iris_flower_classification.ipynb

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              "   sepal_length  sepal_width  petal_length  petal_width species\n",
              "0           5.1          3.5           1.4          0.2  setosa\n",
              "1           4.9          3.0           1.4          0.2  setosa\n",
              "2           4.7          3.2           1.3          0.2  setosa\n",
              "3           4.6          3.1           1.5          0.2  setosa\n",
              "4           5.0          3.6           1.4          0.2  setosa"
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              "summary": "{\n  \"name\": \"iris\",\n  \"rows\": 150,\n  \"fields\": [\n    {\n      \"column\": \"sepal_length\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.828066127977863,\n        \"min\": 4.3,\n        \"max\": 7.9,\n        \"num_unique_values\": 35,\n        \"samples\": [\n          6.2,\n          4.5,\n          5.6\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"sepal_width\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.4358662849366982,\n        \"min\": 2.0,\n        \"max\": 4.4,\n        \"num_unique_values\": 23,\n        \"samples\": [\n          2.3,\n          4.0,\n          3.5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"petal_length\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.7652982332594662,\n        \"min\": 1.0,\n        \"max\": 6.9,\n        \"num_unique_values\": 43,\n        \"samples\": [\n          6.7,\n          3.8,\n          3.7\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"petal_width\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.7622376689603465,\n        \"min\": 0.1,\n        \"max\": 2.5,\n        \"num_unique_values\": 22,\n        \"samples\": [\n          0.2,\n          1.2,\n          1.3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"species\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"setosa\",\n          \"versicolor\",\n          \"virginica\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
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          "metadata": {},
          "execution_count": 4
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      "source": [
        "# Import libraries for classification taskimport numpy as np\n",
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.metrics import accuracy_score , confusion_matrix , classification_report\n",
        "from sklearn.metrics import precision_score, recall_score, f1_score\n",
        "\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "\n",
        "#Remove warnings\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')\n",
        "\n",
        "iris = sns.load_dataset('iris')\n",
        "iris.head()"
      ]
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      "source": [
        "#correlation matrix\n",
        "numerical_columns = iris.select_dtypes(include=['number'])\n",
        "correlation_matrix = numerical_columns.corr()\n",
        "correlation_matrix"
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              "              sepal_length  sepal_width  petal_length  petal_width\n",
              "sepal_length      1.000000    -0.117570      0.871754     0.817941\n",
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              "      const buttonEl =\n",
              "        document.querySelector('#df-eb77f8d8-67f9-4935-b6d2-c97802c04683 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-eb77f8d8-67f9-4935-b6d2-c97802c04683');\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",
              "\n",
              "\n",
              "<div id=\"df-d40f113b-bf3a-4b6f-9663-62e9800bf616\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-d40f113b-bf3a-4b6f-9663-62e9800bf616')\"\n",
              "            title=\"Suggest charts\"\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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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<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-d40f113b-bf3a-4b6f-9663-62e9800bf616 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_da619368-f5d2-46b7-8675-d19f6b1785d9\">\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('correlation_matrix')\"\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_da619368-f5d2-46b7-8675-d19f6b1785d9 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('correlation_matrix');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "correlation_matrix",
              "summary": "{\n  \"name\": \"correlation_matrix\",\n  \"rows\": 4,\n  \"fields\": [\n    {\n      \"column\": \"sepal_length\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.5127858813273581,\n        \"min\": -0.11756978413300088,\n        \"max\": 1.0,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          -0.11756978413300088,\n          0.8179411262715758,\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"sepal_width\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.6657080809503223,\n        \"min\": -0.42844010433053864,\n        \"max\": 1.0,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          1.0,\n          -0.3661259325364377,\n          -0.11756978413300088\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"petal_length\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.6887672414981271,\n        \"min\": -0.42844010433053864,\n        \"max\": 1.0,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          -0.42844010433053864,\n          0.962865431402796,\n          0.8717537758865838\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"petal_width\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.6512846518377995,\n        \"min\": -0.3661259325364377,\n        \"max\": 1.0,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          -0.3661259325364377,\n          1.0,\n          0.8179411262715758\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "iris.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "O9-FRmaGiiBU",
