Clustering.ipynb

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      "name": "Untitled6.ipynb",
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
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      "source": [
        "<a href=\"https://colab.research.google.com/github/DiogoKarmouche/Clustering/blob/main/Clustering.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Assigment 9- Portifólio: Clustering"
      ],
      "metadata": {
        "id": "kBQe3Z4OIiqK"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Informações do dataset"
      ],
      "metadata": {
        "id": "xXCK0o4sK-6n"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**CUSTID** : Identification of Credit Card holder (Categorical)\n",
        "\n",
        "**BALANCE** : Balance amount left in their account to make purchases (\n",
        "\n",
        "**BALANCEFREQUENCY** : How frequently the Balance is updated, score between 0 and 1 (1 = frequently updated, 0 = not frequently updated)\n",
        "\n",
        "**PURCHASES** : Amount of purchases made from account\n",
        "\n",
        "**ONEOFFPURCHASES** : Maximum purchase amount done in one-go\n",
        "\n",
        "**INSTALLMENTSPURCHASES** : Amount of purchase done in installment\n",
        "\n",
        "**CASHADVANCE** : Cash in advance given by the user\n",
        "\n",
        "**PURCHASESFREQUENCY** : How frequently the Purchases are being made, score between 0 and 1 (1 = frequently purchased, 0 = not frequently purchased)\n",
        "\n",
        "**ONEOFFPURCHASESFREQUENCY** : How frequently Purchases are happening in one-go (1 = frequently purchased, 0 = not frequently purchased)\n",
        "\n",
        "**PURCHASESINSTALLMENTSFREQUENCY** : How frequently purchases in installments are being done (1 = frequently done, 0 = not frequently done)\n",
        "\n",
        "**CASHADVANCEFREQUENCY** : How frequently the cash in advance being paid\n",
        "\n",
        "**CASHADVANCETRX** : Number of Transactions made with \"Cash in Advanced\"\n",
        "\n",
        "**PURCHASESTRX** : Numbe of purchase transactions made\n",
        "\n",
        "**CREDITLIMIT** : Limit of Credit Card for user\n",
        "\n",
        "**PAYMENTS** : Amount of Payment done by user\n",
        "\n",
        "**MINIMUM_PAYMENTS** : Minimum amount of payments made by user\n",
        "\n",
        "**PRCFULLPAYMENT** : Percent of full payment paid by user\n",
        "\n",
        "**TENURE** : Tenure of credit card service for user"
      ],
      "metadata": {
        "id": "dvMvdkfALwwo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "id": "3e2o8Y2ALsew",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c65fe649-ca26-4dec-e620-e53fdc59dc26"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Carregando dataset e bibliotecas"
      ],
      "metadata": {
        "id": "Y8eoDyM_ItcH"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "h2YpnAZbITlx"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.preprocessing import StandardScaler\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv('/content/drive/MyDrive/dex/CC GENERAL.csv')"
      ],
      "metadata": {
        "id": "IfqHFXzaIz3f"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
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        "id": "pEXwd19ZKS8H",
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              "  CUST_ID      BALANCE  BALANCE_FREQUENCY  PURCHASES  ONEOFF_PURCHASES  \\\n",
              "0  C10001    40.900749           0.818182      95.40              0.00   \n",
              "1  C10002  3202.467416           0.909091       0.00              0.00   \n",
              "2  C10003  2495.148862           1.000000     773.17            773.17   \n",
              "3  C10004  1666.670542           0.636364    1499.00           1499.00   \n",
              "4  C10005   817.714335           1.000000      16.00             16.00   \n",
              "\n",
              "   INSTALLMENTS_PURCHASES  CASH_ADVANCE  PURCHASES_FREQUENCY  \\\n",
              "0                    95.4      0.000000             0.166667   \n",
              "1                     0.0   6442.945483             0.000000   \n",
              "2                     0.0      0.000000             1.000000   \n",
              "3                     0.0    205.788017             0.083333   \n",
              "4                     0.0      0.000000             0.083333   \n",
              "\n",
              "   ONEOFF_PURCHASES_FREQUENCY  PURCHASES_INSTALLMENTS_FREQUENCY  \\\n",
              "0                    0.000000                          0.083333   \n",
              "1                    0.000000                          0.000000   \n",
              "2                    1.000000                          0.000000   \n",
              "3                    0.083333                          0.000000   \n",
              "4                    0.083333                          0.000000   \n",
              "\n",
              "   CASH_ADVANCE_FREQUENCY  CASH_ADVANCE_TRX  PURCHASES_TRX  CREDIT_LIMIT  \\\n",
              "0                0.000000                 0              2        1000.0   \n",
              "1                0.250000                 4              0        7000.0   \n",
              "2                0.000000                 0             12        7500.0   \n",
              "3                0.083333                 1              1        7500.0   \n",
              "4                0.000000                 0              1        1200.0   \n",
              "\n",
              "      PAYMENTS  MINIMUM_PAYMENTS  PRC_FULL_PAYMENT  TENURE  \n",
              "0   201.802084        139.509787          0.000000      12  \n",
              "1  4103.032597       1072.340217          0.222222      12  \n",
