prodigy_infotech_Task_2.ipynb

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        "<a href=\"https://colab.research.google.com/github/akashlogics/prodigy-infotech-intership/blob/main/prodigy_infotech_Task_2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "cell_type": "markdown",
      "source": [
        "# **Mall Customer Segmentation Data**"
      ],
      "metadata": {
        "id": "f1GW0cI_DdND"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np # linear algebra\n",
        "import pandas as pd # data processing, CSV file I/O\n",
        "import os\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "for dirname, _, filenames in os.walk('/content/Mall_Customers.csv'):\n",
        "    for filename in filenames:\n",
        "        os.path.join(dirname, filename)"
      ],
      "metadata": {
        "id": "S72roaHNDgZF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df=pd.read_csv(\"/content/Mall_Customers.csv\")\n",
        "df.describe()"
      ],
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          "height": 300
        },
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        "outputId": "13e8e523-0ac4-4033-82ce-fcb95f711dc2"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       CustomerID         Age  Annual Income (k$)  Spending Score (1-100)\n",
              "count  200.000000  200.000000          200.000000              200.000000\n",
              "mean   100.500000   38.850000           60.560000               50.200000\n",
              "std     57.879185   13.969007           26.264721               25.823522\n",
              "min      1.000000   18.000000           15.000000                1.000000\n",
              "25%     50.750000   28.750000           41.500000               34.750000\n",
              "50%    100.500000   36.000000           61.500000               50.000000\n",
              "75%    150.250000   49.000000           78.000000               73.000000\n",
              "max    200.000000   70.000000          137.000000               99.000000"
            ],
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              "      <th></th>\n",
              "      <th>CustomerID</th>\n",
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              "      <th>Annual Income (k$)</th>\n",
              "      <th>Spending Score (1-100)</th>\n",
              "    </tr>\n",
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              "      <th>count</th>\n",
              "      <td>200.000000</td>\n",
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              "      <td>200.000000</td>\n",
              "      <td>200.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>100.500000</td>\n",
              "      <td>38.850000</td>\n",
              "      <td>60.560000</td>\n",
              "      <td>50.200000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>57.879185</td>\n",
              "      <td>13.969007</td>\n",
              "      <td>26.264721</td>\n",
              "      <td>25.823522</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>15.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>50.750000</td>\n",
              "      <td>28.750000</td>\n",
              "      <td>41.500000</td>\n",
              "      <td>34.750000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>100.500000</td>\n",
              "      <td>36.000000</td>\n",
              "      <td>61.500000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>150.250000</td>\n",
              "      <td>49.000000</td>\n",
              "      <td>78.000000</td>\n",
              "      <td>73.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>200.000000</td>\n",
              "      <td>70.000000</td>\n",
              "      <td>137.000000</td>\n",
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              "type": "dataframe",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"CustomerID\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 71.77644232399086,\n        \"min\": 1.0,\n        \"max\": 200.0,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          200.0,\n          100.5,\n          150.25\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 60.50135224289181,\n        \"min\": 13.96900733155888,\n        \"max\": 200.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          38.85,\n          36.0,\n          200.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Annual Income (k$)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 62.01038341270951,\n        \"min\": 15.0,\n        \"max\": 200.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          60.56,\n          61.5,\n          200.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Spending Score (1-100)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 61.42496609345541,\n        \"min\": 1.0,\n        \"max\": 200.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          50.2,\n          50.0,\n          200.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
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          "metadata": {},
          "execution_count": 20
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      "execution_count": null,
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 200 entries, 0 to 199\n",