        "outputId": "0ead3f04-844d-4764-ff7d-e5802acddf1d"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 150 entries, 0 to 149\n",
            "Data columns (total 5 columns):\n",
            " #   Column        Non-Null Count  Dtype  \n",
            "---  ------        --------------  -----  \n",
            " 0   sepal_length  150 non-null    float64\n",
            " 1   sepal_width   150 non-null    float64\n",
            " 2   petal_length  150 non-null    float64\n",
            " 3   petal_width   150 non-null    float64\n",
            " 4   species       150 non-null    object \n",
            "dtypes: float64(4), object(1)\n",
            "memory usage: 6.0+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "iris['petal_width'].hist()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        },
        "id": "jIIFqWvDmcAY",
        "outputId": "0e48a09b-410b-4433-dcae-65709cc0dc78"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 30
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "iris['petal_length'].hist()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        },
        "id": "Yei_bcCvlnvV",
        "outputId": "6550335e-2b0d-485a-b3e9-c5c53ef8c0a8"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 27
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "iris['sepal_length'].hist()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        },
        "id": "ZTKoj8XNmWfl",
        "outputId": "7e33dfc9-e710-4c3a-c769-75fabfb5d558"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 28
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "iris['sepal_width'].hist()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        },
        "id": "O7BCd-yBmZiw",
        "outputId": "720d3e8e-d476-4c0b-c889-5e2dbfe65a62"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 29
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "iris['species'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ws8Wvy6EkFqs",
        "outputId": "5640e144-bf67-465f-df4c-97811c5b4016"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "species\n",
              "setosa        50\n",
              "versicolor    50\n",
              "virginica     50\n",
              "Name: count, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.set_style(\"whitegrid\")\n",
        "sns.FacetGrid(iris, hue =\"species\",\n",
        "\t\t\theight = 6).map(plt.scatter,\n",
        "\t\t\t\t\t\t\t'sepal_length',\n",
        "\t\t\t\t\t\t\t'petal_length').add_legend()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 624
        },
        "id": "lKU7cYZRiCtO",
        "outputId": "a354f667-7654-4bb9-9c6f-7bdb0b1c1732"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x789f00c46b60>"
            ]
          },
          "metadata": {},
          "execution_count": 14
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 717.75x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.set_style(\"whitegrid\")\n",
        "sns.FacetGrid(iris, hue =\"species\",\n",
        "\t\t\theight = 6).map(plt.scatter,\n",
        "\t\t\t\t\t\t\t'sepal_width',\n",
        "\t\t\t\t\t\t\t'petal_width').add_legend()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 624
        },
        "id": "fpdMqES1m37u",
        "outputId": "d4cf543b-9532-457a-9ff3-415d60902b39"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x789f00cca6e0>"
            ]
          },
          "metadata": {},
          "execution_count": 31
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 717.75x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.set_style(\"whitegrid\")\n",
        "sns.FacetGrid(iris, hue =\"species\",\n",
        "\t\t\theight = 6).map(plt.scatter,\n",
        "\t\t\t\t\t\t\t'sepal_length',\n",
        "\t\t\t\t\t\t\t'sepal_width').add_legend()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 624
        },
        "id": "aKdQ4lfGnIEW",
        "outputId": "16b930e4-6de2-4f51-cfb1-582557c36354"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x789eff6d3e20>"
            ]
          },
          "metadata": {},
          "execution_count": 32
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 717.75x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.set_style(\"whitegrid\")\n",
        "sns.FacetGrid(iris, hue =\"species\",\n",
        "\t\t\theight = 6).map(plt.scatter,\n",
        "\t\t\t\t\t\t\t'petal_width',\n",
        "\t\t\t\t\t\t\t'petal_length').add_legend()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 624
        },
        "id": "MhAFUBAznR7N",
        "outputId": "ca1372f7-ed1f-4cce-81b0-ee913728b295"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x789eff563160>"
            ]
          },
          "metadata": {},
          "execution_count": 33
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 717.75x600 with 1 Axes>"
            ],