              "2   622.066742        627.284787          0.000000      12  \n",
              "3     0.000000               NaN          0.000000      12  \n",
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              "      <th>CREDIT_LIMIT</th>\n",
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              "          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",
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          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Limpeza dos dados"
      ],
      "metadata": {
        "id": "MSgGJkQGMB-W"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "removendo dados não necessários, como a coluna **CUST_ID**"
      ],
      "metadata": {
        "id": "9EOn2DgRMJD_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_new = df.copy() # criando um cópia do dataset original"
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      "metadata": {
        "id": "00gImIRaMA_-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_new.drop('CUST_ID',axis=1,inplace=True)"
      ],
      "metadata": {
        "id": "v4M3j90SMskt"
      },
      "execution_count": null,
      "outputs": []
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        "df_new.head()"
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              "       BALANCE  BALANCE_FREQUENCY  PURCHASES  ONEOFF_PURCHASES  \\\n",
              "0    40.900749           0.818182      95.40              0.00   \n",
              "1  3202.467416           0.909091       0.00              0.00   \n",
              "2  2495.148862           1.000000     773.17            773.17   \n",
              "3  1666.670542           0.636364    1499.00           1499.00   \n",
              "4   817.714335           1.000000      16.00             16.00   \n",
              "\n",
              "   INSTALLMENTS_PURCHASES  CASH_ADVANCE  PURCHASES_FREQUENCY  \\\n",
              "0                    95.4      0.000000             0.166667   \n",
              "1                     0.0   6442.945483             0.000000   \n",
              "2                     0.0      0.000000             1.000000   \n",
              "3                     0.0    205.788017             0.083333   \n",
              "4                     0.0      0.000000             0.083333   \n",
              "\n",
              "   ONEOFF_PURCHASES_FREQUENCY  PURCHASES_INSTALLMENTS_FREQUENCY  \\\n",
              "0                    0.000000                          0.083333   \n",
              "1                    0.000000                          0.000000   \n",
              "2                    1.000000                          0.000000   \n",
              "3                    0.083333                          0.000000   \n",
              "4                    0.083333                          0.000000   \n",
              "\n",
              "   CASH_ADVANCE_FREQUENCY  CASH_ADVANCE_TRX  PURCHASES_TRX  CREDIT_LIMIT  \\\n",
              "0                0.000000                 0              2        1000.0   \n",
              "1                0.250000                 4              0        7000.0   \n",
              "2                0.000000                 0             12        7500.0   \n",
              "3                0.083333                 1              1        7500.0   \n",
              "4                0.000000                 0              1        1200.0   \n",
              "\n",
              "      PAYMENTS  MINIMUM_PAYMENTS  PRC_FULL_PAYMENT  TENURE  \n",
              "0   201.802084        139.509787          0.000000      12  \n",
              "1  4103.032597       1072.340217          0.222222      12  \n",
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              "    .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>BALANCE</th>\n",
              "      <th>BALANCE_FREQUENCY</th>\n",
              "      <th>PURCHASES</th>\n",
              "      <th>ONEOFF_PURCHASES</th>\n",
              "      <th>INSTALLMENTS_PURCHASES</th>\n",
              "      <th>CASH_ADVANCE</th>\n",
              "      <th>PURCHASES_FREQUENCY</th>\n",
              "      <th>ONEOFF_PURCHASES_FREQUENCY</th>\n",
              "      <th>PURCHASES_INSTALLMENTS_FREQUENCY</th>\n",
              "      <th>CASH_ADVANCE_FREQUENCY</th>\n",
              "      <th>CASH_ADVANCE_TRX</th>\n",
              "      <th>PURCHASES_TRX</th>\n",
              "      <th>CREDIT_LIMIT</th>\n",
              "      <th>PAYMENTS</th>\n",
              "      <th>MINIMUM_PAYMENTS</th>\n",
              "      <th>PRC_FULL_PAYMENT</th>\n",
              "      <th>TENURE</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>40.900749</td>\n",
              "      <td>0.818182</td>\n",
              "      <td>95.40</td>\n",
              "      <td>0.00</td>\n",
              "      <td>95.4</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.166667</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.083333</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1000.0</td>\n",
              "      <td>201.802084</td>\n",
              "      <td>139.509787</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3202.467416</td>\n",
              "      <td>0.909091</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6442.945483</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.250000</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>7000.0</td>\n",
              "      <td>4103.032597</td>\n",
              "      <td>1072.340217</td>\n",
              "      <td>0.222222</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2495.148862</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>773.17</td>\n",
              "      <td>773.17</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>7500.0</td>\n",
