Bank_marketing_Strategy.ipynb

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  "metadata": {
    "colab": {
      "name": "Bank_marketing_Strategy .ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "mount_file_id": "1BrZJaZWfQ6k_RUDXyK3tEaRBavhSg5r_",
      "authorship_tag": "ABX9TyP95WmXlOrSNZY14k28m1dT"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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    "accelerator": "GPU"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Y9eJv789s5EL"
      },
      "source": [
        "The [data](https://www.kaggle.com/henriqueyamahata/bank-marketing) is related with direct marketing campaigns of a Portuguese banking institution. \n",
        "   The marketing campaigns were based on phone calls. Often, more than one contact to the same client was required, \n",
        "   in order to access if the product (bank term deposit) would be (or not) subscribed. \n",
        "\n",
        "> Number of Instances: 45211\n",
        "\n",
        "> Number of Attributes: 16 + output attribute.\n",
        "\n",
        "\n",
        "The classification goal is to predict if the client will subscribe a term deposit (variable y).\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ItA5fU1zuoRj"
      },
      "source": [
        "# Attribute information:\n",
        "   Input variables:\n",
        "  \n",
        "   ## bank client data:\n",
        "   \n",
        "   1 - age (numeric)\n",
        "  \n",
        "   2 - job : type of job (categorical: \"admin.\",\"unknown\",\"unemployed\",\"management\",\"housemaid\",\"entrepreneur\",\"student\",\n",
        "                                       \"blue-collar\",\"self-employed\",\"retired\",\"technician\",\"services\") \n",
        "   \n",
        "   3 - marital : marital status (categorical: \"married\",\"divorced\",\"single\"; note: \"divorced\" means divorced or widowed)\n",
        "  \n",
        "   4 - education (categorical: \"unknown\",\"secondary\",\"primary\",\"tertiary\")\n",
        "   \n",
        "   5 - default: has credit in default? (binary: \"yes\",\"no\")\n",
        "  \n",
        "   6 - balance: average yearly balance, in euros (numeric) \n",
        "  \n",
        "   7 - housing: has housing loan? (binary: \"yes\",\"no\")\n",
        "  \n",
        "   8 - loan: has personal loan? (binary: \"yes\",\"no\")\n",
        "  \n",
        "   ## related with the last contact of the current campaign:\n",
        "   \n",
        "   9 - contact: contact communication type (categorical: \"unknown\",\"telephone\",\"cellular\") \n",
        "  \n",
        "  10 - day: last contact day of the month (numeric)\n",
        "  \n",
        "  11 - month: last contact month of year (categorical: \"jan\", \"feb\", \"mar\", ..., \"nov\", \"dec\")\n",