            "image/png": 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HlId0CACogtlzVc3OSuevX1Q/3dH5DqXlpKnIWVSyPcgWpGGxwwKe6+uP3OHUtalljvfFtS9qWOwwjew+MuD1ARWhCQaASlSUW5pXkKeRy0eSW1oFq52/9F3pmrNpTpnjdTqdmrNpjrqGd/XqeP1x/vpF9VOfNn0MyR1OXZuq2Ztml9le5Cwq2e5LI9ynTR9l5mZq3ZZ1SuyYqKSWSVwBhuFYDgEAFagqt1SSpmZMrZP/tG8Eq50/o4/Xn+evOHd4QLsBSor0rcEsPFWotJy0Ssek5aT5vDQiKTJJPc/o6XN9QFVoggGgAuSWVo/Vzp/Rx2v28zdv6zy3JRDlKXIWad7WeTVUEeAdmmAAqAC5pdVjtfNn9PGa/fztObrH0HFATaMJBoAKkFtaPVY7f0Yfr9nPX5umbQwdB9Q0mmAAqAC5pdVjtfNn9PGa/fzd1OEmBdkqbyOCbEG6qcNNNVQR4B2aYACoALml1WO182f08Zr9/AXXC9aw2GGVjhkWO0zB9YJrqCLAOzTBAFCJ4tzSFiEt3LZHhETUuXgvfyg+f2c1PMtte3jD8Dp5/ir69dIipIXPcWZm/vU3svtI3dn5zjJXhINsQbqz851ex6MBNYmcYACogpG5qla0IX+DDv12yG3bj7/9qA35GwLexPmL01k2J9hXZv/1N7L7SD0Y/6DmbZ2nPUf3qE3TNrqpw01cAYbp0QQDgAeKc0vhHX88TMHMKnq4Rf7x/Go9HMTsv/6C6wVrSOyQQJcBeIXlEAAAv/DnwxTMyGoPBwFqO5pgAIBfWO1hCmZ/uAUAdzTBAAC/sNrDFMz+cAsA7miCAQB+YbWHKZj94RYA3NEEAwD8wmoPUzD7wy0AuKMJBgD4hdUepnD6wy0qYpaHgziKHMo8kKkl25co80AmN+vBkohIAwD4TXH8WVpOmttNckG2IA2LHVan4tEkV6bvHZ3vqPB4zZCLnL4rXVMyprjdxBcREqHRyaNNUR9QU2iCAQB+ZaWHKaTvStecTXPKxKQ5nU7N2TRHXcO7BrTRrCjHOK8gr1o5xkBtRBMMAPA7KzxMoaqcYJtsmpoxVX3a9AnIkgiz1wfUNNYEAwBgALPnBJu9PqCm0QQDAGAAs+cEm70+oKbRBAMAYACz5wSbvT6gptEEAwBgALPnBJu9PqCm0QQDAGodM+bcnp4TXLrRLH4dyJxgs9cH1DTSIQAAtYqZc277RfVT6iWp5dY3KnmUKeorzjF2Ov9IibDZbKbJMQZqCk0wAKDWqA05t/2i+qlPmz7KystSfkG+wkPCldAiwRRXWCvKMS5yFpkixxioSSyHAADUClXl3ErS1IypplkakRSZpAHtBigpMskUDXBl56+YWc4fUBNoggEAtQI5t9XD+QPc0QQDAGoFcm6rh/MHuKMJBgDUCuTcVg/nD3BHEwwAqBXIua0ezh/gjiYYAFAr+DPntjh3ePXPq02TO2y0089fRcgJhpXQBAMAao3iHN4WIS3ctkeERPgcj5a+K11XfHKF7km/R2/ufVP3pN+jKz65Qum70o0q2zSKc4KDbO5//AfZgnRH5zuIR4OlkBMMAKhVjMzhrQ25w0aqKCfY6XSSEwzL4UowAKDWMSKHtzblDhvBascLVIUmGABgSVbLzbXa8QJVoQkGAFiS1XJzrXa8QFVoggEAlmS13FyrHS9QFZpgAIAlWS0312rHC1SFJhgAAsDwXNoih7RjhZT9seuryW5uKj7eJduXGHK8hacKNTdnrp5b/Zzm5sxV4alCr/fhz9xhM6qJnGWj5heoCUSkAUANS9+VrikZU/64SWmvK+d2dPJo3+KpchZJS0dJR/f/sa1pK6n/VCn2GmOKroYyx6vqHW/q2lSl5aSpyFlUsu3FtS9qWOwwjew+0qt9FefmpuWkyen8IzXBZrNpWOywOhcX5o/jNXp+gZrClWAAqEHFubSl79IvzqX1+gENOYuk+UPdG2BJOprr2p6zqJoVV4/Rx5u6NlWzN812a4AlqchZpNmbZit1barX9c3ZNKfc/c3ZNKfOPTDD6OM1/NczUINoggGghhie01rkcF0BLmd/JduWjg7Y0gijj7fwVKHSctIqHZOWk+bx0ojK6itWl3JzjT5ecodR29EEA0ANMTynddc3Za8Al9qjju5zjQsAo4933tZ5Za5gllbkLNK8rfMCUp/ZGX28Vjt/qHtoggGghhie03qs4gbEp3EGM/p49xzdY+g4q+XmGn28Vjt/qHtoggGghhie0xoaYew4gxl9vG2atjF0nNVyc40+XqudP9Q9NMEAUEMMz2mNusCVAlHB/iSb1PRs17gAMPp4b+pwk4Jslf+xFWQL0k0dbgpIfWZn9PFa7fyh7qEJBoAaYnhOa5DdFYP2+x7c/f66/xTXOG8ZkDts9PEG1wvWsNhhlY4ZFjtMwfWCva6vIuQE19z+gJoW0CZ42rRpiomJcfuvf//+gSwJAPyqOKfVZivVNNhsuqPzHd7nqsZeI/3pXalpS/ftTVu5tvuSE5yzSHqli5R2tfTJcNfXV7r4FLfWL6qfUi9JVYuQFm7bI0IilHpJqtfHO7L7SPVp06fc9/q06eNzTnDpK8xBtiDf5sPkjJ4Po/cH1KSAPyzjvPPO0+zZs0te2+38jRFA3VWc01o6Vqo4p7VreFffGuGOV7lSII4ddK0BjrrAtyvAxbnDpWOvinOHfWis+0X1U582fZSVl6X8gnyFh4QroUWCT1cI03ela/me5eW+t3zPcqXvSvfq/FU0H06n0/f5MDkj58Mf+wNqSsCbYLvdrvBwFs0DqPs8zWnt06aP9w1EkF2Kvqh6BVaZO2xz5Q53vMrrBtseZFdSZFK1yjP6/FWVc2uTzff5MDkj5sOf+wNqQsCb4F27diklJUUNGjRQfHy8Hn/8cbVq1cqrfTgcjnK/IvCYE3NhPgIr80CmR7mqmbmZgWkodq6U3YPcYceOlVLblBorq5jR58/082FxNfH7Ff/6bG0BbYK7du2qyZMnKzo6Wvn5+ZoxY4Zuu+02LV68WKGhoR7vJzs7u9LXCDzmxFyYj8BY9/M6z8ZtWaf6B+r7uZqymu1bo3YejNu1aY1++tnz36ONYvT5M/t8wMWfv18lJib6bd8wv4A2wb179y75/44dO+r8889Xnz599Pnnn+vGG2/0eD9xcXGy2+1yOBzKzs4ueY3AY07MhfkIrJMHTkp7qx6X2DFR8ZHxfq+njDOOSR483Cuqcw9FtY33ezmlGX3+TD8fFsfvV/C3gC+HOF3Tpk3Vtm1b7d6926vP2e12tx+Q0q8ReMyJuTAfgZHUMkkRIRHKK8grdx2qTTZFhEQoqWVSYNagRqe4UiWO5qr8dcE2qWkr2aNTfLvprpqMPn+mnw9I4vcr+I+pcoJ//fVX7dmzhxvlANRJ7rmq7opfBzRX1Y+5w4WnCjU3Z66eW/2c5ubMVeGpQq/34c+c24qQcwvUXQFtgqdOnaqMjAzt3btXWVlZevDBBxUUFKSrr746kGUBgN/0i+qn1DOS1OLUKbftEadOKfWMpMDHcfkhdzh1baqS/p6k5zOf1wfff6DnM59X0t+TlLo21et9+SPn1ko5wQD+ENDlEAcOHNDIkSP1888/q3nz5kpMTNT8+fPVvHnzQJYFAP6zbJz6ffux+kjKathA+Xa7wh0OJZz4TfY9H0uNWkmXTwpsjQbmDqeuTdXsTbPLbC9yFpVs9+UBF0bmDlstJxiAS0Cb4JdffjmQ3x4AatapQmnVdEmSXVLSid/Kjlk1Q+o7TvLw0b9+Y0DucOGpQqXlpFU6Ji0nTQ/GP+jxo46L+Tt3uK7nBAMw2ZpgAKjTMmdJzqLKxzgdrnF1wLyt81RUxfEWOYs0b+u8GqrIXVZelkc5wVl5HkRmAKh1aIIBoKb8tNPYcSa35+geQ8cZLb8g39BxAGoXmmAAqCnN2ho7zuTaNG1j6DijhYd4lkTk6TgAtQtNMADUlKR7JFsVv+3a7K5xdcBNHW4qk7pQWpAtSDd1uKmGKnKX0CJBESERZeLWitlkU2RIpBJaJNRwZQBqAk0wAHiiyCHtWCFlf+z6WuTwfh/1gqVeD1Y+ptcDgb8pziDB9YI1LHZYpWOGxQ7z+qY4oxidOwygdqEJBoCq5CySXukipV0tfTLc9fWVLq7t3rp8knTBw2WvCNvsru2Bjkcz2MjuI9Ul5GzJWSqBwelUl5CzvY5HM5rRucMAag9TPTYZAEwnZ5E0f6jKPEb4aK5ruy8PkLh8ktR3nBxr3tKPP2TqrPOSZO/x5zpzBfh0qUtHaOOve8t9b+Ove5W6dIRG9n+9hqtyV5w7nJmbqXVb1imxYyKPSgYsgCYYACpS5JCWjlKZBlj6fZtNWjra9WAJbxumesFSz/u1t2EvnRUfL9nrXsNVWHhcaQe+cr2wlVp3a7NJTqfSDnylBwuPKzi4Uc0XeJri3OH6B+orPjKeBhiwAJZDAEBFdn0jHd1fyQCndHSfaxzKmLdmqopstrINcDGbTUU2m+atmVqzhQGAaIIBoGLHKn6Qgk/jLGbP0d2GjgMAI9EEA0BFQiOMHWcxbZqeY+g4ADASTTAAVCTqAqlpK6mCHFnJJjU92zUOZdzUY5SCnM6yyRDFnE4FOZ26qceomi0MAEQTDMAsjMjhNVqQXepfvF61dCP8++v+U7y/KU5yHd/OlWq279/SzpXVP14Tnr/g4EYaFnmx60U5EWmSNCzy4oDfFAfAmkiHABB4OYtcKQyn34TWtJWrAfU2fsxosddIMVdK3y8p9YZTihngW32/H6/96H61k6QsVe94TXz+RvZ/XVo6QmkHvlLRaduD5GqAAx2PBsC6uBIMILCKc3hLpzAU5/D68kAKIy0bV04D/Lvvl7je94bRx2v28ydXI5x5a6b+0u563XJWkv7S7npl3ppJAwwgoLgSDCBw/JnDa4RThdKq6ZWPWTVD6jvOswddGH28Zj9/pwkObqQhF/01oDUAwOm4EgwgcMyew5s5S3IWVT7G6XCN84TRx2v28wcAJkYTDCBwzJ7D+9NOY8cZfbxmP38AYGI0wQACx+w5vM3aGjvO6OM1+/kDABOjCQYQOGbP4U26R7JV8dukze4a5wmjj9fs5w8ATIwmGEDg+DOH1wj1gqVeD1Y+ptcDnt0UJxl/vGY/fwBgYjTBAAIr9hrpT+9KTVu6b2/ayrXd15xbox4ecfkk6YKHVbbJDHJtv3ySd/sz+nj9df4AoI4jIg1A4MVe44rx2vWN6yau0AjXP+H7egXT6IdHtE6SmrSUfjltf00iXdt9VeYJalWkUFTG6PMHABZAEwzAHILsUvRF1d9P8cMjSmfnFj88wturoxXt7xej93fAt/0VM+r8AYBFsBwCQN1R5cMj5Hp4hKdLI8y+PwCAz2iCAdQdZn8YBQ+3AADToAkGUHeY/WEUPNwCAEyDJhhA3WH2h1HwcAsAMA2aYAB1