              "      <td>622.066742</td>\n",
              "      <td>627.284787</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1666.670542</td>\n",
              "      <td>0.636364</td>\n",
              "      <td>1499.00</td>\n",
              "      <td>1499.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>205.788017</td>\n",
              "      <td>0.083333</td>\n",
              "      <td>0.083333</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.083333</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>7500.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>817.714335</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>16.00</td>\n",
              "      <td>16.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.083333</td>\n",
              "      <td>0.083333</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1200.0</td>\n",
              "      <td>678.334763</td>\n",
              "      <td>244.791237</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-56936e61-4f17-4be7-85ca-01383d2e272c')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "    .colab-df-convert:hover {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "          document.querySelector('#df-56936e61-4f17-4be7-85ca-01383d2e272c 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-56936e61-4f17-4be7-85ca-01383d2e272c');\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",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "verificando se há valores nulos"
      ],
      "metadata": {
        "id": "i3WyrkZrNcZ-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_new.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5FN4AXPzNXmn",
        "outputId": "4334e3eb-15b4-4015-9c0b-3db470c92d5d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "BALANCE                               0\n",
              "BALANCE_FREQUENCY                     0\n",
              "PURCHASES                             0\n",
              "ONEOFF_PURCHASES                      0\n",
              "INSTALLMENTS_PURCHASES                0\n",
              "CASH_ADVANCE                          0\n",
              "PURCHASES_FREQUENCY                   0\n",
              "ONEOFF_PURCHASES_FREQUENCY            0\n",
              "PURCHASES_INSTALLMENTS_FREQUENCY      0\n",
              "CASH_ADVANCE_FREQUENCY                0\n",
              "CASH_ADVANCE_TRX                      0\n",
              "PURCHASES_TRX                         0\n",
              "CREDIT_LIMIT                          1\n",
              "PAYMENTS                              0\n",
              "MINIMUM_PAYMENTS                    313\n",
              "PRC_FULL_PAYMENT                      0\n",
              "TENURE                                0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "em caso de valores nulos, foi sugerido substituir os valores nulos pelo mínimo valor da coluna"
      ],
      "metadata": {
        "id": "6VVWr8u6NfEX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "display(min(df_new['MINIMUM_PAYMENTS']))\n",
        "display(min(df_new['CREDIT_LIMIT']))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        },
        "id": "v0D0LWKyNlPX",
        "outputId": "877bf6f9-7d0d-4f77-d4ff-201fa78f0148"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "0.019163"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "50.0"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_new['MINIMUM_PAYMENTS'].fillna(min(df_new['MINIMUM_PAYMENTS']),inplace=True)\n",
        "df_new['CREDIT_LIMIT'].fillna(min(df_new['CREDIT_LIMIT']),inplace=True)"
      ],
      "metadata": {
        "id": "gxTmdqnKN1im"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_new.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PGiSwVOaOCH1",
        "outputId": "5c13ee17-183f-4dd3-b07d-daf601e2e660"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "BALANCE                             0\n",
              "BALANCE_FREQUENCY                   0\n",
              "PURCHASES                           0\n",
              "ONEOFF_PURCHASES                    0\n",
              "INSTALLMENTS_PURCHASES              0\n",
              "CASH_ADVANCE                        0\n",
              "PURCHASES_FREQUENCY                 0\n",
              "ONEOFF_PURCHASES_FREQUENCY          0\n",
              "PURCHASES_INSTALLMENTS_FREQUENCY    0\n",
              "CASH_ADVANCE_FREQUENCY              0\n",
              "CASH_ADVANCE_TRX                    0\n",
              "PURCHASES_TRX                       0\n",
              "CREDIT_LIMIT                        0\n",
              "PAYMENTS                            0\n",
              "MINIMUM_PAYMENTS                    0\n",
              "PRC_FULL_PAYMENT                    0\n",
              "TENURE                              0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "remoção de outlier"
      ],
      "metadata": {
        "id": "XHLVxM0eYh0E"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "outlier = df_new.describe(percentiles=[0.15,0.3,0.45,0.60,0.75,0.95])\n",
        "outlier"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 490
        },
        "id": "NUyho5byOvVA",
        "outputId": "a74cd66a-aa14-405f-9467-b8737cc32886"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            BALANCE  BALANCE_FREQUENCY     PURCHASES  ONEOFF_PURCHASES  \\\n",
              "count   8950.000000        8950.000000   8950.000000       8950.000000   \n",
              "mean    1564.474828           0.877271   1003.204834        592.437371   \n",
              "std     2081.531879           0.236904   2136.634782       1659.887917   \n",
              "min        0.000000           0.000000      0.000000          0.000000   \n",