            "Data columns (total 5 columns):\n",
            " #   Column                  Non-Null Count  Dtype \n",
            "---  ------                  --------------  ----- \n",
            " 0   CustomerID              200 non-null    int64 \n",
            " 1   Gender                  200 non-null    object\n",
            " 2   Age                     200 non-null    int64 \n",
            " 3   Annual Income (k$)      200 non-null    int64 \n",
            " 4   Spending Score (1-100)  200 non-null    int64 \n",
            "dtypes: int64(4), object(1)\n",
            "memory usage: 7.9+ KB\n"
          ]
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      "source": [
        "df[\"Gender\"].value_counts()"
      ],
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Gender\n",
              "Female    112\n",
              "Male       88\n",
              "Name: count, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
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              "CustomerID                0\n",
              "Gender                    0\n",
              "Age                       0\n",
              "Annual Income (k$)        0\n",
              "Spending Score (1-100)    0\n",
              "dtype: int64"
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              "<Axes: >"
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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.scatterplot(data=df,x=\"Spending Score (1-100)\",y=\"Annual Income (k$)\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 466
        },
        "id": "7Bnq6_Xz7hNQ",
        "outputId": "60f16797-118a-47df-ca40-6a096a10ad36"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='Spending Score (1-100)', ylabel='Annual Income (k$)'>"
            ]
          },
          "metadata": {},
          "execution_count": 25
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.histplot(data=df,x=\"Age\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 466
        },
        "id": "m0umwapv7uRP",
        "outputId": "bedd68fe-68fb-41b7-d159-14ad60ca50fc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='Age', ylabel='Count'>"
            ]
          },
          "metadata": {},
          "execution_count": 26
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.cluster import KMeans\n",
        "sse = []\n",
        "k_rng = range(1,10)\n",
        "for k in k_rng:\n",
        "    km = KMeans(n_clusters=k)\n",
        "    km.fit(df[['Spending Score (1-100)','Annual Income (k$)']])\n",
        "    sse.append(km.inertia_)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Q7nyiNMy7z88",
        "outputId": "d31fcc37-d08e-47ab-d592-075beccb2cb2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.xlabel('K')\n",
        "plt.ylabel('Sum of squared error')\n",
        "plt.plot(k_rng,sse)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 466
        },
        "id": "_MhBj8Fr8Ids",
        "outputId": "2b096a37-af0c-4fcc-cb8f-496eb7e56531"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7b5a55329b70>]"
            ]
          },
          "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": [
        "clf=KMeans(n_clusters=5)\n",
        "y_predicted = km.fit_predict(df[['Spending Score (1-100)','Annual Income (k$)']])\n",
        "y_predicted"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WZ8PKi9G8I9s",
        "outputId": "fbfcc8e4-2c57-408e-f0c5-ff887aef53af"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([6, 3, 4, 3, 6, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 6, 3, 6, 3, 6, 3,\n",
              "       4, 3, 4, 3, 6, 3, 6, 3, 4, 3, 4, 3, 4, 3, 4, 3, 6, 3, 6, 3, 6, 0,\n",
              "       6, 0, 0, 0, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
              "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 0, 0, 8, 8, 0, 0, 0, 0,\n",
              "       0, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8,\n",
              "       8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 2, 8, 2, 8, 2, 5, 2, 5, 2,\n",
              "       8, 2, 5, 2, 5, 2, 5, 2, 5, 2, 8, 2, 5, 2, 8, 2, 5, 2, 5, 2, 5, 2,\n",
              "       5, 2, 5, 2, 5, 2, 8, 2, 5, 2, 5, 2, 5, 2, 5, 2, 5, 2, 5, 2, 5, 2,\n",
              "       5, 2, 5, 2, 1, 2, 1, 2, 1, 2, 1, 7, 1, 7, 1, 7, 1, 7, 1, 7, 1, 7,\n",
              "       1, 7], dtype=int32)"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['cluster']=y_predicted\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "QRN72Dcl8Ygj",
        "outputId": "792504ab-9ff8-4485-bd4b-b7ff81842f5d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   CustomerID  Gender  Age  Annual Income (k$)  Spending Score (1-100)  \\\n",
              "0           1    Male   19                  15                      39   \n",
              "1           2    Male   21                  15                      81   \n",
              "2           3  Female   20                  16                       6   \n",
              "3           4  Female   23                  16                      77   \n",
              "4           5  Female   31                  17                      40   \n",
              "\n",
              "   cluster  \n",
              "0        6  \n",
              "1        3  \n",
