "source": [
        "#Then check the newest candidate value\n",
        "candidate3_list"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cjA-83JrQmR-",
        "outputId": "a54d816e-a2af-4e7f-fc4b-47cf0026773c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Database D dataframe\n",
            "           items\n",
            "0        [1, 2]\n",
            "1     [1, 2, 3]\n",
            "2  [1, 2, 3, 4]\n",
            "3     [1, 2, 5]\n",
            "4     [1, 3, 5]\n",
            "5        [4, 5]\n",
            "6  [1, 2, 3, 5]\n",
            "7        [1, 3]\n",
            "8        [1, 4]\n",
            "9     [2, 3, 4]\n",
            "(Initial) Dataframe from Candidate with All zeros sup\n",
            "      itemset  sup\n",
            "0  {1, 2, 3}    0\n",
            "1  {1, 2, 5}    0\n",
            "2  {1, 3, 5}    0\n"
          ]
        }
      ],
      "source": [
        "count_candidate3_df = count_support(df, candidate3_list)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i3Ln0yR4Qmgg",
        "outputId": "0991dc0c-d982-4214-d584-3704b84b3662"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     itemset  sup\n",
              "0  {1, 2, 3}    3\n",
              "1  {1, 2, 5}    2\n",
              "2  {1, 3, 5}    2"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-82717a8a-3e85-4611-a368-a16426d26eaf\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
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              "</style>\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>itemset</th>\n",
              "      <th>sup</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>{1, 2, 3}</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>{1, 2, 5}</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>{1, 3, 5}</td>\n",
              "      <td>2</td>\n",
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              "                                                     [key], {});\n",
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              "\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": 51
        }
      ],
      "source": [
        "count_candidate3_df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "tM2a356hQmk4"
      },
      "outputs": [],
      "source": [
        "freq_itemset3 = filter_sup(count_candidate3_df)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EA_51hUIQmoS",
        "outputId": "6c2ea41b-1d19-4560-bf08-aefcd81ffd28"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     itemset  sup\n",
              "0  {1, 2, 3}    3"
            ],
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              "      <th>0</th>\n",
              "      <td>{1, 2, 3}</td>\n",
              "      <td>3</td>\n",
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              "  </tbody>\n",
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              "\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-5005c543-3bff-489b-926b-5d2dc410091f');\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",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 53
        }
      ],
      "source": [
        "freq_itemset3"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6onKjTKERI-M"
      },
      "source": [
        "#All Frequent Itemset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IWY-KT8CQ6AV",
        "outputId": "b4cb2549-9db8-49a7-a269-343271e6fff5"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   itemset  sup\n",
              "0        1    8\n",
              "1        2    6\n",
              "2        3    6\n",
              "3        4    4\n",
              "4        5    4"
            ],
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              "      <th>3</th>\n",
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              "      <td>4</td>\n",
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              "      <th>4</th>\n",
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              "              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",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "\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-1556b1d6-4b47-4dbf-b6f1-a87322c1f80b 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-1556b1d6-4b47-4dbf-b6f1-a87322c1f80b');\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": 54
        }
      ],
      "source": [
        "#Let'see each frequent itemset (L)\n",
        "freq_itemset1"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qyRnygmeQ6Dq",
        "outputId": "93f4650d-ec81-45cc-9941-6b0018d1e698"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  itemset  sup\n",
              "0  {1, 2}    5\n",
              "1  {1, 3}    5\n",
              "3  {1, 5}    3\n",
              "4  {2, 3}    4"
            ],
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              "<style scoped>\n",
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              "\n",
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              "      <th>sup</th>\n",
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              "      <th>0</th>\n",
              "      <td>{1, 2}</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>{1, 3}</td>\n",
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              "      <th>3</th>\n",
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              "      <td>3</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>{2, 3}</td>\n",
              "      <td>4</td>\n",
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              "       width=\"24px\">\n",
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              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "\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",
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              "\n",
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              "        const buttonEl =\n",
              "          document.querySelector('#df-eda320fc-d29b-4346-87ed-75cb0ff818de 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-eda320fc-d29b-4346-87ed-75cb0ff818de');\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": 55
        }
      ],
      "source": [
        "freq_itemset2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hzoPPFSdQ6HM",
        "outputId": "7776d21f-516f-4a02-9ae0-ace564c7ded1"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     itemset  sup\n",