              "15%       44.512466           0.636364      0.000000          0.000000   \n",
              "30%      207.176552           0.909091     89.285000          0.000000   \n",
              "45%      665.632031           1.000000    282.396500          0.000000   \n",
              "50%      873.385231           1.000000    361.280000         38.000000   \n",
              "60%     1207.815587           1.000000    557.546000        168.378000   \n",
              "75%     2054.140036           1.000000   1110.130000        577.405000   \n",
              "95%     5909.111808           1.000000   3998.619500       2671.094000   \n",
              "max    19043.138560           1.000000  49039.570000      40761.250000   \n",
              "\n",
              "       INSTALLMENTS_PURCHASES  CASH_ADVANCE  PURCHASES_FREQUENCY  \\\n",
              "count             8950.000000   8950.000000          8950.000000   \n",
              "mean               411.067645    978.871112             0.490351   \n",
              "std                904.338115   2097.163877             0.401371   \n",
              "min                  0.000000      0.000000             0.000000   \n",
              "15%                  0.000000      0.000000             0.000000   \n",
              "30%                  0.000000      0.000000             0.083333   \n",
              "45%                 31.926000      0.000000             0.333333   \n",
              "50%                 89.000000      0.000000             0.500000   \n",
              "60%                213.950000    238.633724             0.666667   \n",
              "75%                468.637500   1113.821139             0.916667   \n",
              "95%               1750.087500   4647.169122             1.000000   \n",
              "max              22500.000000  47137.211760             1.000000   \n",
              "\n",
              "       ONEOFF_PURCHASES_FREQUENCY  PURCHASES_INSTALLMENTS_FREQUENCY  \\\n",
              "count                 8950.000000                       8950.000000   \n",
              "mean                     0.202458                          0.364437   \n",
              "std                      0.298336                          0.397448   \n",
              "min                      0.000000                          0.000000   \n",
              "15%                      0.000000                          0.000000   \n",
              "30%                      0.000000                          0.000000   \n",
              "45%                      0.000000                          0.083333   \n",
              "50%                      0.083333                          0.166667   \n",
              "60%                      0.083333                          0.416667   \n",
              "75%                      0.300000                          0.750000   \n",
              "95%                      1.000000                          1.000000   \n",
              "max                      1.000000                          1.000000   \n",
              "\n",
              "       CASH_ADVANCE_FREQUENCY  CASH_ADVANCE_TRX  PURCHASES_TRX  CREDIT_LIMIT  \\\n",
              "count             8950.000000       8950.000000    8950.000000   8950.000000   \n",
              "mean                 0.135144          3.248827      14.709832   4493.952864   \n",
              "std                  0.200121          6.824647      24.857649   3638.915681   \n",
              "min                  0.000000          0.000000       0.000000     50.000000   \n",
              "15%                  0.000000          0.000000       0.000000   1200.000000   \n",
              "30%                  0.000000          0.000000       1.000000   2000.000000   \n",
              "45%                  0.000000          0.000000       6.000000   3000.000000   \n",
              "50%                  0.000000          0.000000       7.000000   3000.000000   \n",
              "60%                  0.083333          1.000000      11.000000   4200.000000   \n",
              "75%                  0.222222          4.000000      17.000000   6500.000000   \n",
              "95%                  0.583333         15.000000      57.000000  12000.000000   \n",
              "max                  1.500000        123.000000     358.000000  30000.000000   \n",
              "\n",
              "           PAYMENTS  MINIMUM_PAYMENTS  PRC_FULL_PAYMENT       TENURE  \n",
              "count   8950.000000       8950.000000       8950.000000  8950.000000  \n",
              "mean    1733.143852        833.984123          0.153715    11.517318  \n",
              "std     2895.063757       2335.989679          0.292499     1.338331  \n",
              "min        0.000000          0.019163          0.000000     6.000000  \n",
              "15%      250.997079        118.472690          0.000000    11.000000  \n",
              "30%      459.438287        174.121321          0.000000    12.000000  \n",
              "45%      725.330384        239.691068          0.000000    12.000000  \n",
              "50%      856.901546        289.628402          0.000000    12.000000  \n",
              "60%     1185.259270        438.826129          0.000000    12.000000  \n",
              "75%     1901.134317        788.713501          0.142857    12.000000  \n",
              "95%     6082.090595       2719.566935          1.000000    12.000000  \n",
              "max    50721.483360      76406.207520          1.000000    12.000000  "
            ],
            "text/html": [
              "\n",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>BALANCE</th>\n",
              "      <th>BALANCE_FREQUENCY</th>\n",
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              "      <th>ONEOFF_PURCHASES</th>\n",