        "  \n",
        "  12 - duration: last contact duration, in seconds (numeric)\n",
        "  \n",
        "   ## other attributes:\n",
        "  \n",
        "  13 - campaign: number of contacts performed during this campaign and for this client (numeric, includes last contact)\n",
        "  \n",
        "  14 - pdays: number of days that passed by after the client was last contacted from a previous campaign (numeric, -1 means client was not previously contacted)\n",
        "  \n",
        "  15 - previous: number of contacts performed before this campaign and for this client (numeric)\n",
        "\n",
        "  16 - poutcome: outcome of the previous marketing campaign (categorical: \"unknown\",\"other\",\"failure\",\"success\")\n",
        "\n",
        "# Output variable (desired target):\n",
        "\n",
        "  17 - y - has the client subscribed a term deposit? (binary: \"yes\",\"no\")"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b6N0UTV_oUaS"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline\n",
        "import seaborn as sns\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LoABQcECqE3m"
      },
      "source": [
        "path = '/content/drive/My Drive/Datasets/Bank Marketing Data Set/bank-full.csv'\n",
        "df  = pd.read_csv(path,sep=';')"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D6CWhbOoqGLf",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "c8305780-8513-4561-c3b9-8b4cd4d69874"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>age</th>\n",
              "      <th>job</th>\n",
              "      <th>marital</th>\n",
              "      <th>education</th>\n",
              "      <th>default</th>\n",
              "      <th>balance</th>\n",
              "      <th>housing</th>\n",
              "      <th>loan</th>\n",
              "      <th>contact</th>\n",
              "      <th>day</th>\n",
              "      <th>month</th>\n",
              "      <th>duration</th>\n",
              "      <th>campaign</th>\n",
              "      <th>pdays</th>\n",
              "      <th>previous</th>\n",
              "      <th>poutcome</th>\n",
              "      <th>y</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>58</td>\n",
              "      <td>management</td>\n",
              "      <td>married</td>\n",
              "      <td>tertiary</td>\n",
              "      <td>no</td>\n",
              "      <td>2143</td>\n",
              "      <td>yes</td>\n",
              "      <td>no</td>\n",
              "      <td>unknown</td>\n",
              "      <td>5</td>\n",
              "      <td>may</td>\n",
              "      <td>261</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>44</td>\n",
