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      "source": [
        "#23_MarketBasketAnalysisusingAPIRIORI\n",
        "### Importing the basic libraries\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "### Load Dataset from Local Directory\n",
        "from google.colab import files\n",
        "uploaded = files.upload()\n",
        "### Importing the dataset\n",
        "dataset = pd.read_csv('dataset.csv')\n",
        "print(dataset.shape)\n",
        "print(dataset.head(5))\n",
        "### Data Pre-Processing using vectorized operations\n",
        "# Extract the relevant columns (assuming first 20)\n",
        "transactions_df = dataset.iloc[:, :20]\n",
        "# Convert all values to strings\n",
        "transactions_df = transactions_df.astype(str)\n",
        "# Convert DataFrame to list of lists\n",
        "transactions = transactions_df.values.tolist()\n",
        "### Training APRIORI\n",
        "!pip install apyori\n",
        "from apyori import apriori\n",
        "rules = apriori(transactions = transactions, min_support = 0.003, min_confidence = 0.2, min_lift = 3, min_length = 2, max_length = 2)\n",
        "### Result\n",
        "results = list(rules)\n",
        "results\n",
        "### Results in Dataframe\n",
        "lhs         = [tuple(result[2][0][0])[0] for result in results]\n",
        "rhs         = [tuple(result[2][0][1])[0] for result in results]\n",
        "supports    = [result[1] for result in results]\n",
        "confidences = [result[2][0][2] for result in results]\n",
        "lifts       = [result[2][0][3] for result in results]\n",
        "resultsinDataFrame = pd.DataFrame(zip(lhs, rhs, supports, confidences, lifts), columns = ['Left Hand Side', 'Right Hand Side', 'Support', 'Confidence', 'Lift'])\n",
        "resultsinDataFrame"
      ],
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              "// See the License for the specific language governing permissions and\n",
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          "text": [
            "Saving dataset.csv to dataset.csv\n",
            "(7500, 20)\n",
            "           shrimp    almonds     avocado    vegetables mix green grapes  \\\n",
            "0         burgers  meatballs        eggs               NaN          NaN   \n",
            "1         chutney        NaN         NaN               NaN          NaN   \n",
            "2          turkey    avocado         NaN               NaN          NaN   \n",
            "3   mineral water       milk  energy bar  whole wheat rice    green tea   \n",
            "4  low fat yogurt        NaN         NaN               NaN          NaN   \n",
            "\n",
            "  whole weat flour yams cottage cheese energy drink tomato juice  \\\n",
            "0              NaN  NaN            NaN          NaN          NaN   \n",
            "1              NaN  NaN            NaN          NaN          NaN   \n",
            "2              NaN  NaN            NaN          NaN          NaN   \n",
            "3              NaN  NaN            NaN          NaN          NaN   \n",
            "4              NaN  NaN            NaN          NaN          NaN   \n",
            "\n",
            "  low fat yogurt green tea honey salad mineral water salmon antioxydant juice  \\\n",
            "0            NaN       NaN   NaN   NaN           NaN    NaN               NaN   \n",
            "1            NaN       NaN   NaN   NaN           NaN    NaN               NaN   \n",
            "2            NaN       NaN   NaN   NaN           NaN    NaN               NaN   \n",
            "3            NaN       NaN   NaN   NaN           NaN    NaN               NaN   \n",
            "4            NaN       NaN   NaN   NaN           NaN    NaN               NaN   \n",
            "\n",
            "  frozen smoothie spinach  olive oil  \n",
            "0             NaN     NaN        NaN  \n",
            "1             NaN     NaN        NaN  \n",
            "2             NaN     NaN        NaN  \n",
            "3             NaN     NaN        NaN  \n",
            "4             NaN     NaN        NaN  \n",
            "Collecting apyori\n",
            "  Downloading apyori-1.1.2.tar.gz (8.6 kB)\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Building wheels for collected packages: apyori\n",
            "  Building wheel for apyori (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for apyori: filename=apyori-1.1.2-py3-none-any.whl size=5954 sha256=6f460bf2d21945572fd7d1a90d9524bf5c416704c59847856c42f2fb0d60d484\n",
            "  Stored in directory: /root/.cache/pip/wheels/77/3d/a6/d317a6fb32be58a602b1e8c6b5d6f31f79322da554cad2a5ea\n",
            "Successfully built apyori\n",
            "Installing collected packages: apyori\n",
            "Successfully installed apyori-1.1.2\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         Left Hand Side Right Hand Side   Support  Confidence      Lift\n",
              "0           light cream         chicken  0.004533    0.290598  4.843305\n",
              "1  mushroom cream sauce        escalope  0.005733    0.300699  3.790327\n",
              "2                 pasta        escalope  0.005867    0.372881  4.700185\n",
              "3         fromage blanc           honey  0.003333    0.245098  5.178128\n",
              "4         herb & pepper     ground beef  0.016000    0.323450  3.291555\n",
              "5          tomato sauce     ground beef  0.005333    0.377358  3.840147\n",
              "6           light cream       olive oil  0.003200    0.205128  3.120612\n",
              "7     whole wheat pasta       olive oil  0.008000    0.271493  4.130221\n",
              "8                 pasta          shrimp  0.005067    0.322034  4.514494"
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              "      <th>Left Hand Side</th>\n",
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              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-99413864-1e27-4eff-b893-b72424d2b6a1 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_608141c4-567b-4f50-88d6-7182c8a13969\">\n",
              "    <style>\n",
              "      .colab-df-generate {\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-generate: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-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate: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",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('resultsinDataFrame')\"\n",
              "            title=\"Generate code using this dataframe.\"\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=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_608141c4-567b-4f50-88d6-7182c8a13969 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('resultsinDataFrame');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "resultsinDataFrame",
              "summary": "{\n  \"name\": \"resultsinDataFrame\",\n  \"rows\": 9,\n  \"fields\": [\n    {\n      \"column\": \"Left Hand Side\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 7,\n        \"samples\": [\n          \"light cream\",\n          \"mushroom cream sauce\",\n          \"tomato sauce\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Right Hand Side\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 6,\n        \"samples\": [\n          \"chicken\",\n          \"escalope\",\n          \"shrimp\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Support\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.003896500487537852,\n        \"min\": 0.0032,\n        \"max\": 0.016,\n        \"num_unique_values\": 9,\n        \"samples\": [\n          0.008,\n          0.005733333333333333,\n          0.005333333333333333\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Confidence\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.056168653549259547,\n        \"min\": 0.20512820512820515,\n        \"max\": 0.37735849056603776,\n        \"num_unique_values\": 9,\n        \"samples\": [\n          0.2714932126696833,\n          0.30069930069930073,\n          0.37735849056603776\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Lift\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.7066844698506499,\n        \"min\": 3.120611639881417,\n        \"max\": 5.178127589063795,\n        \"num_unique_values\": 9,\n        \"samples\": [\n          4.130221288078346,\n          3.7903273197390845,\n          3.840147461662528\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "rj5duez_ERkd"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}