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              "      <th>CREDIT_LIMIT</th>\n",
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              "      <th>MINIMUM_PAYMENTS</th>\n",
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              "      <th>TENURE</th>\n",
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              "      <td>8950.000000</td>\n",
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              "      <td>8950.000000</td>\n",
              "      <td>8950.000000</td>\n",
              "      <td>8950.000000</td>\n",
              "      <td>8950.000000</td>\n",
              "      <td>8950.000000</td>\n",
              "      <td>8950.000000</td>\n",
              "      <td>8950.000000</td>\n",
              "      <td>8950.000000</td>\n",
              "      <td>8950.000000</td>\n",
              "      <td>8950.000000</td>\n",
              "      <td>8950.000000</td>\n",
              "      <td>8950.000000</td>\n",
              "      <td>8950.000000</td>\n",
              "      <td>8950.000000</td>\n",
              "      <td>8950.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>1564.474828</td>\n",
              "      <td>0.877271</td>\n",
              "      <td>1003.204834</td>\n",
              "      <td>592.437371</td>\n",
              "      <td>411.067645</td>\n",
              "      <td>978.871112</td>\n",
              "      <td>0.490351</td>\n",
              "      <td>0.202458</td>\n",
              "      <td>0.364437</td>\n",
              "      <td>0.135144</td>\n",
              "      <td>3.248827</td>\n",
              "      <td>14.709832</td>\n",
              "      <td>4493.952864</td>\n",
              "      <td>1733.143852</td>\n",
              "      <td>833.984123</td>\n",
              "      <td>0.153715</td>\n",
              "      <td>11.517318</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>2081.531879</td>\n",
              "      <td>0.236904</td>\n",
              "      <td>2136.634782</td>\n",
              "      <td>1659.887917</td>\n",
              "      <td>904.338115</td>\n",
              "      <td>2097.163877</td>\n",
              "      <td>0.401371</td>\n",
              "      <td>0.298336</td>\n",
              "      <td>0.397448</td>\n",
              "      <td>0.200121</td>\n",
              "      <td>6.824647</td>\n",
              "      <td>24.857649</td>\n",
              "      <td>3638.915681</td>\n",
              "      <td>2895.063757</td>\n",
              "      <td>2335.989679</td>\n",
              "      <td>0.292499</td>\n",
              "      <td>1.338331</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.019163</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>6.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15%</th>\n",
              "      <td>44.512466</td>\n",
              "      <td>0.636364</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1200.000000</td>\n",
              "      <td>250.997079</td>\n",
              "      <td>118.472690</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>11.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30%</th>\n",
              "      <td>207.176552</td>\n",
              "      <td>0.909091</td>\n",
              "      <td>89.285000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.083333</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>2000.000000</td>\n",
              "      <td>459.438287</td>\n",
              "      <td>174.121321</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>12.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45%</th>\n",
              "      <td>665.632031</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>282.396500</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>31.926000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.083333</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>3000.000000</td>\n",
              "      <td>725.330384</td>\n",
              "      <td>239.691068</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>12.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>873.385231</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>361.280000</td>\n",
              "      <td>38.000000</td>\n",
              "      <td>89.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.500000</td>\n",
              "      <td>0.083333</td>\n",
              "      <td>0.166667</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>7.000000</td>\n",
              "      <td>3000.000000</td>\n",
              "      <td>856.901546</td>\n",
              "      <td>289.628402</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>12.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>60%</th>\n",
              "      <td>1207.815587</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>557.546000</td>\n",
              "      <td>168.378000</td>\n",
              "      <td>213.950000</td>\n",
              "      <td>238.633724</td>\n",
              "      <td>0.666667</td>\n",
              "      <td>0.083333</td>\n",
              "      <td>0.416667</td>\n",
              "      <td>0.083333</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>4200.000000</td>\n",
              "      <td>1185.259270</td>\n",
              "      <td>438.826129</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>12.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>2054.140036</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1110.130000</td>\n",
              "      <td>577.405000</td>\n",
              "      <td>468.637500</td>\n",
              "      <td>1113.821139</td>\n",
              "      <td>0.916667</td>\n",
              "      <td>0.300000</td>\n",
              "      <td>0.750000</td>\n",