              "      <td>technician</td>\n",
              "      <td>single</td>\n",
              "      <td>secondary</td>\n",
              "      <td>no</td>\n",
              "      <td>29</td>\n",
              "      <td>yes</td>\n",
              "      <td>no</td>\n",
              "      <td>unknown</td>\n",
              "      <td>5</td>\n",
              "      <td>may</td>\n",
              "      <td>151</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>33</td>\n",
              "      <td>entrepreneur</td>\n",
              "      <td>married</td>\n",
              "      <td>secondary</td>\n",
              "      <td>no</td>\n",
              "      <td>2</td>\n",
              "      <td>yes</td>\n",
              "      <td>yes</td>\n",
              "      <td>unknown</td>\n",
              "      <td>5</td>\n",
              "      <td>may</td>\n",
              "      <td>76</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>47</td>\n",
              "      <td>blue-collar</td>\n",
              "      <td>married</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "      <td>1506</td>\n",
              "      <td>yes</td>\n",
              "      <td>no</td>\n",
              "      <td>unknown</td>\n",
              "      <td>5</td>\n",
              "      <td>may</td>\n",
              "      <td>92</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>33</td>\n",
              "      <td>unknown</td>\n",
              "      <td>single</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "      <td>1</td>\n",
              "      <td>no</td>\n",
              "      <td>no</td>\n",
              "      <td>unknown</td>\n",
              "      <td>5</td>\n",
              "      <td>may</td>\n",
              "      <td>198</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   age           job  marital  education  ... pdays  previous poutcome   y\n",
              "0   58    management  married   tertiary  ...    -1         0  unknown  no\n",
              "1   44    technician   single  secondary  ...    -1         0  unknown  no\n",
              "2   33  entrepreneur  married  secondary  ...    -1         0  unknown  no\n",
              "3   47   blue-collar  married    unknown  ...    -1         0  unknown  no\n",
              "4   33       unknown   single    unknown  ...    -1         0  unknown  no\n",
              "\n",
              "[5 rows x 17 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6OKUS2nSqGI3",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c0f19ce9-b1e0-4921-f3dc-170dbd5eb9b2"
      },
      "source": [
        "df.info()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 45211 entries, 0 to 45210\n",
