Apriori_삼겹살과_쌈장의_관계.ipynb

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      "name": "Apriori 삼겹살과 쌈장의 관계.ipynb",
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      "source": [
        "# Apriori 분석에 필요한 라이브러리 설치\n",
        "import pandas as pd\n",
        "from mlxtend.preprocessing import TransactionEncoder\n",
        "from mlxtend.frequent_patterns import apriori, association_rules"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataset = [\n",
        "           ['삼겹살', '쌈장', '콜라'],\n",
        "           ['항정살', '상추'],\n",
        "           ['사이다', '콜라'],\n",
        "           ['삼겹살', '쌈장', '사이다'],\n",
        "           ['삼겹살', '쌈장', '상추'],\n",
        "           ['항정살', '쌈장', '상추'],\n",
        "           ['삼겹살', '항정살', '쌈장', '상추', '콜라']\n",
        "]"
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      "source": [
        "te = TransactionEncoder()\n",
        "te_ary = te.fit(dataset). transform(dataset)\n",
        "df = pd.DataFrame(te_ary, columns=te.columns_) #array를 보기좋게 DF로 변경"
      ],
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              "     사이다    삼겹살     상추     쌈장     콜라    항정살\n",
              "0  False   True  False   True   True  False\n",
              "1  False  False   True  False  False   True\n",
              "2   True  False  False  False   True  False\n",
              "3   True   True  False   True  False  False\n",
              "4  False   True   True   True  False  False\n",
              "5  False  False   True   True  False   True\n",
              "6  False   True   True   True   True   True"
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        "# 지지도(Support) 최소지지도 = 0.5\n",
        "frequent_itemsets = apriori(df, use_colnames=True)\n",
        "frequent_itemsets"
      ],
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              "    support   itemsets\n",
              "0  0.571429      (삼겹살)\n",
              "1  0.571429       (상추)\n",
              "2  0.714286       (쌈장)\n",
              "3  0.571429  (삼겹살, 쌈장)"
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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",
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              "      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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              "    }\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-e280dbab-ad68-4c3d-b720-49da32d01950 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-e280dbab-ad68-4c3d-b720-49da32d01950');\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",
              "  "
            ],
            "text/plain": [
              "    support   itemsets\n",
              "2  0.714286       (쌈장)\n",
              "0  0.571429      (삼겹살)\n",
              "1  0.571429       (상추)\n",
              "5  0.571429  (삼겹살, 쌈장)\n",
              "3  0.428571       (콜라)\n",
              "4  0.428571      (항정살)\n",
              "6  0.428571   (쌈장, 상추)\n",
              "7  0.428571  (항정살, 상추)"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 신뢰도(Confidence) 와 향상도(lift)\n",
        "association_rules(frequent_itemsets, metric=\"confidence\") "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 162
        },
        "id": "_EkcCjQuyXvx",
        "outputId": "9aec870c-90be-406b-fb40-d7c7ccbf12d9"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-a41a1fba-c630-47c6-ada0-ab35135e33e4\">\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>antecedents</th>\n",
              "      <th>consequents</th>\n",
              "      <th>antecedent support</th>\n",
              "      <th>consequent support</th>\n",
              "      <th>support</th>\n",
              "      <th>confidence</th>\n",
              "      <th>lift</th>\n",
              "      <th>leverage</th>\n",
              "      <th>conviction</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>(삼겹살)</td>\n",
              "      <td>(쌈장)</td>\n",
              "      <td>0.571429</td>\n",
              "      <td>0.714286</td>\n",
              "      <td>0.571429</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.163265</td>\n",
              "      <td>inf</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a41a1fba-c630-47c6-ada0-ab35135e33e4')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "      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-a41a1fba-c630-47c6-ada0-ab35135e33e4 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-a41a1fba-c630-47c6-ada0-ab35135e33e4');\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",
              "  "
            ],
            "text/plain": [
              "  antecedents consequents  antecedent support  ...  lift  leverage  conviction\n",
              "0       (삼겹살)        (쌈장)            0.571429  ...   1.4  0.163265         inf\n",
              "\n",
              "[1 rows x 9 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "association_rules(frequent_itemsets, metric=\"confidence\", min_threshold=0.3) \n",
        "# antecedent support & consequent support 뭘까?\n",
        "# 아! 알아냄 >> \n",
        "# 첫번째 행을 기준으로 각 선행사건(삼겹살), 이후에 일어난 사건(쌈장)의 지지도이다.\n",
        "# support는 {삼겹살, 쌈장}의 집합 지지도"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 193
        },
        "id": "37NLEDmN3FXL",
        "outputId": "72bfcf9a-11f8-4e65-aad0-0171917bf9c0"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-30cd299f-4cda-4b63-8dde-f8e3fb1d57af\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "    }\n",
              "\n",
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              "        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>antecedents</th>\n",
              "      <th>consequents</th>\n",
              "      <th>antecedent support</th>\n",
              "      <th>consequent support</th>\n",
              "      <th>support</th>\n",
              "      <th>confidence</th>\n",
              "      <th>lift</th>\n",
              "      <th>leverage</th>\n",
              "      <th>conviction</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>(삼겹살)</td>\n",
              "      <td>(쌈장)</td>\n",
              "      <td>0.571429</td>\n",
              "      <td>0.714286</td>\n",
              "      <td>0.571429</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.163265</td>\n",
              "      <td>inf</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>(쌈장)</td>\n",
              "      <td>(삼겹살)</td>\n",
              "      <td>0.714286</td>\n",
              "      <td>0.571429</td>\n",
              "      <td>0.571429</td>\n",
              "      <td>0.8</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.163265</td>\n",
              "      <td>2.142857</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-30cd299f-4cda-4b63-8dde-f8e3fb1d57af')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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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",
              "      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-30cd299f-4cda-4b63-8dde-f8e3fb1d57af 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-30cd299f-4cda-4b63-8dde-f8e3fb1d57af');\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",
              "  "
            ],
            "text/plain": [
              "  antecedents consequents  antecedent support  ...  lift  leverage  conviction\n",
              "0       (삼겹살)        (쌈장)            0.571429  ...   1.4  0.163265         inf\n",
              "1        (쌈장)       (삼겹살)            0.714286  ...   1.4  0.163265    2.142857\n",
              "\n",
              "[2 rows x 9 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "http://rasbt.github.io/mlxtend/api_subpackages/mlxtend.frequent_patterns/"
      ],
      "metadata": {
        "id": "HmYrcJwT3J-r"
      }
    }
  ]
}