              "      <td>0.222222</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>17.000000</td>\n",
              "      <td>6500.000000</td>\n",
              "      <td>1901.134317</td>\n",
              "      <td>788.713501</td>\n",
              "      <td>0.142857</td>\n",
              "      <td>12.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>95%</th>\n",
              "      <td>5909.111808</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>3998.619500</td>\n",
              "      <td>2671.094000</td>\n",
              "      <td>1750.087500</td>\n",
              "      <td>4647.169122</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.583333</td>\n",
              "      <td>15.000000</td>\n",
              "      <td>57.000000</td>\n",
              "      <td>12000.000000</td>\n",
              "      <td>6082.090595</td>\n",
              "      <td>2719.566935</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>12.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>19043.138560</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>49039.570000</td>\n",
              "      <td>40761.250000</td>\n",
              "      <td>22500.000000</td>\n",
              "      <td>47137.211760</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.500000</td>\n",
              "      <td>123.000000</td>\n",
              "      <td>358.000000</td>\n",
              "      <td>30000.000000</td>\n",
              "      <td>50721.483360</td>\n",
              "      <td>76406.207520</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>12.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-38f55f83-2f61-498b-9f05-f37ece9ea4e2')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-38f55f83-2f61-498b-9f05-f37ece9ea4e2 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-38f55f83-2f61-498b-9f05-f37ece9ea4e2');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "outlier=outlier[['BALANCE','PURCHASES','MINIMUM_PAYMENTS','PAYMENTS','CREDIT_LIMIT','PURCHASES_TRX','ONEOFF_PURCHASES','CASH_ADVANCE','CASH_ADVANCE_TRX']]"
      ],
      "metadata": {
        "id": "m2Dz4IwtRgp8"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "outlier = outlier.loc['95%'].tolist()"
      ],
      "metadata": {
        "id": "DS1ixsVOSufT"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df = df_new[(df_new['BALANCE']<5909.111808)&\n",
        "            (df_new['PURCHASES']<3998.619500)&\n",
        "            (df_new['MINIMUM_PAYMENTS']<2719.566935)&\n",
        "            (df_new['PAYMENTS']<6082.090595)&\n",
        "            (df_new['CREDIT_LIMIT']<12000.000000)&\n",
        "            (df_new['PURCHASES_TRX']<57.000000)&\n",
        "            (df_new['ONEOFF_PURCHASES']<2671.094000)&\n",
        "            (df_new['CASH_ADVANCE']<4647.169122)&\n",
        "            (df_new['CASH_ADVANCE_TRX']<15.000000)]"
      ],
      "metadata": {
        "id": "NJU7mwSIZxXM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "scaler = StandardScaler()\n",
        "normalized_df = scaler.fit_transform(df[['BALANCE','PURCHASES','MINIMUM_PAYMENTS','PAYMENTS','CREDIT_LIMIT','PURCHASES_TRX','ONEOFF_PURCHASES','CASH_ADVANCE','CASH_ADVANCE_TRX']])"
      ],
      "metadata": {
        "id": "ll3wfTULYbYz"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## EDA"
      ],
      "metadata": {
        "id": "05LdFMCLYlmG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eDifqM8QYyUr",
        "outputId": "2944d472-5194-40ef-f5d5-6694c2ca4d7e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 6880 entries, 0 to 8949\n",
            "Data columns (total 17 columns):\n",
            " #   Column                            Non-Null Count  Dtype  \n",
            "---  ------                            --------------  -----  \n",
            " 0   BALANCE                           6880 non-null   float64\n",
            " 1   BALANCE_FREQUENCY                 6880 non-null   float64\n",
            " 2   PURCHASES                         6880 non-null   float64\n",
            " 3   ONEOFF_PURCHASES                  6880 non-null   float64\n",
            " 4   INSTALLMENTS_PURCHASES            6880 non-null   float64\n",
            " 5   CASH_ADVANCE                      6880 non-null   float64\n",
            " 6   PURCHASES_FREQUENCY               6880 non-null   float64\n",
            " 7   ONEOFF_PURCHASES_FREQUENCY        6880 non-null   float64\n",
            " 8   PURCHASES_INSTALLMENTS_FREQUENCY  6880 non-null   float64\n",
            " 9   CASH_ADVANCE_FREQUENCY            6880 non-null   float64\n",
            " 10  CASH_ADVANCE_TRX                  6880 non-null   int64  \n",
            " 11  PURCHASES_TRX                     6880 non-null   int64  \n",
            " 12  CREDIT_LIMIT                      6880 non-null   float64\n",
            " 13  PAYMENTS                          6880 non-null   float64\n",
            " 14  MINIMUM_PAYMENTS                  6880 non-null   float64\n",
            " 15  PRC_FULL_PAYMENT                  6880 non-null   float64\n",
            " 16  TENURE                            6880 non-null   int64  \n",
            "dtypes: float64(14), int64(3)\n",
            "memory usage: 967.5 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.describe().T"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 582
        },
        "id": "Z-eQCyE8Ym2q",
        "outputId": "68c44fb6-19b6-4640-e01f-2025244f3200"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                   count         mean          std        min  \\\n",
              "BALANCE                           6880.0   995.151694  1190.965770   0.000000   \n",
              "BALANCE_FREQUENCY                 6880.0     0.857780     0.252570   0.000000   \n",