            "Data columns (total 17 columns):\n",
            " #   Column     Non-Null Count  Dtype \n",
            "---  ------     --------------  ----- \n",
            " 0   age        45211 non-null  int64 \n",
            " 1   job        45211 non-null  object\n",
            " 2   marital    45211 non-null  object\n",
            " 3   education  45211 non-null  object\n",
            " 4   default    45211 non-null  object\n",
            " 5   balance    45211 non-null  int64 \n",
            " 6   housing    45211 non-null  object\n",
            " 7   loan       45211 non-null  object\n",
            " 8   contact    45211 non-null  object\n",
            " 9   day        45211 non-null  int64 \n",
            " 10  month      45211 non-null  object\n",
            " 11  duration   45211 non-null  int64 \n",
            " 12  campaign   45211 non-null  int64 \n",
            " 13  pdays      45211 non-null  int64 \n",
            " 14  previous   45211 non-null  int64 \n",
            " 15  poutcome   45211 non-null  object\n",
            " 16  y          45211 non-null  object\n",
            "dtypes: int64(7), object(10)\n",
            "memory usage: 5.9+ MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1qaNOG0qsCvo",
        "outputId": "bcf65967-662e-4dd2-b8df-ac6eae0c8d6b"
      },
      "source": [
        "df.y.value_counts()"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "no     39922\n",
              "yes     5289\n",
              "Name: y, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Nm7UnQ9eYe6C"
      },
      "source": [
        "#EDA "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "uYxo-LJndkzt",
        "outputId": "4225bedc-4300-4ca8-a201-a56ca64881d9"
      },
      "source": [
        "int_column = df.dtypes[df.dtypes == 'int64'].index\n",
        "\n",
        "for column in int_column:\n",
        "  plt.figure(figsize=(16,4))\n",
        "\n",
        "  plt.subplot(1,3,1)\n",
        "  sns.distplot(df[column])\n",
        "  plt.xlabel(column)\n",
        "  plt.ylabel('Density')\n",
        "  plt.title(f'{column}  Distribution')\n",
        "\n",
        "  plt.subplot(1,3,2)\n",
        "  sns.boxplot(x='y', y=column, data =df, showmeans=True )\n",
        "  plt.xlabel('Target')\n",
        "  plt.ylabel(column)\n",
        "  plt.title(f'{column}  Distribution')\n",
        "\n",
        "  plt.subplot(1,3,3)\n",
        "  counts, bins = np.histogram(df[column], bins=20, normed=True)\n",
        "  cdf = np.cumsum (counts)\n",
        "  plt.plot (bins[1:], cdf/cdf[-1])\n",
        "  #plt.xticks(range(15,100,5))\n",
        "  plt.yticks(np.arange(0,1.1,.1))\n",
        "  plt.title(f'{column}  cdf')\n",
        "  plt.show()\n",