              "0  {1, 2, 3}    3"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-baf4941d-13cf-4760-9e71-5950240b36f7\">\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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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>itemset</th>\n",
              "      <th>sup</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>{1, 2, 3}</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-baf4941d-13cf-4760-9e71-5950240b36f7')\"\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",
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              "    <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",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "    }\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",
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              "\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-baf4941d-13cf-4760-9e71-5950240b36f7 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-baf4941d-13cf-4760-9e71-5950240b36f7');\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": 56
        }
      ],
      "source": [
        "freq_itemset3"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Y2xJe5GoQ6Pl"
      },
      "outputs": [],
      "source": [
        "frequent_itemset = pd.concat([freq_itemset1, freq_itemset2, freq_itemset3], axis=0)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "g6PVZL3QQ6X0",
        "outputId": "fa74e8cf-2066-426b-c72d-5c99598d4d3a"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     itemset  sup\n",
              "0          1    8\n",
              "1          2    6\n",
              "2          3    6\n",
              "3          4    4\n",
              "4          5    4\n",
              "0     {1, 2}    5\n",
              "1     {1, 3}    5\n",
              "3     {1, 5}    3\n",
              "4     {2, 3}    4\n",
              "0  {1, 2, 3}    3"
            ],
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              "\n",
              "  <div id=\"df-224bfcfd-0034-465b-a41f-380698eba5a5\">\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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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>itemset</th>\n",
              "      <th>sup</th>\n",
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              "      <th>0</th>\n",
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              "      <th>4</th>\n",
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              "      <td>4</td>\n",
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              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>{1, 2}</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>{1, 3}</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
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              "      <th>4</th>\n",
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              "      <th>0</th>\n",
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              "      <td>3</td>\n",
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              "       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-224bfcfd-0034-465b-a41f-380698eba5a5 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-224bfcfd-0034-465b-a41f-380698eba5a5');\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": 58
        }
      ],
      "source": [
        "frequent_itemset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "-34t1cG-Rw1N"
      },
      "outputs": [],
      "source": [
        "#Reset the index\n",
        "frequent_itemset_final = frequent_itemset.reset_index(drop=True)"
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "yQIp1HB1P_R9"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cdFw-6CMR-R-"
      },
      "source": [
        "#Final Output of Freq. Itemset (L1-L3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "v_TMvD8kRw4Y",
        "outputId": "0fe705ab-e109-4ec6-8000-3672858a675d"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     itemset  sup\n",
              "0          1    8\n",
              "1          2    6\n",
              "2          3    6\n",
              "3          4    4\n",
              "4          5    4\n",
              "5     {1, 2}    5\n",
              "6     {1, 3}    5\n",
              "7     {1, 5}    3\n",
              "8     {2, 3}    4\n",
              "9  {1, 2, 3}    3"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a01eac94-e2e6-46e0-9aac-372959ac110b\">\n",
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              "      <div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "</style>\n",
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              "      <th></th>\n",
              "      <th>itemset</th>\n",
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              "      <th>0</th>\n",
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              "      <th>5</th>\n",
              "      <td>{1, 2}</td>\n",
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              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>{1, 3}</td>\n",
              "      <td>5</td>\n",
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              "      <td>{1, 5}</td>\n",
              "      <td>3</td>\n",
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              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>{2, 3}</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>{1, 2, 3}</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a01eac94-e2e6-46e0-9aac-372959ac110b')\"\n",
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              "      gap: 12px;\n",
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              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "          document.querySelector('#df-a01eac94-e2e6-46e0-9aac-372959ac110b 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-a01eac94-e2e6-46e0-9aac-372959ac110b');\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",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 60
        }
      ],
      "source": [
        "frequent_itemset_final"
      ]
    }
  ],
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    "kernelspec": {
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    "language_info": {
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