              "PURCHASES                         6880.0   579.426174   721.139243   0.000000   \n",
              "ONEOFF_PURCHASES                  6880.0   300.337948   517.630795   0.000000   \n",
              "INSTALLMENTS_PURCHASES            6880.0   279.366419   452.429074   0.000000   \n",
              "CASH_ADVANCE                      6880.0   500.025960   902.031092   0.000000   \n",
              "PURCHASES_FREQUENCY               6880.0     0.469246     0.391970   0.000000   \n",
              "ONEOFF_PURCHASES_FREQUENCY        6880.0     0.162995     0.261136   0.000000   \n",
              "PURCHASES_INSTALLMENTS_FREQUENCY  6880.0     0.346478     0.386524   0.000000   \n",
              "CASH_ADVANCE_FREQUENCY            6880.0     0.100031     0.152807   0.000000   \n",
              "CASH_ADVANCE_TRX                  6880.0     1.823547     2.995315   0.000000   \n",
              "PURCHASES_TRX                     6880.0     9.750872    11.296587   0.000000   \n",
              "CREDIT_LIMIT                      6880.0  3456.202556  2465.720075  50.000000   \n",
              "PAYMENTS                          6880.0   974.664002   974.757099   0.000000   \n",
              "MINIMUM_PAYMENTS                  6880.0   410.897522   443.575376   0.019163   \n",
              "PRC_FULL_PAYMENT                  6880.0     0.153512     0.290509   0.000000   \n",
              "TENURE                            6880.0    11.468750     1.404998   6.000000   \n",
              "\n",
              "                                          25%          50%          75%  \\\n",
              "BALANCE                             75.973734   547.868765  1462.396758   \n",
              "BALANCE_FREQUENCY                    0.818182     1.000000     1.000000   \n",
              "PURCHASES                           41.400000   308.190000   832.010000   \n",
              "ONEOFF_PURCHASES                     0.000000     0.000000   395.012500   \n",
              "INSTALLMENTS_PURCHASES               0.000000    76.430000   387.702500   \n",
              "CASH_ADVANCE                         0.000000     0.000000   650.349033   \n",
              "PURCHASES_FREQUENCY                  0.083333     0.416667     0.916667   \n",
              "ONEOFF_PURCHASES_FREQUENCY           0.000000     0.000000     0.250000   \n",
              "PURCHASES_INSTALLMENTS_FREQUENCY     0.000000     0.166667     0.750000   \n",
              "CASH_ADVANCE_FREQUENCY               0.000000     0.000000     0.166667   \n",
              "CASH_ADVANCE_TRX                     0.000000     0.000000     3.000000   \n",
              "PURCHASES_TRX                        1.000000     6.000000    13.000000   \n",
              "CREDIT_LIMIT                      1500.000000  2700.000000  5000.000000   \n",
              "PAYMENTS                           320.166113   651.613201  1298.660032   \n",
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              "\n",
              "                                           max  \n",
              "BALANCE                            5906.184924  \n",
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              "CASH_ADVANCE_FREQUENCY                1.166667  \n",
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              "CREDIT_LIMIT                      11500.000000  \n",
              "PAYMENTS                           6043.227704  \n",
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              "TENURE                               12.000000  "
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              "      <td>0.083333</td>\n",
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              "      <td>1298.660032</td>\n",
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              "      <th>MINIMUM_PAYMENTS</th>\n",
              "      <td>6880.0</td>\n",
              "      <td>410.897522</td>\n",
              "      <td>443.575376</td>\n",
              "      <td>0.019163</td>\n",
              "      <td>145.768171</td>\n",
              "      <td>218.279833</td>\n",
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              "      <th>PRC_FULL_PAYMENT</th>\n",
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              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.166667</td>\n",
              "      <td>1.000000</td>\n",
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              "    <tr>\n",
              "      <th>TENURE</th>\n",
              "      <td>6880.0</td>\n",
              "      <td>11.468750</td>\n",
              "      <td>1.404998</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>12.000000</td>\n",
              "      <td>12.000000</td>\n",
              "      <td>12.000000</td>\n",
              "      <td>12.000000</td>\n",
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              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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          "metadata": {},
          "execution_count": 55
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      "cell_type": "code",
      "source": [
        "df.skew()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UNESDvpvhDLX",
        "outputId": "9d4af66a-8e75-4165-bc1d-85bcd43be01a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "BALANCE                             1.657985\n",
              "BALANCE_FREQUENCY                  -1.784670\n",
              "PURCHASES                           1.733119\n",
              "ONEOFF_PURCHASES                    2.150898\n",
              "INSTALLMENTS_PURCHASES              2.644484\n",
              "CASH_ADVANCE                        2.197890\n",
              "PURCHASES_FREQUENCY                 0.146781\n",
              "ONEOFF_PURCHASES_FREQUENCY          1.902771\n",