        "  print()\n"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x288 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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WA62trVx55ZVZh2Fmderzdz7CI9t28OV3vNqrSZtNMR4ynYEhQ6a9sJaZmZnZlPWrJ5/l83e1s/SVL+Ck331e1uGY2V5yQpyB8mnDnkJsZmZmNjUNDAQXfeMBZk1v5ONnLMw6HDPbB06IMxDDhkybmZmZ2dTz1Xsf48ePdnLx6Qs55IDpWYdjZvvACXEGhlSInRCbmZmZTTm/2b6TT93+S35/wSG85bjDsg7HzPaRE+IMDETQkC4s3e85xGZmZpYzktokPSypXdJFFY4fKek7ku6XdJekeVnEOZKI4OPffJC+gQGu+OOXIXnHELOpyglxBgYGgsaGhsHHZmZmZnkhqQBcA5wKLATOljR8Au4/Aysj4uXAZcA/1jbK0a158Dese+hJ3r/4GI5snZV1OGa2H5wQZyCAQloidoXYzMzMcuYEoD0iNkZED3AjsHTYOQuB76aP76xwPDPbu3u5ZNUGFh56EO/8/aOyDsfM9pMT4gxEQGMhTYhdITYzM7N8OQzYXNbekvaV+znwJ+njPwYOlNQ6/EKSzpW0XtL6bdu2VSXY4T55+y/peG4Xn3rLy2ks+KO02VTnv8UZGIigqVAaMp1xMGZmZmaTz4eAN0j6KfAGYCvQP/ykiLguIhZFxKK5c+dWPah7Nnbw9Xsf469ffxTHzptd9dczs+przDqAPBqIoDEdMj3gIdNmZmaWL1uBw8va89K+QRHxOGmFWNIBwFsioqtmEVaws7efj/7nA8yb08yFJx+TZShmNoFcIc7AQDBYIfYcYjMzM8uZ+4CjJR0laRpwFrCq/ARJh0gqfU79KHBDjWPcw+fvbGfjth1c8cfHMnOaa0pm9cIJcQYiYnAOsVeZNjMzszyJiD7gPGAt8Avg5ojYIOkySWemp50EPCzpf4HnA1dkEmzqie3dXPu9R/ijV76ANxxT/aHZZlY7/norAwPB4JBpV4jNzMwsbyJiNbB6WN8lZY9vAW6pdVwjeeSpHfT2B2efcETWoZjZBHOFOAPJHOJ0yLQrxGZmZmaTWmexB4CDZ03LOBIzm2hOiGssIoZsu+RVps3MzMwmt67uXgBmz2zKOBIzm2hOiGusNEK60YtqmZmZmU0JXTuSCnFLsyvEZvXGCXGNlbZZairNIfaQaTMzM7NJrau7l1nTCkxr9Edns3pT1b/VktokPSypXdJFFY5Pl3RTevweSfPLjn007X9Y0il7cc0rJT1Xrfe0v0rpbyFNiMMVYjMzM7NJrbPYQ8tMV4fN6lHVEmJJBeAa4FRgIXC2pIXDTjsH6IyIBcBngU+lz11IsifdS4E24POSCmNdU9IiYE613tNEGKwQF7yolpmZmdlU0FXspcXzh83qUjUrxCcA7RGxMSJ6gBuBpcPOWQqsSB/fArxJktL+GyNiV0T8GmhPrzfiNdNk+Z+Aj1TxPe233XOIve2SmZmZ2VTQVexhjivEZnWpmgnxYcDmsvaWtK/iOekm7duB1lGeO9o1zwNWRcQTowUl6VxJ6yWt37Zt2169oYlQqhCX9iH2KtNmZmZmk5srxGb1qy5WBpD0AuDPgKvGOjcirouIRRGxaO7cudUPbpjSCOnBfYhdITYzM6uZ9vZ2Tj/9dNrb27MOxaaQrm4nxGb1qpoJ8Vbg8LL2vLSv4jmSGoHZQMcozx2p/1XAAqBd0iZgpqRJ+S/dYIV4cB9iJ8RmZma1cvnll7Njxw4uv/zyrEOxKWJgIDxk2qyOVTMhvg84WtJRkqaRLJK1atg5q4Dl6eM/Bb4bybLLq4Cz0lWojwKOBu4d6ZoRcVtE/E5EzI+I+UAxXahr0ol0iLQX1TIzM6ut9vZ2Nm3aBMCmTZtcJbZxeXZXHwMBs5tdITarR1VLiNM5wecBa4FfADdHxAZJl0k6Mz3teqA1reZeCFyUPncDcDPwELAGeG9E9I90zWq9h2oYPofYQ6bN6oukD0jaIOlBSV+XNCP9Eu+edLu4m9Iv9Kqy9ZyZjWx4VdhV4uyMYxvNIyTdKemnku6XdFoWcUKyoBbgCrFZnWqs5sUjYjWweljfJWWPd5LM/a303CuAK8ZzzQrnHLAv8dbC7iHTyXcR3ofYrH5IOgy4AFgYEd2SbiYZyXIa8NmIuFHSv5JsOXctZVvPSTqLZOu5tw3beu4FwB2Sjklf5hpgCcmigvdJWhURD9XwbZpNWaXq8Ehtq42ybTRHu5ddTFL4uDa9J64G5tc8WKCz2AvAnFmuEJvVo7pYVGsqKY2Qbiptu+RVps3qTSPQnK6LMBN4AvhDkq3lINlq7o/SxxO29ZyZjW3+/Pmjtq1mxnMvC+Cg9PFs4PEaxjdEqUI8u9kVYrN65IS4xkoV4YKHTJvVnYjYCvwz8BhJIrwd+DHQlU75gKHbxU3k1nNDZL3FnNlkdPHFF4/atpoZz73sE8BfStpCUh0+v9KFanGv6ypViL3KtFldckJcY7u3XfIq02b1RtIckirHUSRDnWcBbVnEkvUWc2aT0YIFCwarwvPnz2fBgkm5/qYlzga+HBHzSKadfEXSHp9ba3GvK1WIWzyH2KwuOSGusWDoHGKvMm1WVxYDv46IbRHRC3wDeD3Qkg6hhqFb0E3U1nNmNk4XX3wxs