h9kfRsHDLQDANGiCAdQdZn8Yhdv+KuDrwy2MykX+naPIocwDmVqyfYkyD2TKwc16AOoYItIA1C2x10gXPCStmu6exWuzuZ7+5uvDKMrNHZ7i2/4ah0u/5pV9r3G4b/FoBucip+9K15SMKTpY8Mfa5IiQCI1OHq1+Uf28rw8ATIgrwQDqlpxF0jfTyj58wlnk2p6zyPt9xl4jPbpRGvaZdP3brq+PZvvWsL4aX34DLLm2vxrv3f6Kc4dLp04U5yJ7ebzpu9I1cvlItwZYkvIK8jRy+Uil70r3rj4AMCmaYAB1R6U5vL/zNYe3+GEUcTe4vvqyZKHgiPTTjsrH/LTDNc4TBucOO4ocmpIxRc5y9le8bWrGVJZGAKgTaIIB1B1mz+H94EZjxxl8vFl5WWWuALvvzakDBQeUlZflWX0AYGI0wQDqDrPn8B7Za+w4g483vyDf0HEAYGY0wQDqDrPn8Ia1NnacwccbHhJu6DgAMDOaYAB1h9lzeG/5yNhxBh9vQosERYREyFbB/myyKTIkUgktEjyrDwBMjCYYgDkYkXPrzxzeU4XSqhnSkiddX08Ver+PkDCpWXTlY5pFu8Z5wuAcY3uQXaOTR//+aff9Fb8elTxKdl/OHwCYDE0wgMDLWSS90kVKu1r6ZLjr6ytdfI8zu+AhyVbqtzdbkGu7L7Fmy8ZJz0ZIX4yRMt5yfX02wrXdW4+sr7gRbhbtet8bxTnGTVu6b2/ayrXdy+PtF9VPqZekqkVIC7ftESERSr0klZxgAHWGzw/L2Llzp9asWaNDhw6pqMg9j/PBBx+sdmEALKI457Z0LFdxzq23jVxxTnDp/Tmdru2tk7zb37Jx0jevld3uLPpj++WTPN+f5Gp0C47I8fcbderH7ap3VjvZb/3I8yvApcVeI3W8ypUCceygaw1w1AW+XfGWqxHu06aPsvKylF+Qr/CQcCW0SOAKMIA6xacmeP78+frrX/+qZs2a6ayzzpLN9sc/m9lsNppgAJ6pMufW5sq57XiVZw2d0fs7Veh68lxlVs2Q+o6T6gVXvb/ThYRJd36ujevXKz4+XrJXs8EszjE2iD3IrqTIJMP2BwBm41MT/MYbb+jRRx/Vn//8Z6PrAWAl3uTcetLgGb2/zFllnzxXZpcO17heD1S9PwCAafi0JvjIkSO68sorja4FgNUYnetr9Lifdho7DgBgGj41wf3799fKlSuNrgWA1Rid62v0uGZtjR0HADANj5dDvPvuuyX/HxUVpVdffVXfffedOnTooHr13HczdOhQ4yoEUHcV59wezVX563htrvc9zfU1en9J90jLnq58SYTN7hoHAKhVPG6C58yZ4/Y6JCREGRkZysjIcNtus9loggF4pjjndv5QuXJtT29cvc+5dd9fBbzZX71gqdeD5adDFOv1gPc3xQEAAs7jJvjLL7/0Zx0ArKo453bpKPeb2pq2cjWs3ub6xl4jxVwpfb+k7HsxV3q/v+L4s1XT3a8I2+yuBtjbeDQAgCn4lA4xffp0DR8+XI0aNXLbfuLECf3tb38jIg2Ad4zMuV02rvwGWHJtXzbO+8b18kmuGLTMWa6b4Jq1dS2B4AowANRaPt0YN2PGDBUUFJTZfvz4cc2YMaPaRQGwoOKc27gbXF99frSxB7m+vjzyuF6w68rvgBdYAgEAdYBPTbDT6XR7QEaxLVu2KCzMxyceAUB1eZPrCwCwNK+WQyQlJclms8lms+mKK65wa4QdDocKCgp08803G14kAHiEXF8AgIe8aoLHjBkjp9OpMWPG6KGHHlKTJk1K3qtfv77OPvtsdevWzfAiAcAj5PoCADzkVRM8ePBgSVLr1q3VrVs31a9f3y9FAYBPyPUFAHjIp3SI2NhY/fbbb/rtt9/KvBccHKzgYG4YAeClIkf10yFqU65vkUPauVLN9q2RzjgmRaf4djMgAMAnPjXB3bt3L/fGuGKRkZEaPHiwHnzwQQUF+XTvHQAryVlUQU7wVN9yfXeulPZnlX2vVYI5cn1/P1770f1qJ0lZ8v14AQA+8akJnjJlil5++WUNHjxYXbt2lSRt2LBBCxcu1P3336/Dhw/rnXfeUXBwsO677z5DCwZQx+Qs+v0Jb6Uec3w017X9T+961xguG1d+Ayy5tvuSE2wko48XAOATn5rgTz/9VKNGjdKAAQNKtvXt21cdOnTQvHnzlJaWppYtW+rNN9+kCQZQsSKH6wpw6YZQ+n2bTVo62vUgDU+WCniaE9x3XGCWRBh9vAAAn/m0VuHbb79VbGxsme2xsbFav369JCkxMVG5ubnVKg5AHbfrG/clEGU4paP7XOM8YfacYKOPFwDgM5+a4JYtW+rjjz8us/3jjz9WZGSkJOnnn39W06ZNq1cdgLrt2EFjx5k9J9jo4wUA+Myn5RB/+ctf9Mgjj+irr75SXFycJGnjxo3avn27XnvNdVd2dna223IJACgjNMLYcWbPCTb6eAEAPvOpCb700kv1+eefa968edq5c6ck6eKLL9aMGTPUunVrSdKtt95qWJEA6qioC1ypCEdzVf46WZvr/agLPNuf2XOCjT5eAIDPfGqCJalNmzZ64oknjKwFgD+ZMZc2yO6KBZs/VJJN7o3h7zGM/ad4XqfZc4KNPl4AgM98boKPHj2qDRs26NChQ3I63a9oDBo0qLp1ATCSmXNpY69xxYKVmxM8pe7lBBt9vABgoNGjR+vo0aN6/fXXA12K3/nUBH/55Zd64oknVFBQoNDQULcHZ9hsNppgwExqQy5t7DWuWLDqPjFOMn9OsFRyvI4dK7Vr0xpFde4huxmuzAOwvLFjx5a5uFlX+dQET506Vddff71GjhypRo0aGV0TAKPUplzaILsUfVH19mH2nODTBdmltin66edQRbWND/z5BwBJTZo0CXQJNcaniLSDBw9q6NChNMCA2Vktl9bsOcEA4IGlS5dq4MCB6tq1q3r06KE77rhDBQUFGj16tEaMGKHp06erZ8+eSkhI0P/93/+psLCw5LNFRUWaOXOm+vbtq65du+qaa67R0qVL3fb/ww8/6N5771VCQoK6deumW2+9Vbt375akku/h6f6OHDmixx9/XD179lTXrl11+eWX65NPPvHzGTKGT1eCU1JSlJ2drTZt2hhdDwAjWS2X1uw5wQBQhby8PD3++ON68skn1a9fP/36669au3ZtyRKFVatWqUGDBpo7d6727dunp556Ss2aNdNjjz0mSZo5c6YWLVqkCRMmqG3btsrMzNSTTz6p5s2bKzk5WQcPHtTtt9+u5ORkpaWlKTQ0VFlZWTp16lS59VS1v1dffVXbtm3TrFmz1KxZM+3evVsnTpyosfNVHT41wb1799YLL7ygbdu2qUOHDqpXz303l156qSHFAagmq+XSmj0nGACqkJ+fr1OnTumyyy7T2WefLUmKiYkpeT84OFjPPfecGjVqpPPOO08PP/ywnn/+eT3yyCM6deqUZs6cqdmzZ6tbt26SXGle69at07x585ScnKz3339foaGhSk1NVf369SVJ0dHR5dZSWFhY5f7279+vTp06lTw3ojgqtzbwqQkeN26cJGnGjBll3rPZbNq8eXP1qgJgDKvl0po9JxgAqtCxY0f16tVLAwcOVEpKilJSUnTFFVcoLCxMkqshPn05ardu3VRQUKDc3FwVFBTo+PHjuuuuu9z2efLkSXXq1EmStHnzZnXv3r2kAa7Mrl27qtzfLbfcoocfflg5OTm68MIL1a9fPyUkJFTrHNQUn5rgLVu2GF0HAH+oTbm0RY7qp0OYPScYAKpgt9s1e/ZsZWVl6euvv9bcuXP18ssva/78+VV+tqCgQJJrCUNEhPu/8AUHu37fa9iwoce1eLK/3r176z//+Y/++9//6uuvv9Ydd9yh2267TaNGjfL4+wSKTzfGne63334zog5J0ltvvaWYmBg9++yzhu0TsLzYa6QLHpJOizKU5Hp9wUOBj0eTXDFur3SR0q6WPhnu+vpKF9d2b10+SWpW/j/tqVl04OPRAKAKNptNiYmJevjhh7Vw4ULVr19f6enpkqTvv//ebc3t+vXrFRISopYtW6p9+/YKDg7W/v37FRUV5fZfy5YtJbmuJK9du1YnT56ssg5P9idJzZs31+DBg/Xiiy9qzJgxmjdvnsFnxD98aoIdDodmzJihiy66SN26ddOePXskSa+88oo++ugjnwrZsGGDPvzwQ7d1LwAMkLNI+mZa2SUCziLXdl8aTSMV5xiXTrEozjH2tr4PbpF+2lH+ez/tcL0PACb13Xff6c0331R2drb279+vZcuW6fDhw2rXrp0k1zrdsWPH6n//+5/++9//atq0abr99tsVFBSk0NBQ3XXXXZo8ebI+/fRT7d69W5s2bdLcuXP16aefSpJuu+02HTt2TCNHjlR2drZ27typhQsXavv27WVq8WR/r776qtLT07Vr1y798MMPWr58udq3b19zJ6wafFoO8cYbb2jhwoV68sknS9YHS1KHDh2UlpamG2+80av9/frrr3ryySf1zDPP6I033vClJADlqTQn+HeBzAk2Ose48Lj0/ZLKx3y/xDUumIhHAOYTGhqqzMxMpaWl6dixY2rVqpVGjx6t3r176/PPP1evXr0UFRWl2267TYWFhbr66qv10EMPlXz+0UcfVfPmzTVz5kzt3btXTZo0UWxsrO677z5JUrNmzZSWlqYXXnhBQ4YMUVBQkDp16qTExMRy66lqf/Xr11dqaqr27dunhg0bKjExUampqf4/UQbwqQn+xz/+oUmTJqlXr14aP358yfaYmJhy/yZRlYkTJ6p379664IILfGqCHQ5HuV8ReMxJgO1cKbsHOcGOHSultik1VlYJo+v7Yqw8aeUdX4yVBrzgaZV+w8+HuTAf5lIT82G3m+B+iFLat2+vt99+u9IxDz/8sB5++OFy37PZbBo2bJiGDRtW4ec7duxY4feYMmWKV/sbMWKEW65wbeJTE3zw4EGdc845ZbY7nc4Kc+Yq8s9//lM5OTn6+OOPfSlFkpSdnV3pawQecxIYzfatUTsPxu3atEY//Rzq93pKM7q+c3d9pzAP9nds13f63/r1HoysGfx8mAvzYS7+nI+Krn7CGnxqgs8991ytXbu2JL+u2NKlS0siMzyRm5urZ599Vu+8844aNGjgSymSpLi4ONntdjkcDmVnZ5e8RuAxJwF2xjEpq+phUZ17uB7dW9OMrm//+dKPa6scFhp1vuLjPdifn/HzYS7Mh7kwH/A3n5rgESNGaPTo0Tp48KCcTqeWLVumHTt2aOHChZo5c6bH+9m0aZMOHTqk6667rmSbw+FQZmam3n//fWVnZ3v0C99ut7uNK/0agcecBEh0ikc5wfbolMCsCTa6viueldZV/s+IkmS/4lnJRL8e+fkwF+bDXJiPP5ReqoDq8akJ7tevn958803NmDFDjRo10muvvabY2Fi9+eabuvDCCz3eT8+ePbV48WK3bU899ZTatWune+65h1/0QHX5MyfYiFxfo+sLbiTFDKj85riYAb7dFGfE8QIATMOnJliSunfvrtmzZ1frm4eGhqpDhw5u20JCQnTGGWeU2Q7AR7HXSH9615XCcPpNaE1buRpMX3KCcxZVsL+p3u+vOMd41XTJeVoTbLO5Hnzh7f5u+cAVg1ZeIxwzwPW+t4w8XgCAKfjcBAOoRWKvkTpeJceOldq1aY2iOvfwfQlEca5v6eULxbm+f3rXu8awOMe49P6Kc4xbJ/nWCBcel/71tHR4u9S8nXTZM75dATb6eAEApuBxE5yUlCRb6SdOVSAjI8PngubOnevzZwFUIsgutU3RTz+Hum4y83UJhJG5vv7MMQ5uJF31knefKc3o4wUAmIbHTfCYMWP8WQeA2mDXN2Wf7ObGleurXd9I0RfV/P6MZvb6AAA+87gJHjx4sNc7f+utt3TzzTeradOmXn8WgAkdO2jucUYze30AAJ8F+XPnb775po4cOeLPbwGgJoVGmHuc0cxeHwDAZ35tgp3OStb5Aah9oi5wpSKoovsDbFLTs13jArE/o5m9PgCohr179yomJkabN28OdCkB4dcmGEAdU5zrWxlvcn3d9le60axmjrERzF4fANNxFDm1atsh/WP9Pq3adkiOIi4ImhVNMADvFOf62kr99mELcm33JSf4T+9KTVu6b2/ayhzxY2avD4BpLN2Yq5SpX+qWWav1yIfrdcus1UqZ+qWWbsz17/ddulQDBw5U165d1aNHD91xxx0qKCiQJH300Ue68sorFRcXp/79++v9998v+dyll14qSRo0aJBiYmI0ZMgQSVJRUZGmT5+uiy++WF26dNG1116rr776quRzhYWFmjhxolJSUhQXF6c+ffq4PTF49uzZGjhwoOLj49W7d2/99a9/1a+//urXc+ALcoIBeKfCXF+n77m+v+cYm/aJbGavD0DALd2Yq/vfyyoTqHjgyAnd/16W3rg9Qf27tCz3s9WRl5enxx9/XE8++aT69eunX3/9VWvXrpXT6dSiRYv06quv6v/+7//UqVMnbd68WePGjVNISIgGDx6sjz76SDfeeKPmzJmjc889V/Xr15ckvfvuu5o9e7YmTpyoTp066ZNPPtGIESP02WefqW3btpo7d66+/PJLvfLKK2rZsqVyc3N14MCBkppsNpvGjh2r1q1ba8+ePZowYYJeeOEF/fWvfzX8+KuDJhiA5/yZmxtkN3fMmNnrAxAwjiKnJizOqex3Rk1YnKPLYiNlD/LsmQueys/P16lTp3TZZZfp7LPPliTFxMRIkqZNm6bRo0fr8ssvlyS1adNG//vf/zRv3jwNHjxYzZs3lySdccYZCg8PL9nn22+/rXvuuUdXXXWVJOnJJ5/UmjVrlJaWpvHjxys3N1dRUVFKTEyUzWYr+b7F7rjjjpL/b926tR599FGNHz/eWk1w9+7d1aBBA39+CwA1idxcACgjY8dh5R45UeH7Tkm5R04oY8dh9Wp/pqHfu2PHjurVq5cGDhyolJQUpaSk6IorrlD9+vW1e/dujR07VuPGjSsZf+rUKTVp0qTC/R07dkx5eXlKSEhw256QkKAtW7ZIcsXm3nXXXerfv78uuugiXXLJJUpJSSkZ+80332jmzJnavn27jh07JofDod9++03Hjx9Xo0Y+PLnTTzxugo8dO+bxTkNDQyVJs2bN8r4iAOZFbi4AlJH3S8UNsC/jvGG32zV79mxlZWXp66+/1ty5c/Xyyy/rzTfflCRNmjRJ559/vttngoKqd0tY586d9e9//1tfffWVvvnmGz366KO64IIL9Nprr2nv3r269957dcstt+ixxx5TWFiY1q1bp7Fjx+rkyZO1swnu3r17lY9Ndjqdstlslo3aAOo8cnMBoIwWTRoaOs5bNptNiYmJSkxM1AMPPKA+ffooKytLLVq00J49e3TNNeXfp1G8BtjhcJRsCw0NVYsWLZSVlaXk5OSS7VlZWeratavbuAEDBmjAgAG64oordPfdd+vnn3/Wpk2b5HQ6NXr06JJm+/PPP/fHYVebx03wu+++6886ANQGxbm5R3NV/rpgm+t9cnMBWEhydHO1DGuoA0dOVPQ7oyLDGio5urnh3/u7777TqlWrdOGFF+rMM8/Ud999p8OHD6tdu3Z6+OGH9cwzz6hJkya66KKLVFhYqI0bN+ro0aO68847deaZZ6phw4ZasWKFIiMj1aBBAzVp0kTDhw/XtGnTdM4556hjx45asGCBtmzZohdffFGSK/0hPDxcnTp1UlBQkJYuXarw8HA1bdpUUVFROnnypObOnau+fftq3bp1+vDDDw0/biN43ASf/rcBABZVnJs7f6hcv62f/ts9ubkArMkeZNP4gbG6/72sin5n1PiBsYbfFCe5rshmZmYqLS1Nx44dU6tWrTR69Gj17t1bktSwYUO9/fbbev755xUSEqIOHTpo2LBhkqR69erp6aef1owZM/Taa6+pe/fumjt3roYOHapjx45pypQpOnz4sNq3b6/XX39dbdu2lSQ1btxYf/vb37Rr1y4FBQUpLi5Ob731loKCgtSxY0c99dRTmjVrllJTU9W9e3eNHDlSo0aNMvzYq8vmrMZj3Y4fP679+/fr5MmTbts7duxY7cI84XA4tH79esXHx8tut5d5jcBjTkykyCHHjpXatWmNojr3kD06xfdmNWeRKyXi9Jvkmp7taoDJzfUYPx/mwnyYS22cj6UbczVhcY7bTXItwxpq/MBYv8SjoXp8Soc4fPiwnnrqKbfg5NOxJhgwmd+bVvvR/WonSVlyLVvoP9W3ppXcXAAoo3+XlrosNlIZOw4r75cTatHEtQTCH1eAUX0+NcHPPvusjh49qvnz52vo0KGaPn26fvzxR73xxhsaPXq00TUCqI6cRb8vXyj1jz5Hc13bfX3qGbm5AFCGPchmeAwa/MOnJnjNmjV6/fXXFRcXJ5vNplatWunCCy9UaGioZs6cqUsuucTgMgH4xJ8PtwAAoBbzKSiuoKCg5CkjYWFhOnz4sCSpQ4cOysnJMa46ANXjzcMtAACwEJ+a4OjoaO3YsUOS69F88+bN08GDB/Xhhx+6PXYPQIDxcAsAAMrl03KIoUOHKj8/X5L04IMP6u6779bixYtVv359TZkyxdACAVQDD7cAAKBcPjXB1157bcn/d+nSRf/5z3+0fft2tWzZsmSZBAAT4OEWAACUy6flENOnT9fx48dLXjdq1EidO3dWSEiIpk+fblhxAKqp+OEWkv6IbJf767r6cIsih7RjhZT9setrkaPqzwAALMOnJnjGjBkqKCgos/348eOaMWNGtYsCYKDYa1wxaE1LBbU3beV7PJrZ5SySXukipV0tfTLc9fWVLq7tAIBq2bt3r2JiYgx7LoTR+/OUT8shnE6nbLaywc9btmxRWFhYtYsCYLDfH25h2BPjzMxfucgAAElSy5YttXLlSjVr1izQpVSLV01wUlKSbDabbDabrrjiCrdG2OFwqKCgQDfffLPhRQIwQJBdapuin34OVVTb+LrZAJOLDADVdvLkSdWvX7/C9+12u+nSwAoLCxUcHOzVZ7xqgseMGSOn06kxY8booYceUpMmTUreq1+/vs4++2x169bNqwIAwDDe5CLztDsA/lDkqNFHys+bN0/Tpk3TV199paCgP1a53n///TrjjDM0efJkpaena8aMGfrf//6nFi1aaPDgwbrvvvtUr56rDYyJidH48eP11VdfafXq1Ro+fLiGDh2qiRMn6uuvv1ZBQYEiIyN177336vrrr9fevXt16aWXauHCherUqZMk6YcfftCLL76ozMxMOZ1OderUSVOmTNE555yjoqIivf7665o/f74OHz6s9u3b6/HHH9fFF19c4XFlZGTo+eef15YtW3TGGWdo0KBBevTRR0tqHjJkiM477zzZ7XYtWrRIHTp00Ny5c706d141wYMHD5YktW7dWgkJCSWFAIApkIsMIJByFrn+Ner0v4w3beW6QdlPy7D69++vSZMmac2aNerVq5ck6eeff9aKFSs0a9YsrV27VqNGjdLTTz+t7t27a/fu3Ro3bpwkV8xtsenTp+vxxx/X2LFjZbfb9eqrr2rbtm2aNWuWmjVrpt27d+vEiRPl1nDw4EHdfvvtSk5OVlpamkJDQ5WVlaVTp05Jkt59913Nnj1bEydOVKdOnfTJJ59oxIgR+uyzz9S2bdty9/fnP/9ZgwcP1tSpU7Vjxw49/fTTatCggR566KGScZ9++qluueUWffDBBz6dO5+62OTkZO3evVuffPKJ9uzZo7Fjx+rMM8/Uf//7X7Vq1UrnnXeeT8UAQLWQiwwgUAJ0P0JYWJguvvhiLV68uKQJ/uKLL9SsWTP16NFDd911V0lDKUlt2rTRI488ohdeeMGtCb766qt1/fXXl7zev3+/OnXqpLi4OEmuC6AVef/99xUaGqrU1NSSZRTR0dEl77/99tu65557dNVVV0mSnnzySa1Zs0ZpaWkaP358mf39/e9/V2RkpP7v//5PNptN7du318GDB/Xiiy/qgQceKLni3bZtW/3lL3/x6bxJPqZDZGRkaODAgdqwYYOWLVtWkhTx/fffa9q0aT4XAwDVUpyLXCYOrphNano2ucgAjFXl/Qhy3Y/gp6jGgQMHatmyZSosLJQkLV68WFdddZWCgoK0ZcsWzZgxQ926dSv5b9y4ccrPz3eLu+3SpYvbPm+55RYtWbJE1157rZ5//nllZWVV+P03b96s7t27l7uO+NixY8rLy1NCQoLb9oSEBG3btq3c/W3btk3dunVzu/csMTFRBQUFOnDgQMm2zp07V3JWquZTE/zSSy/p0Ucf1ezZs90OuGfPnlq/fn21CgLgJ6cKpdVvqHX2a9LqN1yv6xor5yIDCBxv7kfwg759+8rpdGr58uXKzc3V2rVrNXDgQElSQUGBHnroIS1cuLDkv8WLF2vZsmVq0KBByT5CQkLc9tm7d2/95z//0R133KG8vDzdcccdmjp1qsrTsGFDvxxXVRo1alStz/vUBG/dulX9+vUrs7158+b66aefqlUQAD9YNk56NkL2f41VxM6Fsv9rrPRshGt7XWPFXGQAgRXg+xEaNGigyy+/XIsXL9Znn32m6OjokquksbGx2rFjh6Kiosr8d/qNdOVp3ry5Bg8erBdffFFjxozRvHnzyh0XExOjtWvX6uTJk2XeCw0NVYsWLcpcSc7KytK5555b7v7at2+vb7/9Vk7nH1fW161bp8aNGysyMrLSmr3h05rgJk2aKD8/X23atHHbvnnzZkVEsNYOMJVl46RvXiu73Vn0x/bLJ9VsTf72ey5yTd6hDcDCTHA/wsCBA3Xvvffqhx9+0DXX/PGX/QceeED33XefWrVqpSuuuKJkicTWrVv12GOPVbi/V199VZ07d9Z5552nwsJCLV++XO3bty937G233aa5c+dq5MiR+vOf/6wmTZpo/fr16tq1q9q1a6fhw4dr2rRpOuecc9SxY0ctWLBAW7Zs0Ysvvlju/m699ValpaVp0qRJuu2227Rjxw5NmzZNd955Z5WNuzd8aoKvuuoqvfjii3r11Vdls9lUVFSkdevWaerUqRo0aJBhxQGoplOF0qoqHmW+aobUd5xUz7t8RdMLshODBqBmFN+PcDRX5a8Ltrne9+P9CD179lRYWJh27NhRshRCki666CK9+eabmjFjhmbNmqV69eqpXbt2uvHGGyvdX/369ZWamqp9+/apYcOGSkxMVGpqarljmzVrprS0NL3wwgsaMmSIgoKC1KlTJyUmJkqShg4dqmPHjmnKlCklEWmvv/56uckQkhQREaG33npLzz//vObPn68zzjhDN9xwg+6//37fTk4FbM7TrzV7qLCwUBMnTtSnn34qh8OhevXq6dSpUxo4cKCmTJkiu71mrrY4HA6tX79e8fHxstvtZV4j8JiTAFs1Q/piTNXjrnhO6vWA/+uBG34+zIX5MJdaNx8l6RCSeyP8+/0ILMcyHZ+uBAcHB+uZZ57RAw88oK1bt6qgoECxsbGKiooyuj4A1fHTTmPHAQDKV3w/Qrk5wVNogE3I56ddfPTRR0pLS9POnTslubLahg0bVuXldQA1qFlbY8cBACrG/Qi1ik9N8Kuvvqo5c+bo9ttvV3x8vCRp/fr1eu6557R//3498sgjRtYIwFdJ90jLnnbdBFcRm901DgBQfdyPUGv41AR/8MEHmjRpkq6++uqSbZdeeqliYmI0adIkmmDALOoFS70eLD8dolivB+reTXEAAFTBpyb41KlTZZ4sIrme3OFw+OdpKAB8VBx/tmq6+xVhm93VANe1eDQAADzgU9jatddeqw8++KDM9vnz57vFcgAwicsnSWMPynHZszrYdpAclz0rjT1AAwwAsCyfb4z7+OOP9fXXX+v888+XJG3YsEH79+/XoEGDNHny5JJxTz31VPWrBFB99YKlnvdrb8NeOis+XqoNkUMAAPiJT03w1q1bFRsbK0navXu3JOmMM87QGWecoa1bt5aMs9lsBpQIAAAAGMunJnju3LlG1wEAAADUGOMewAwAAABTmTZtmq699tpq72fNmjWKiYnR0aNHPf7M6NGjNWLEiGp/b3/xeU0wAAAAzO2uu+7S7bffXu39dOvWTStXrlSTJk08/szYsWPldDqrHhggNMGAVZwqlNa8pdY/ZEonkqQefyYfGADquMaNG6tx48YVvl9YWKjg4Kr/LAgODlZ4eLhX39ubhjkQWA4BWMGycdKzEbL/a6widi6U/V9jpWcjXNsBAIZxFDmUeSBTS7YvUeaBTDmK/Pv8hHnz5iklJUVFRe5PBr3//vv11FNPlVkOUbxE4Y033lBKSor69+8vScrKytK1116ruLg4XXfddUpPT1dMTIw2b94sqexyiAULFqh79+5asWKFrrzySnXr1k3Dhw9XXl5eme9VrKioSLNmzdJll12mLl266JJLLtEbb7xR8v4LL7ygK664Queff74uvfRSvfLKKzp58qTxJ+13XAkG6rpl48p/Ypyz6I/t5AUDQLWl70rXlIwpOlhwsGRbREiERiePVr+ofn75nv3799ekSZO0Zs0a9erVS5L0888/a8WKFZo1a5bWrl1b5jOrVq1SaGioZs+eLUk6duyY7r//fl188cV66aWXtG/fPj333HNVfu8TJ07onXfe0fPPP6+goCA9+eSTmjp1ql566aVyx7/00kv66KOP9NRTTykxMVF5eXnasWNHyfuNGzfW5MmT1aJFC23dulXjxo1T48aNdc899/hyaqrElWCgLjtV6HpSXGVWzXCNAwD4LH1XukYuH+nWAEtSXkGeRi4fqfRd6X75vmFhYbr44ou1ePHikm1ffPGFmjVrph49epT7mZCQED3zzDM677zzdN5555V89plnntG5556r3r176+67767ye588eVITJkxQXFycOnfurNtuu02rV68ud+yxY8f07rvv6sknn9TgwYN1zjnnqHv37rrxxhtLxowYMUIJCQlq3bq1+vbtq7vuukuff/65N6fDKzTBQF2WOcv9UcnlcTpc4wAAPnEUOTQlY4qcKnsTWPG2qRlT/bY0YuDAgVq2bJkKC10XNBYvXqyrrrpKQUHlt3kdOnRwWwe8Y8cOxcTEqEGDBiXb4uLiqvy+jRo10jnnnFPyukWLFjp06FC5Y7dv367CwkL17Nmzwv0tWbJEN998sy688EJ169ZNr7zyinJzc6usw1c0wUBd9tNOY8cBAMrIyssqcwX4dE45daDggLLysvzy/fv27Sun06nly5crNzdXa9eu1cCBAysc36hRI0O+b7167qtqbTZbhWkQpzfY5fn222/1xBNPqHfv3nrzzTf16aef6r777mNNMAAfNWtr7DgAQBn5BfmGjvNWgwYNdPnll2vx4sXatWuXoqOj1blzZ48/Hx0drUWLFrklRWRnZxtaY9u2bdWwYUOtXr1abdq0KfP+t99+q1atWun+++8v2bZ//35DayiNK8FAXZZ0j2Sr4sfcZneNAwD4JDzEs+gwT8f5YuDAgVq+fLk++eSTSq8CV/RZp9OpcePGadu2bVqxYoXeeecdSa6ru0Zo0KCB7rnnHr3wwgtauHChdu/erfXr1+ujjz6SJEVFRSk3N1f//Oc/tXv3br377rtKT/fPOupiNMFAXVYvWOr1YOVjej1AXjAAVENCiwRFhETIpvIbRptsigyJVEKLBL/V0LNnT4WFhWnHjh1eN8GhoaF64403tHnzZl177bV6+eWX9cADD0iSRxnCnhoxYoTuvPNOvfbaaxowYIAee+wxHT58WJJ06aWXatiwYZo4caKuvfZaffvtt25Xhf3B5jTzozyq4HA4tH79esXHx8tut5d5jcBjTkxi2ThXSsTpN8nZ7K4GmHi0gOHnw1yYD3OpbfNRnA4hye0GueLGOPWSVL/FpPnDokWLNGbMGK1du1YNGzYMdDl+wZpgwAounyT1HSfHmrf04w+ZOuu8JNl5YhwAGKZfVD+lXpJabk7wqORRpm+AFy5cqNatWysiIkLff/+9XnzxRfXv37/ONsASTTBgHfWCpZ73a2/DXjorPl6qBVdWAKA26RfVT33a9FFWXpbyC/IVHhKuhBYJsgeZ//fb/Px8vfbaa8rPz1d4eLj69++vxx57LNBl+RVNMAAAgEHsQXYlRSYFugyv3XPPPX57MptZcWMcAAAALIcmGAAAAJZDEwwAAADLoQkGAACA5dAEAwAAwHJoggEAAGA5NMEAAACwHJpgAAAAWA5NMAAAACyHJhgAAACWQxMMAAAAy6kX6AIA1FJFDmnXN9Kxg1JohBR1gRRkD3RVAAB4JKBN8N///nd98MEH2rdvnyTpvPPO04gRI9S7d+9AlgWgKjmLpKWjpKP7/9jWtJXUf6oUe03g6gIAwEMBXQ4RGRmpJ554QgsWLNAnn3yinj176oEHHtAPP/wQyLIAVCZnkTR/qHsDLElHc13bcxYFpi4AALwQ0Ca4b9++6t27t9q2bavo6Gg99thjCgkJ0fr16wNZFoCKFDlcV4DlLOfN37ctHe0aBwCAiZlmTbDD4dDSpUtVUFCgbt26ef3Z8r4i8JgTc6n2fOxcKXvpK8BunNLRfXLsWCm1TfHte1gIPx/mwnyYS03Mh93OfQxWZnM6neVd0qkx33//vW6++Wb99ttvCgkJ0UsvveTxmmCHw8FVY6AGNdv3b7XLerbKcdsTxuqnsy+tgYoAwHeJiYmBLgEBFPArwdHR0Vq4cKF++eUXffHFFxo1apTee+89nXvuuR7vIy4uTna7XQ6HQ9nZ2SWvEXjMiblUez7OOCZlVT0sqnMPRbWN937/FsPPh7kwH+bCfMDfAt4EBwcHKyoqSpLUpUsXZWdn691339XEiRM93ofdbnf7ASn9GoHHnJiLz/MRneJKgTiaq/LXBdukpq1kj04hLs0L/HyYC/NhLswH/MV0D8soKipSYWFhoMsAUJ4guysGTZJkK/Xm76/7T6EBBgCYXkCb4JdeekmZmZnau3evvv/+e7300kvKyMjQwIEDA1kWgMrEXiP96V2paUv37U1bubaTEwwAqAUCuhzi0KFDGjVqlPLy8tSkSRPFxMTo7bff1oUXXhjIsgBUJfYaqeNVPDEOAFBrBbQJfu655wL57QFUR5Bdir4o0FUAAOAT060JBgAAAPyNJhgAAACWQxMMAAAAy6EJBgAAgOXQBAMAAMByaIIBAABgOTTBAAAAsByaYAAAAFgOTTAAAAAshyYYAAAAlkMTDAAAAMuhCQYAAIDl0AQDAADAcmiCAQAAYDk0wQAAALAcmmAAAABYDk0wAAAALIcmGAAAAJZDEwwAAADLoQkGAACA5dAEAwAAwHJoggEAAGA5NMEAAACwHJpgAAAAWA5NMAAAACyHJhgAAACWQxMMAAAAy6EJBgAAgOXQBAMAAMByaIIBAABgOTTBAAAAsByaYAAAAFgOTTAAAAAshyYYAAAAlkMTDAAAAMuhCQYAAIDl0AQDAADAcmiCAQAAYDk0wQAAALAcmmAAAABYDk0wAAAALIcmGAAAAJZDEwwAAADLoQkGAACA5dAEAwAAwHJoggEAAGA5NMEAAACwHJpgAAAAWA5NMAAAACyHJhgAAACWQxMMAAAAy6EJBgAAgOXQBAMAAMByaIIBAABgOTTBAAAAsByaYAAAAFgOTTAAAAAshyYYAAAAlkMTDAAAAMuhCQYAAIDl0AQDAADAcmiCAQAAYDk0wQAAALAcmmAAAABYDk0wAAAALIcmGAAAAJZDEwwAAADLoQkGAACA5dAEAwAAwHJoggEAAGA59QL5zWfOnKlly5Zp+/btatiwobp166YnnnhC7dq1C2RZAAAAqOMCeiU4IyNDt912m+bPn6/Zs2fr1KlTGj58uAoKCgJZFgAAAOq4gF4Jfvvtt91eT5kyRb169dKmTZuUlJQUoKoAAABQ15lqTfAvv/wiSQoLCwtwJQAAAKjLAnol+HRFRUV67rnnlJCQoA4dOnj1WYfDUe5XBB5zYi7Mh7kwH+bCfJhLTcyH3W73275hfjan0+kMdBGSNH78eK1YsUJ///vfFRkZ6dFnHA6H1q9f79/CAABAnZSYmBjoEhBAprgSPHHiRC1fvlzvvfeexw3w6eLi4mS32+VwOJSdnV3yGoHHnJgL82EuzIe5MB/mwnzA3wLaBDudTk2aNEn/+te/NHfuXLVp08an/djtdrcfkNKvEXjMibkwH+bCfJgL82EuzAf8JaBN8IQJE/TZZ5/p9ddfV+PGjZWfny9JatKkiRo2bBjI0gznKHIqY8dh5f1yQi2aNFRydHPZg2yBLquE2esDAAAwUkCb4A8++ECSNGTIELftkydP1nXXXReIkvxi6cZcTVico9wjJ0q2tQxrqPEDY9W/S8sAVuZi9voAAACMFtAm+Pvvvw/kt68RSzfm6v73slT67sMDR07o/vey9MbtCQFtNM1eHwAAgD+