              "PURCHASES_INSTALLMENTS_FREQUENCY    0.582509\n",
              "CASH_ADVANCE_FREQUENCY              1.889330\n",
              "CASH_ADVANCE_TRX                    1.968691\n",
              "PURCHASES_TRX                       1.618780\n",
              "CREDIT_LIMIT                        1.098603\n",
              "PAYMENTS                            1.995513\n",
              "MINIMUM_PAYMENTS                    2.102209\n",
              "PRC_FULL_PAYMENT                    1.933730\n",
              "TENURE                             -2.755131\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 56
        }
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    {
      "cell_type": "code",
      "source": [
        "df.kurtosis()"
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        "outputId": "c13e76ee-059d-4187-a260-b4384af6ca1e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "BALANCE                             2.654931\n",
              "BALANCE_FREQUENCY                   2.068834\n",
              "PURCHASES                           2.861146\n",
              "ONEOFF_PURCHASES                    4.393224\n",
              "INSTALLMENTS_PURCHASES              9.016155\n",
              "CASH_ADVANCE                        4.549602\n",
              "PURCHASES_FREQUENCY                -1.579250\n",
              "ONEOFF_PURCHASES_FREQUENCY          2.807966\n",
              "PURCHASES_INSTALLMENTS_FREQUENCY   -1.281228\n",
              "CASH_ADVANCE_FREQUENCY              3.973434\n",
              "CASH_ADVANCE_TRX                    3.458518\n",
              "PURCHASES_TRX                       2.510806\n",
              "CREDIT_LIMIT                        0.474510\n",
              "PAYMENTS                            4.686560\n",
              "MINIMUM_PAYMENTS                    4.953503\n",
              "PRC_FULL_PAYMENT                    2.434585\n",
              "TENURE                              6.501901\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 57
        }
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    {
      "cell_type": "code",
      "source": [
        "for i in df.columns:\n",
        "  sns.displot(df[i],kde=True)"
      ],
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        "id": "r6FlnyaLjV0P",
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          "height": 1000
        },
        "outputId": "162508df-4be3-4dd5-8077-ade913274ad0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Library Import from sklearn.preprocessing import __________ \n",
        "['BALANCE','PURCHASES','MINIMUM_PAYMENTS','PAYMENTS','CREDIT_LIMIT','PURCHASES_TRX','ONEOFF_PURCHASES','CASH_ADVANCE','CASH_ADVANCE_TRX']\n",
        "from sklearn import metrics\n",
        "from sklearn.metrics import silhouette_score\n",
        "#v_measure_score\n",
        "from sklearn.cluster import KMeans \n",
        "# Normalize # Você deve montar o procedimento aqui _______________ _______________ _______________ \n",
        "scaler = StandardScaler()\n",
        "normalized_df = scaler.fit_transform(df[['BALANCE','PURCHASES','MINIMUM_PAYMENTS','PAYMENTS','CREDIT_LIMIT','PURCHASES_TRX','ONEOFF_PURCHASES','CASH_ADVANCE','CASH_ADVANCE_TRX']])"
      ],
      "metadata": {
        "id": "94rS3fb4npU2"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "alvo = normalized_df#df\n",
        "max = 15\n",
        "km_scores = []\n",
        "km_silhouette = []\n",
        "for i in range(2,max):\n",
        "  km = KMeans(n_clusters=i, random_state=0).fit(alvo)\n",
        "  preds = km.predict(alvo)\n",
        "  km_scores.append(-km.score(alvo))\n",
        "  silhouette = silhouette_score(alvo,preds)\n",
        "  km_silhouette.append(silhouette)\n",
        "  # Plotagem do método da Silhouette (Silhueta)\n",
        "plt.figure(figsize=(7,4))\n",
        "plt.title(\"Silhouette Method\",fontsize=16)\n",
        "plt.scatter(x=[i for i in range(2,max)],y=km_silhouette,s=150,edgecolor='k')\n",
        "plt.grid(True) \n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        },
        "id": "iBhJlNDCodkk",
        "outputId": "32fc1d27-0559-48ec-fec0-b4b209065ec9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 504x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Nota: Execute a seguinte ordem do processo: Standard -> Normalize -> PCA para 2 Dimensões -> Aplicar o GaussianMixture no resultante 2D.\n",
        "#Library Import \n",
        "from sklearn.preprocessing import StandardScaler, normalize\n",
        "from sklearn.mixture import GaussianMixture\n",
        "from sklearn.decomposition import PCA\n",
        "# Standardize data \n",
        "scaler = StandardScaler()\n",
        "#scaled_df = scaler.fit_transform(df)\n",
        "scaled_df =scaler.fit_transform(df[['BALANCE','PURCHASES','MINIMUM_PAYMENTS','PAYMENTS','CREDIT_LIMIT','PURCHASES_TRX','ONEOFF_PURCHASES','CASH_ADVANCE','CASH_ADVANCE_TRX']])\n",
        "# Normalizing \n",
        "normalized_df = normalize(scaled_df,axis=1)\n",
        "# PCA _____________ \n",
        "pca = PCA(n_components=2)\n",
        "X_principal = pca.fit_transform(normalized_df) \n",
        "X_principal = pd.DataFrame(X_principal) \n",
        "X_principal.columns = ['P1', 'P2'] \n",
        "# Plotagem da clusterização (em 2D) \n",
        "plt.title('Clusterização - Mistura Gaussiana',fontsize=25) \n",
        "plt.scatter(X_principal['P1'], \n",
        "            X_principal['P2'],\n",
        "            c = GaussianMixture(n_components = 8).fit_predict(X_principal),\n",
        "            alpha = 0.6,cmap='Blues')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IAmpTdtHkS3H",
        "outputId": "bfe1a66b-d6c6-4724-bc07-264bad2fe564"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}