2bNcnU4W+O5l51DssAqEfEjYAZwSE2iG6Y0h9irTJvVJyfENTY4h9hDps3q0WPAayXNTOcCv4lktfw7SbaWg2SruW+mjydk67kavC+zurFgwQJuu+02V4ezNZ572WMk91AkvYQkIc5k/kdXsYeDZjQOTnczs/pS1VWmbU+lIdKlCrGHTJvVj4i4R9ItwE+APuCnwHXAbcCNki5P+65Pn3I9yTDAduBpkg+FpFvUlbae6yPdeg5AUmnruQJww1Tbes7MLCL6Kt3LJF0GrI+IVcAHgS9I+gDJAltvj4y25ujq7mXOLA+XNqtXTohrrHQrbyy4QmxWjyLiUuDSYd0bSVZVHX5uVbaeMzOb7MaxNedDJFNOMtdZ7PX8YbM65iHTNVbah7ipIa0QOx82MzMzm7S2F3to8fxhs7rlhLjGSglxqULsIdNmZmZmk1dnsddbLpnVMSfENTZ82yWvMm1mZmY2eXUVezxk2qyOOSGusYhhi2p5DrGZmZnZpNTXP8AzO/tocYXYrG45Ia4xV4jNzMzMpobt3ckexJ5DbFa/nBDX2OCiWmmF2KtMm5mZmU1OXWlC7G2XzOqXE+IaKyXEpc3dvaiWmVn1dXR0cMEFF9DR0ZF1KGY2hXQVewA8h9isjjkhrrFSQbiptA/xQIbBmJnlxIoVK3jggQdYuXJl1qGY2RTSVfSQabN654S4xkoJcaHBi2qZmdVCR0cHa9asISJYs2aNq8RmNm6daUI8xxVis7rlhLjGdg+ZhgY5ITYzq7YVK1YwMJAMx+nv73eV2MzGrTRkerZXmTarW06Ia6yUAEuiQfIq02ZmVXbHHXfQ19cHQF9fH+vWrcs4IjOT1CbpYUntki6qcPyzkn6W/vyvpK4s4uwq9lJoEAfNaMzi5c2sBpwQ11gp/22QaGiQV5k2M6uyxYsX09iYfJhtbGxkyZIlGUdklm+SCsA1wKnAQuBsSQvLz4mID0TEKyPilcBVwDdqHyl0FntoaW5CUhYvb2Y14IS4xiJNgBsEBcmrTJuZVdny5ctpSNdtKBQKLFu2LOOIzHLvBKA9IjZGRA9wI7B0lPPPBr5ek8iG6eru9XBpszrnhLjGyivEhQZ5lWkzsyprbW2lra0NSbS1tdHa2pp1SGZ5dxiwuay9Je3bg6QjgaOA79Ygrj10FXu8oJZZnXNCXGO75xB7US0zs1o58cQTkcSJJ56YdShmtnfOAm6JiP5KByWdK2m9pPXbtm2b8BfvKvZ6yyWzOueEuMYGBodMlyrETojNzKrt6quvZmBggKuuuirrUMwMtgKHl7XnpX2VnMUow6Uj4rqIWBQRi+bOnTuBISa6ir20uEJsVtecENdYDBsy7QqxmVl1tbe3s2nTJgA2bdpEe3t7tgGZ2X3A0ZKOkjSNJOldNfwkSS8G5gA/qnF8gzqLPbR4DrFZXXNCXGNDh0w7ITYzq7bLL7981LaZ1VZE9AHnAWuBXwA3R8QGSZdJOrPs1LOAGyOy+bC0q6+fYk8/c5wQm9U1b6pWY7srxHgfYjOzGihVh0dqm1ntRcRqYPWwvkuGtT9Ry5iG217sBfCQabM65wpxje2uEHuVaTOzWpg/f/6obTOzSrq6SwmxK8Rm9cwJcY2VzyFuaPAq02Zm1XbeeecNaZ9//vkZRWJmU0nnjh4Ab7tkVuecENfY7lWmoeAh02ZmVff9739/1LaZWSWd6ZDp2d52yayuOSGusYEhFWLR7wqxmVlV3XHHHUPa69atyygSM5tKtnenFeJZrhCb1TMnxDVWvsp0QWLAFWIzs6pavHgxjY3JGpKNjY0sWbIk44jMbCooVYhbXCE2q2tOiGssBodMex9iM7NaWL58OQ0NyT93hUKBZcuWZRyRmU0FXcVephUamDmtkHUoZlZFTohrrHzItORVps3Mqq21tZW2tjYk0dbWRmtra9YhmdkU0FXsoWVmE5KyDsXMqsgJcY0NWVTLq0ybmdXEmWeeycyZM3nzm9+cdShmNkV0FXu95ZJZDlQ1IZbUJulhSe2SLqpwfLqkm9Lj90iaX3bso2n/w5JOGeuakq6X9HNJ90u6RdIB1Xxv+6pUIZbkVabN6pCklvQe9EtJv5D0e5IOlrRO0q/SP+ek50rSlen97H5Jx5VdZ3l6/q8kLS/rP17SA+lzrpRLF+OyatUqisUit956a9ahmNkU0VnsocVbLpnVvaolxJIKwDXAqcBC4GxJC4eddg7QGRELgM8Cn0qfuxA4C3gp0AZ8XlJhjGt+ICJeEREvBx4Dhm48OUlE2aJaDZ5DbFaPPgesiYgXA68AfgFcBHwnIo4GvpO2IbmXHZ3+nAtcCyDpYOBS4DXACcClpSQ6PeddZc9rq8F7mtI6Ojq4/fbbiQhWr15NR0dH1iGZ2RTQVez1glpmOVDNCvEJQHtEbIyIHuBGYOmwc5YCK9LHtwBvSqsdS4EbI2JXRPwaaE+vN+I1I+IZSCouQDMwKTPNKJtD7AqxWX2RNBs4EbgeICJ6IqKLofe6FcAfpY+XAisjcTfQIulQ4BRgXUQ8HRGdwDqgLT12UETcHcm3ayvLrmUjWLFiBb29yWqxvb29rFy5MuOIzGwq6OruYY4rxGZ1r5oJ8WHA5rL2lrSv4jkR0QdsB1pHee6o15T0JeA3wIuBqybiTUy08jnEDQ1OiM3qzFHANuBLkn4q6YuSZgHPj4gn0nN+Azw/fby397rD0sfD+/cg6VxJ6yWt37Zt236+rant29/+9pD22rVrM4rEzErGmlaXnvNWSQ9J