              "2        4  \n",
              "3        3  \n",
              "4        6  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-ed3f44e9-0ebf-43c2-9ba4-22f176b0cb89\" 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>CustomerID</th>\n",
              "      <th>Gender</th>\n",
              "      <th>Age</th>\n",
              "      <th>Annual Income (k$)</th>\n",
              "      <th>Spending Score (1-100)</th>\n",
              "      <th>cluster</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Male</td>\n",
              "      <td>19</td>\n",
              "      <td>15</td>\n",
              "      <td>39</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>Male</td>\n",
              "      <td>21</td>\n",
              "      <td>15</td>\n",
              "      <td>81</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>Female</td>\n",
              "      <td>20</td>\n",
              "      <td>16</td>\n",
              "      <td>6</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>Female</td>\n",
              "      <td>23</td>\n",
              "      <td>16</td>\n",
              "      <td>77</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>Female</td>\n",
              "      <td>31</td>\n",
              "      <td>17</td>\n",
              "      <td>40</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ed3f44e9-0ebf-43c2-9ba4-22f176b0cb89')\"\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 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-ed3f44e9-0ebf-43c2-9ba4-22f176b0cb89 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-ed3f44e9-0ebf-43c2-9ba4-22f176b0cb89');\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-f877612a-e198-40e0-81b6-07fdb722d5c3\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-f877612a-e198-40e0-81b6-07fdb722d5c3')\"\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",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </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-f877612a-e198-40e0-81b6-07fdb722d5c3 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 200,\n  \"fields\": [\n    {\n      \"column\": \"CustomerID\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 57,\n        \"min\": 1,\n        \"max\": 200,\n        \"num_unique_values\": 200,\n        \"samples\": [\n          96,\n          16,\n          31\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Gender\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Female\",\n          \"Male\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 13,\n        \"min\": 18,\n        \"max\": 70,\n        \"num_unique_values\": 51,\n        \"samples\": [\n          55,\n          26\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Annual Income (k$)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 26,\n        \"min\": 15,\n        \"max\": 137,\n        \"num_unique_values\": 64,\n        \"samples\": [\n          87,\n          101\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Spending Score (1-100)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25,\n        \"min\": 1,\n        \"max\": 99,\n        \"num_unique_values\": 84,\n        \"samples\": [\n          83,\n          39\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"cluster\",\n      \"properties\": {\n        \"dtype\": \"int32\",\n        \"num_unique_values\": 9,\n        \"samples\": [\n          1,\n          3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df1 = df[df.cluster==0]\n",
        "df2 = df[df.cluster==1]\n",
        "df3 = df[df.cluster==2]\n",
        "df4 = df[df.cluster==3]\n",
        "plt.scatter(df1['Spending Score (1-100)'],df1['Annual Income (k$)'] ,color='green',label='1')\n",
        "plt.scatter(df2['Spending Score (1-100)'],df2['Annual Income (k$)'] ,color='red',label='2')\n",
        "plt.scatter(df3['Spending Score (1-100)'],df3['Annual Income (k$)'] ,color='black',label='3')\n",
        "plt.scatter(df4['Spending Score (1-100)'],df4['Annual Income (k$)'],color='blue',label='4')\n",
        "plt.scatter(km.cluster_centers_[:,0],km.cluster_centers_[:,1],color='purple',marker='*',label='centroid')\n",
        "plt.legend()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        },
        "id": "Vm0ZbXaY8Y9t",
        "outputId": "4fb7b8d5-2a77-438d-9418-f0684b14bd9d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7b5a526cd060>"
            ]
          },
          "metadata": {},
          "execution_count": 31
        },
        {
          "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": [
        "df.hist(bins=50,figsize=(12,8))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 786
        },
        "id": "lOMnauaU9HDb",
        "outputId": "dce3626e-d561-4ab1-e108-c937159e424b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[<Axes: title={'center': 'CustomerID'}>,\n",
              "        <Axes: title={'center': 'Age'}>],\n",
              "       [<Axes: title={'center': 'Annual Income (k$)'}>,\n",
              "        <Axes: title={'center': 'Spending Score (1-100)'}>],\n",
              "       [<Axes: title={'center': 'cluster'}>, <Axes: >]], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 32
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x800 with 6 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}