YKie4rnEUOTVhcU6ZBlNSybYJi3PkKApMQIfZ6wMAAPAXmmA/ythx2G2JQWlOSblHTihjx+GaK+o0Zq8PAADAX2iC/Sjvl4obTF/GGc3s9QEAAPgLTbAftWjiWcKFp+OMZvb6AAAA/IUm2I+So5urZVhDVRQ0ZpMrhSE5unlNllXC7PUBAAD4C02wH9mDbBo/MFaSyjSaxa/HD4wNWB6v2esDAADwF5pgP+vfpaXeuD1BkWHuSwoiwxqaIn7M7PUBAAD4Q0Bzgq2if5eWuiw20rRPZDN7fQAAAEajCa4h9iCberU/M9BlVMjs9QEAABiJ5RAAAACwHJpgAAAAWA5NMAAAACyHJhgAAACWw41xNcRR5DQ0fcHs+yve5+rth5S5+7hOND2knu3DSZwAAACmQBNcA5ZuzNWExTnKPXKiZFvLsIYaPzDWpxxes++v3H2uyaz2PgEAAIzCcgg/W7oxV/e/l+XWYErSgSMndP97WVq6MbdO7c9f+wQAADASTbAfOYqcmrA4R85y3iveNmFxjhxF5Y2offvz1z4BAACMRhPsRxk7Dpe5Gno6p6TcIyeUseNwndifv/YJAABgNJpgP8r7peJmsC6O89c+AQAAjEYT7EctmjS01Dh/7RMAAMBoNMF+lBzdXC3DGqqiUDCbXCkMydHN68T+/LVPAAAAo9EE+5E9yKbxA2MrHTN+YKzH2bmn76/0J4pf+7o/I+rzR42ncxQ5tWrbIf1j/T6t2naIm+sAAIDPaIL9rH+XljorNLjc984KDfY6M7d/l5Z64/YERYa5LyeIDGuoN25P8Gl/f744WqV70iCb9OeLo33K9DW6RskVu5Yy9UvdMmu1HvlwvW6ZtVopU78kbg0AAPiEh2X4We8XvlT+scJy38s/VqjeL3yp/z7Z16t99u/SUpfFRhryhLelG3P11lc7ykSaOZ3SW1/tULdzmvncCF8WG6nV2/KVuXGrkrp08PmJccW5w6VrLM4d9rWxBgAA1kUT7EdHCk5q16HjlY7Zdei4jhScVFhIfa/2bQ+yqVf7M6tTXpWZvja5Mn0vi430qXm1B9nUs92Zani0keLbnenzEgh/1ggAAKyJ5RB+dNecDEPHGa02ZPrWhhoBAEDtQxPsR/srad58GWe02pDpWxtqBAAAtQ9NsB+1CvMsC9fTcUarDZm+taFGAABQ+9AE+9E7dyQbOs5otSHTtzbUCAAAah+a4AoUnirS2yu26//+sVFvr9iuwlNFXu8jLKS+os5sVOmYqDMbeX1TnGRMZq4/coKN5s/cYQAAYF2kQ5Rj8pIczVqxQ6f3lc8u2ax7LorWUwMqbxpL+++TfRU9+p/lphvYfn/fW0s35mrC4hy3G8ZahjXU+IGxPuUEx7Vuqg17j5Z5L651U1NEjxXnDpc+5kgfjxkAAIAmuJTJS3I086sdZbYXOVWy3ZtGuOtfvyi3AZZcyQZd//qFNvz1Co/3Z3Rm7j3vZpbbAEvShr1Hdc+7mZo1NMnj/fmLkdnIAAAALIc4TeGpIs1aUbYBPt2sFTs8XhqRf/Q3HT1xqtIxR0+cUv7R3zzaX1WZuZIrM9fTpRHHCx36V05epWP+lZOn44UOj/bnb8XZyNfGn61e7X3LHQYAAJBogt3MXbVTVfWPRU7XOE8Mfn2loeOMzsx9bkmOoeMAAABqC5rg0+w6XGDouMO/njR0nNGZuTsPeXYcno4DAACoLWiCTxPVPMTQcc0be5b64Ok4ozNz257p2XF4Og4AAKC2oAk+zZBebVXVMtMgm2ucJz4dkWLoOKMzc8d4eIOfp+MAAABqC5rg0wTXC9I9F0VXOuaei6IVXM+z0xbetIGaNqw8gKNpw3oKb9rAo/0ZnevbKNiuy2JbVDrmstgWahRs92h/AAAAtQVNcClPDYhV19ZNy32va+umXucEVxV/5k08mvRHrm95fMn1nTU0qcJG+LLYFqaIRwMAADAaTXApk5fkVJqbO9nLpIRO4z6v1vuleZLr661ZQ5O0eWJ/Del5ji467ywN6XmONk/sTwMMAADqLB6WcRpPc4Ifv7yjR0siDvx8QsdPVp4pfPxkkQ78fEKRZ1R9M5s3ub7eLmFoFGzXpEFxXn0GAACgtuJK8GmMzgm+etpXho4j1xcAAMAYNMGnMTonuKqnxXk7jlxfAAAAY9AEn8bonOCqkiG8HUeuLwAAgDFogk9jdE7wZw9dbOg4cn0BAACMQRN8GqNzgiPPaKhG9Ssf26h+kEc3xUn+zfV1FDm1atsh/WP9Pq3adkiOqhZHAwAA1GKkQ5RSnAM8a8UOt5vkgmyuBtjbnODNk65U9Oh/qryW0vb7+96YNTRJvV/4UrsOHS/zXtSZjXyKNVu6MVcTFuco98iJkm0twxpq/MBYr3OHAQAAagOuBJfjqQGx2jLpSo27qpOG9orSuKs6acukK71ugCXpmukrym2AJcn5+/vemLwkp9wGWJJ2HTrudY7x0o25uv+9LLcGWJIOHDmh+9/L0tKNuV7tDwAAoDbgSnAFgusFafhF7aq1j2MnTlX4YItiG/Ye1bETpxTqwc1xRucYO4qcmrA4p9wm3SnXleoJi3N0WWykx49iBgAAqA24EuxHj8371tBxRucYZ+w4XOYK8OmcknKPnFDGjsMe7Q8AAKC2oAn2o90/lb9swddxRucY5/1ScQPsyzgAAIDagibYj85p1sjQcUbnGLdo4lkqhafjAAAAaguaYD96+aZuho4zOsc4Obq5WoY1VEW7tMmVEpEc3dyj/QEAANQWNMF+FNqwnrq2blrpmK6tm3p0U5xkfI6xPcim8QNdiRelG+Hi1+MHxnJTHAAAqHNogv1s0YMXKTw0uNz3wkODtejBi7za31MDYnXvxdFlrggH2aR7L/Y+x7h/l5Z64/YERYa5L3mIDGuoN25PICcYAADUSUSk+dnkJTnKP1ZY7nv5xwo1eUmO143rUwNi9fjlHTV31U7tOlygqOYhGtKrrcdXgEvr36WlLouNVMaOw8r75YRaNHEtgeAKMAAAqKtogv3I6Fzf0xmRY3w6e5BNvdqfadj+AAAAzIzlEH5kdK4vAAAAjEET7EdG5/oCAADAGDTBfmR0ri8AAACMQRPsR0bn+gIAAMAYNMF+ZHSuLwAAAIxBOkQFHEVOQyLDiuPPZq3Y4XaTXJDN1QB7G48GAACA6qMJLsfSjbmasDhHuUdOlGxrGdZQ4wfG+vTwCKNzfQEAAFA9NMGlLN2Yq/vfy1LpZLMDR07o/veyfH6KmtG5vgAAAPAdlyJP4yhyasLinDINsKSSbRMW58hRVfgvAAAATI0m+DQZOw67LYEozSkp98gJZew4XHNFAQAAwHA0wafJ+6XiBtiXcQAAADAnmuDTtGjS0NBxAAAAMCea4NMkRzdXy7CGqigIzSZXSkRydPOaLAsAAAAGC2gTnJmZqfvuu08pKSmKiYlRenp6IMuRPcim8QNdub2lG+Hi1+MHxvqUF+wocmrVtkP6x/p9WrXtEDfXAQAABFBAI9IKCgoUExOj66+/Xg8++GAgSynRv0tLvXF7Qpmc4Mhq5AQbnTsMAACA6gloE9y7d2/17t07kCWUq3+XlrosNtKQJ8b5K3cYAAAAvuNhGRWwB9nUq/2Z1dpHVbnDNrlyhy+LjfSpwQYAAIBv6kQT7HA4yv0aaKu3H/Iod3j1tnz1bFe9htuszDYnVsd8mAvzYS7Mh7nUxHzY7Xa/7RvmVyea4Ozs7EpfB0rm7uOejdu4VQ2PNvJzNYFlljmBC/NhLsyHuTAf5uLP+UhMTPTbvmF+daIJjouLk91ul8PhUHZ2dsnrQDvR9JC0JrPKcUldOii+Dl8JNtOcWB3zYS7Mh7kwH+bCfMDf6kQTbLfb3X5ASr8OlJ7tw9UyrKEOHDlR7rpgm1ypEz3bh9f5NcFmmRO4MB/mwnyYC/NhLswH/CWgOcG//vqrNm/erM2bN0uS9u7dq82bN2v//v2BLMsw/swdBgAAgO8C2gRv3LhRgwYN0qBBgyRJkydP1qBBg/Taa68FsixDFecOR4a5P2o5Mqwh8WgAAAABEtDlED169ND3338fyBJqhJG5wwAAAKi+OrEmuDYwIncYAAAAxgjocggAAAAgEGiCAQAAYDk0wQAAALAcmmAAAABYDk0wAAAALIcmGAAAAJZDEwwAAADLoQkGAACA5dAEAwAAwHJoggEAAGA5NMEAAACwHJpgAAAAWA5NMAAAACyHJhgAAACWQxMMAAAAy6EJBgAAgOXUC3QB1eF0OiVJDoej3K8IPObEXJgPc2E+zIX5MJeamo+goCDZbDa/fg+Yk81Z3EnWQoWFhcrOzg50GQAAoJaKj4+X3W4PdBkIgFrdBBcVFenUqVP8LQ4AAPiEHsK6anUTDAAAAPiCG+MAAABgOTTBAAAAsByaYAAAAFgOTTAAAAAshyYYAAAAlkMTDAAAAMuhCQYAAIDl1Lom+P3331ffvn0VFxenG2+8URs2bKh0/Oeff67+/fsrLi5OAwcO1H//+98aqtQavJmPBQsWKCYmxu2/uLi4Gqy2bsvMzNR9992nlJQUxcTEKD09vcrPrFmzRoMHD1aXLl102WWXacGCBTVQqTV4Ox9r1qwp8/MRExOj/Pz8Gqq4bps5c6auv/56devWTb169dKIESO0ffv2Kj/HnyH+4ct88GcIjFarmuAlS5Zo8uTJeuCBB/Tpp5+qY8eOGj58uA4dOlTu+KysLD3++OO64YYbtHDhQl166aV64IEHtHXr1hquvG7ydj4kKTQ0VCtXriz57z//+U8NVly3FRQUKCYmRuPHj/do/J49e3TvvfeqR48e+sc//qFhw4bp6aef1ooVK/xcqTV4Ox/Fli5d6vYzcuaZZ/qpQmvJyMjQbbfdpvnz52v27Nk6deqUhg8froKCggo/w58h/uPLfEj8GQKDOWuRG264wTlhwoSS1w6Hw5mSkuKcOXNmueMfeeQR55///Ge3bTfeeKNz3Lhxfq3TKrydj08++cSZmJhYU+VZWocOHZz/+te/Kh3z/PPPO6+66iq3bY8++qjzrrvu8mdpluTJfKxevdrZoUMH55EjR2qoKms7dOiQs0OHDs6MjIwKx/BnSM3xZD74MwRGqzVXggsLC7Vp0yZdcMEFJduCgoJ0wQUX6Ntvvy33M+vXr1evXr3ctqWkpGj9+vX+LNUSfJkPyXV1rE+fPurdu7fuv/9+/fDDDzVRLsrBz4c5DRo0SCkpKbrzzju1bt26QJdTZ/3yyy+SpLCwsArH8DNSczyZD4k/Q2CsWtME//TTT3I4HGX+afDMM8/Ujz/+WO5nfvzxR5111lkej4fnfJmP6OhoPffcc3r99df1wgsvyOl06uabb9aBAwdqomSUUt7Px1lnnaVjx47pxIkTAarKusLDwzVhwgS99tpreu211xQZGamhQ4dq06ZNgS6tzikqKtJzzz2nhIQEdejQocJx/BlSMzydD/4MgdHqBboAWEe3bt3UrVs3t9cDBgzQhx9+qEcffTRwhQEm0K5dO7Vr167kdUJCgvbs2aM5c+bohRdeCGBldc+ECRP0ww8/6O9//3ugS4E8nw/+DIHRas2V4GbNmslut5e56erQoUNl/qZe7KyzzirzN/bKxsNzvsxHafXr11enTp20e/duf5SIKpT38/Hjjz8qNDRUDRs2DFBVOF1cXBw/HwabOHGili9frrS0NEVGRlY6lj9D/M+b+SiNP0NQXbWmCQ4ODlbnzp21atWqkm1FRUVatWqV298MTxcfH6/Vq1e7bfvmm28UHx/vz1ItwZf5KM3hcGjr1q0KDw/3V5moBD8f5rdlyxZ+PgzidDo1ceJE/etf/1JaWpratGlT5Wf4GfEfX+ajNP4MQXXVquUQd955p0aNGqUuXbqoa9euSktL0/Hjx3XddddJkv7yl78oIiJCjz/+uCRp6NChGjJkiN555x317t1bS5Ys0caNGzVx4sRAHkad4e18TJ8+XfHx8YqKitLRo0f19ttva//+/brxxhsDeRh1xq+//up2RWTv3r3avHmzwsLC1KpVK7300ks6ePCgnn/+eUnSzTffrPfff1/PP/+8rr/+eq1evVqff/65Zs6cGahDqFO8nY85c+aodevWOu+88/Tbb7/po48+0urVq/XOO+8E6hDqlAkTJuizzz7T66+/rsaNG5fkLzdp0qTkXz74M6Tm+DIf/BkCo9WqJnjAgAE6fPiwXnvtNeXn56tTp07629/+VvJPU7m5uQoK+uPidkJCgl588UW98sorSk1NVdu2bTVjxoxKF97Dc97Ox9GjRzVu3Djl5+crLCxMnTt31ocffqhzzz03UIdQp2zcuFFDhw4teT158mRJ0uDBgzVlyhTl5+crNze35P02bdpo5syZmjx5st59911FRkbqmWee0UUXXVTjtddF3s7HyZMnNXXqVB08eFCNGjVShw4dNHv2bPXs2bPGa6+LPvjgA0nSkCFD3LZPnjy55C/u/BlSc3yZD/4MgdFsTqfTGegiAAAAgJpUa9YEAwAAAEahCQYAAIDl0AQDAADAcmiCAQAAYDk0wQAAALAcmmAAAABYDk0wAAAALIcmGAAAAJZDEwyg1lqzZo1iYmJ09OhRw/cdExOj9PT0Ct/fu3evYmJitHnz5kr3M2TIED377LNGlwcAqCaaYAABt2DBAnXv3j3QZbhZuXKlLr74Yo/H+7MhBwAYr16gCwAAMwoPDw90CQAAP+JKMIBqGzJkiCZOnKiJEycqMTFRPXr00CuvvCKn0ylJKiws1NSpU3XRRRcpPj5eN954o9asWSPJdQX1qaee0i+//KKYmBjFxMRo2rRpkqSFCxfquuuuU7du3XThhRfq8ccf16FDh7yuz+l0qmfPnlq6dGnJtmuvvVYpKSklr9euXasuXbro+PHjksouh9iwYYMGDRqkuLg4XXfddW7LIPbu3auhQ4dKkpKSkhQTE6PRo0e7ff/nn39eycnJuvDCC0uODwAQODTBAAzx6aefym6366OPPtLYsWM1Z84cffTRR5KkiRMn6ttvv9XLL7+sRYsWqX///rr77ru1c+dOdevWTWPGjFFoaKhWrlyplStX6q677pIknTp1So888ogWLVqkGTNmaN++fW7NpadsNpuSkpKUkZEhSTpy5Ii2bdumEydOaNu2bZKkzMxMxcXFqVGjRmU+/+uvv+ree+9V+/bttWDBAj300EOaOnVqyfstW7YsaWyXLl2qlStXauzYsW7nJiQkRPPnz9eTTz6pGTNm6Ouvv/b6OAAAxmE5BABDtGzZUmPGjJHNZlO7du20detWzZkzRykpKVqwYIH+85//KCIiQpI0fPhwrVixQgsWLNDIkSPVpEkT2Wy2MksQbrjhhpL/b9OmjcaOHasbbrhBv/76qxo3buxVfcnJyZo3b54kV8MbGxurs846SxkZGWrfvr0yMjKUnJxc7mc/++wzFRUV6bnnnlODBg103nnn6cCBA/rrX/8qSbLb7QoLC5MknXnmmWratKnb52NiYvTggw9Kktq2bav33ntPq1at0oUXXujVMQAAjEMTDMAQ559/vmw2W8nr+Ph4zZ49W1u3bpXD4VD//v3dxhcWFuqMM86odJ8bN27U9OnTtWXLFh05cqRkeUVubq7OPfdcr+pLSkrSs88+q8OHDyszM1PJycklTfANN9ygb7/9VnfffXe5n922bZtiYmLUoEGDkm3dunXz+HvHxMS4vQ4PD/dpWQcAwDg0wQD8qqCgQHa7XZ988onsdrvbeyEhIZV+bvjw4UpJSdGLL76oZs2aKTc3V8OHD9fJkye9riMmJkZhYWHKyMhQZmamHn30UYWHh+tvf/ubsrOzderUKa8aW2/Uq+f+W63NZitp6AEAgUETDMAQGzZscHv93XffKSoqSp06dZLD4dDhw4crjEGrX7++HA6H27bt27fr559/1hNPPKGWLVtKcl0Z9pXNZlP37t3173//Wz/88IMSExPVqFEjFRYWat68eerSpUuFTXn79u31j3/8Q7/99lvJ1eD169eXOQZJZY4DAGBO3BgHwBD79+/X5MmTtX37dn322Wd67733NHToUEVHR2vgwIH6y1/+omXLlmnPnj3asGGDZs6cqeXLl0uSzj77bBUUFGjVqlU6fPiwjh8/rlatWql+/fqaO3eu9uzZo3//+996/fXXq1VjcnKy/vnPf6pTp05q3LixgoKC1L17dy1evFhJSUkVfu7qq6+WzWbT008/rf/973/673//q3feecdtzNlnny2bzably5fr8OHD+vXXX6tVKwDAv2iCARhi0KBBOnHihG688UZNnDhRQ4cO1U033SRJmjx5sgYNGqQpU6boyiuv1IgRI5SdnV1yhTchIUE333yzHn30UfXq1Ut/+9vf1Lx5c02ZMkVLly7VgAEDNGvWLI0aNapaNSYnJ8vhcLjdAFfettIaN26sN998U1u3btWgQYP08ssv64knnnAbExERoYceekgvvfSSLrjgAk2aNKlatQIA/MvmZGEagGoaMmSIOnbs6BYLBgCAmXElGAAAAJbDjXEA6oS7775b69atK/e9e++9V/fdd18NVwQAMDOWQwCoEw4ePKgTJ06U+15YWFiVmcQAAGuhCQYAAIDlsCYYAAAAlkMTDAAAAMuhCQYAAIDl0AQDAADAcmiCAQAAYDk0wQAAALAcmmAAAABYDk0wAAAALOf/AYgMK17rWFDhAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(10,5))\n",
        "sns.heatmap(correlation_matrix,annot=True , cmap='RdYlGn')\n",
        "plt.title(\"Correlation of Iris dataset\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 468
        },
        "id": "AT0hq5kYh6MH",
        "outputId": "3dbd4c1a-aa0b-45a0-d135-618334ea6c52"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Visualize the data before handling outliers\n",
        "plt.figure(figsize=(8, 6))\n",
        "sns.boxplot(data=iris)\n",
        "plt.title(\"Data with Outliers\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 545
        },
        "id": "M8T00HtSjJUc",
        "outputId": "6f240317-48b4-43dc-c178-bfc3c5c1427b"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Building the classification model\n",
        "X = iris.drop(['species'], axis=1)\n",
        "y = iris['species']\n",
        "# Split the data into train and test\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
        "# Create model\n",
        "lg = LogisticRegression()\n",
        "\n",
        "#Fit the model\n",
        "clf = lg.fit(X_train, y_train)\n",
        "# Predict the model\n",
        "y_pred = clf.predict(X_test)\n",
        "#Evaluate the model\n",
        "print(classification_report(y_test, y_pred))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yEybQFr3jcAg",
        "outputId": "5ea6d5b0-4cbe-4074-c197-f8780a4e7cb5"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "      setosa       1.00      1.00      1.00        10\n",
            "  versicolor       1.00      1.00      1.00         9\n",
            "   virginica       1.00      1.00      1.00        11\n",
            "\n",
            "    accuracy                           1.00        30\n",
            "   macro avg       1.00      1.00      1.00        30\n",
            "weighted avg       1.00      1.00      1.00        30\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Accuracy Score : \", accuracy_score(y_test, y_pred)*100)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UVVE-j1IoV_-",
        "outputId": "da7bd1c1-3c81-4f0f-e113-f4bef18069e8"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy Score :  100.0\n"
          ]
        }
      ]
    }
  ]
}