2iDpa7WMLyLoLPbSMssVYrN6V1eLakXEO4AXkAxRfFulc7L+kDgwrELsEdNmdaUROA64NiJeBexg9/BoANLKbtX/5kfEdRGxKCIWzZ07t9ovN6mV9iAeqW1mtTWeaXWSjgY+Crw+Il4KvL+WMe7sHaCnb4CWZleIzepdNRPircDhZe15aV/FcyQ1ArOBjlGeO+Y1I6KfZCj1WyoFlfWHxIGyOcSFBtHvjNisnmwBtkTEPWn7FpIE+cl0uDPpn0+lx/f2Xrc1fTy830bx3HPPjdo2s5obz7S6dwHXpNNGiIinqKHOYg8Ac7zKtFndq2ZCfB9wtKSjJE0jWSRr1bBzVgGl1VP/FPhuWj1ZBZyVrkJ9FMnCMfeOdM10pdYFMDiH+Ezgl1V8b/ssBodMCwkPmTarIxHxG2CzpN9Nu94EPMTQe91y4Jvp41XAsvQe9lpgezq0ei1wsqQ56WJaJwNr02PPSHpteq9bVnYtG8EBBxwwatvMam480+qOAY6R9D+S7pZUcQHBao38KyXE3nbJrP5VbdxYRPRJOo/kg10BuCEiNki6DFgfEatIFp75iqR24GmSBJf0vJtJPkj2Ae9NK7+McM0GYIWkgwABPwfeU633tj+GDJn2KtNm9eh84Kvpl3YbgXeQfPl4s6RzgEeBt6bnrgZOI1k4sJieS0Q8LekfSL4EBLgsIp5OH/8t8GWSxQNvT39sFKUFtUZqm9mk1EhSEDmJZDTM9yUdmy5UOG9jD4sAACAASURBVCgirgOuA1i0aNGEfajaXkzuE952yaz+VXUiVUSsJvnAV953SdnjncCfjfDcK4ArxnnNAeD1ExBy1ZUvquVVps3qT0T8DFhU4dCbKpwbwHtHuM4NwA0V+tcDL9vPMHPl0EMPZdOmTUPaZpap8Uyr2wLcExG9wK8l/S9JgnwfNdA5mBC7QmxW7+pqUa2poJT/SvIq02ZmNfDkk0+O2jazmhvPtLr/IqkOI+kQkiHUG2sVYFd3aQ6xK8Rm9W5cCbGkb0g6PR2abPshhlWIPWTaLFtPPvkk55xzDqeeemqpa0Y6tNnqxJIlS0imXCdfRp588skZR2SWb+lWm6UpcL8Abi5Nq5N0ZnraWqBD0kPAncCHI6KjVjF2pRXi2c2uEJvVu/EmuJ8H/hz4laRPli0YY3vha/c8xr2/TqYB/udPtrKlq9sVYrOMvf3tb+eUU07h8ccfL3XtpMbbe1h1LV++fHCrpaamJpYtW5ZxRGYWEasj4piIeFE6TY6IuCRdY4ZIXBgRCyPi2Ii4sZbxdRV7aG4qMKOpUMuXNbMMjCshjog7IuIvSLYP2QTcIemHkt4hyV+d7YXBgrCSKrELxGbZ+u1vf8tb3/pWGhqG3A77s4rHJl5rayuve93rAHjd615Ha2trxhFZltrb2zn99NNpb2/POhSbxDqLvd5yySwnxj0EWlIr8HbgncBPgc+RJMjrqhJZndqdDwuB9yE2y9isWbPo6OgYHFILzAK2ZxiSVcHGjcnUw0ceeSTjSCxrl19+OTt27ODyyy/POhSbxLqKPcz2/GGzXBjvHOL/BP4bmAm8OSLOjIibIuJ8wBs67o00AZaSrZc8ZNosW5/5zGc488wzeeSRR3j9618PcBTJ1klWJ9rb29m8OdnydPPmza4M5lh7e/vgiuObNm3y/ws2oi5XiM1yY7wV4i+kczj+MSKeAJA0HSAiKm0vYiMYrBArWdxlwAmxWaaOO+44vve97/HDH/6Qf/u3fwPYEBH3Zx2XTZzhlUBXBvPL/y/YeHUWe7zlkllOjDchrvQvxo8mMpC8KI2QFqJBHjJtlrVrrrmG5557jpe+9KW87GUvA2iQ9LdZx2UTp3wP4kptyw//v2Djtb27lxYPmTbLhVETYkm/I+l4oFnSqyQdl/6cRDJ82vZSlA2ZlkT/QMYBmeXcF77wBVpaWsq7+oF3ZRSOVcEBBxwwatvyY/78+aO2zSD5rOYh02b50TjG8VNIFtKaB3ymrP9Z4GNViqmulQ+ZbhDeh9gsY/39/URE+aJaAC4L1JG+vr5R25YfF198Me985zuHtM2Ge25XH30DQUuz/ykwy4NRE+KIWAGskPSWiPiPGsVU1wbKhkzLi2qZZa6trY23ve1t/M3f/E2p64XAlzIMySbYySefzKpVqwbbp5xySobRWJYWLFjA/Pnz2bRpE/Pnz2fBggVZh2STUFexF8BziM1yYqwh03+ZPpwv6cLhPzWIr+4E5atMu0JslrVPfepTvPGNb+Taa6/l2muvBXgG+EjGYdkEWr58OU1NyQfbpqYmli1blnFElqWLL76YWbNmuTpsI+os9gB4DrFZTow1ZHpW+qcnXE2Q3YtqJT9eZdosWw0NDbznPe/hPe95DwCSfhsR/RmHZROotbWVU089lVtvvZXTTjuN1tbWrEOyDC1YsIDbbrst6zBsEitViD2H2Cwfxhoy/W/pn39fm3DqX0SaDEvJPsSuEJtl6n/+53/4xCc+waOPPlqaW3qspI0R8cKsY7OJs3z5cjZt2uTqsJmNyRVis3wZ17ZLkj4t6SBJTZK+I2lb2XBq2wvB7gQ42Yc4w2DMjHPOOYcLL7yQH/zgB9x3330ADwGvzjgsm2Ctra1ceeWVrg6bTRKS2iQ9LKld0kUVjr89/bz5s/TnnZWuUw3buz2H2CxPxrsP8ckR8QxwBrAJWAB8uFpB1bOIZP4w4H2IzSaB2bNnc+qpp/K85z2vlCz1R0RH1nHZxOro6OCCCy6go8P/ac2yJqkAXAOcCiwEzpa0sMKpN0XEK9OfL9Yqvs4daULc7ITYLA/GmxCXhlafDvx7RGyvUjy5UNrexatMm2XvjW98Ix/+8If50Y9+xE9+8hOAmZKOyzoum1grVqzggQceYOXKlVmHYhnzlyOTwglAe0RsjIge4EZgacYxDeos9nDg9EYaC+P9mGxmU9l4/6Z/S9IvgeOB70iaC+ysXlj1KyIo7XbakD7wwlpm2bnnnntYv349H/vYx/jgBz8Iyb7r/5xxWDaBOjo6WLNmDRHB7bff7kQo5/zlyKRwGLC5rL0l7RvuLZLul3SLpMMrXUjSuZLWS1q/bdu2CQlue3cvLbNcHTbLi3ElxBFxEfA6YFFE9AI7mETf5E0l5UOmS5ViD5s2y86dd9455Af434j4w6zjsomzYsUKenqSRXJ6enqcCOVY+Zcja9as8Zcjk9utwPyIeDmwDlhR6aSIuC4iFkXEorlz507IC3cWe2hp9oJaZnmxN2NBXgy8TdIy4E+Bk6sTUn0LdifCgxViJ8Rmmbrtttv49Kc/zWWXXQZwqKRLso7JJs66deuGtL/97W9nFIllbcWKFQykq1n29/f7y5HsbAXKK77z0r5BEdEREbvS5hdJRinWRFex1wtqmeXIeFeZ/grJEMLfJ1l99dXAoirGVbfKh0yXEmOvNG2WnXe/+93cdNNNXHXVVUTy5dQc4MiMw7IJ1NLSMmrb8uOOO+4oba9GX1/fHl+WWM3cBxwt6ShJ04CzgFXlJ0g6tKx5JvCLWgXXVexhjrdcMsuN8VaIFwGvj4i/jYjz058LqhlYvRpg6CrT4CHTZln64Q9/yMqVK5kzZw6XXnopwC+BYzIOyybQE088MWrb8mPx4sU0NibrhDY2NrJkyZKMI8qniOgDzgPWkiS6N0fEBkmXSTozPe0CSRsk/Ry4AHh7reLr6naF2CxPGsc+BYAHgd8B/CliP0WA2L3KNOCVps0y1NzcDMDMmTN5/PHHIZnZcOhozzGzqWn58uWsWbMGgEKhwLJlyzKOKL8iYjWweljfJWWPPwp8tNZx9Q9EsqiWK8RmuTHeCvEhwEOS1kpaVfqpZmD1KiL2qBB7lWmz7Jxxxhl0dXXx4Q9/mOOOOw7gWODrGYdlE2jWrFmjti0/WltbaWtrQxJtbW2lvcfNBj3T3UuE9yA2y5PxVog/Uc0g8qR8US2vMm2WvY9//OMAvOUtb+GMM85gxowZGyLi4xmHZROot7d31Lbly/Lly9m0aZOrw1ZRV3dyf5jjbZfMcmNcCXFEfE/SkcDREXGHpJlAobqh1aeI3WV5V4jNsvONb3xjpEMHSvqTiBjxBJtampqaBrddKrUtv1pbW7nyyiuzDsMmqc5icq/wtktm+TGuhFjSu4BzgYOBF5Fsnv6vwJuqF1p9imQSMQCFtELc64TYrOZuvfXWkQ61AGcATojrxI4dO0Ztm5mVbC8mFWIvqmWWH+MdMv1e4ATgHoCI+JWk51UtqjpX2napkJaIe/u875JZrX3pS1+q2P/lL395U0T89f5cW1IBWA9sjYgzJB0F3Ai0Aj8G/ioieiRNB1aS7K/ZAbwtIjal1/gocA7QD1wQEWvT/jbgcySjdL4YEZ/cn1jNzGy3UoXY2y6Z5cd4E+Jd6Yc3ACQ1kkyHtb0UsXvucCkh7ul3QmyWpdtuu40NGzawc+dOgEMlXRIRl+3HJd9HspXIQWn7U8BnI+JGSf9Kkuhem/7ZGRELJJ2Vnvc2SQtJ9uV8KfAC4A5Jpa2grgGWAFuA+yStioiH9iPWulcoFOjv7x/SNjOrpNMVYrPcGe8q09+T9DGgWdIS4N+BEccb2siC3atMNzYkv/4eV4jNMvPud7+bm266iauuuiqZ0gBzgCP39XqS5gGnA19M2wL+ELglPWUF8Efp46Vpm/T4m9LzlwI3RsSuiPg10E4ySucEoD0iNkZED0nVeem+xpoXJ5xwwqhtM7OS7cUeJDhohhNis7wYb0J8EbANeAD4G5J94y6uVlD1rGwKMY2F5NEuJ8RmmfnhD3/IypUrmTNnDpdeeinAL4FjxnjaaP4F+AhQ+ovdCnRFRF/a3kKyDgPpn5sB0uPb0/MH+4c9Z6T+PUg6V9J6Seu3bdu2H29n6tuyZcuobTOzks5iL7Obm2gorXxqZnVvvKtMD0j6L+C/IiLfn6z2U/m2S4NziD1k2iwzzc3NAMycOZPHH38ckr+mh+7LtSSdATwVET+WdNJExbgvIuI64DqARYsW5XqKy+bNm0dtm5mVdHX3ev6wWc6MWiFW4hOSfgs8DDwsaZukS2oTXv0ZiNhdIS7NIXaF2CwzZ5xxBl1dXXzkIx/h+OOPBzgW+Po+Xu71wJmSNpEMZ/5DkgWwWtK1FwDmAVvTx1uBw2FwbYbZJItrDfYPe85I/TaK0pceI7UtXzo6Orjgggvo6OjIOhSbhLqKPZ4/bJYzYw2Z/gDJB7xXR8TBEXEw8Brg9ZI+UPXo6lDFRbWcEJtl5kMf+hA33HADX/nKV/i93/s9gN8AV+zLtSLioxExLyLmkyyK9d2I+AvgTuBP09OWA99MH69K26THvxvJROZVwFmSpqcrVB8N3AvcBxwt6ShJ09LXWLUvseZJd3f3qG3LlxUrVvDAAw+wcuXKrEOxSair2EtLsxNiszwZKyH+K+DsdFEXACJiI/CXwLJqBlavkiHTyePBRbU8ZNosM8uXL2fDhg1ccMEFnH/++QDNJFshTaS/Ay6U1E4yR/j6tP96oDXtv5BkvQYiYgNwM/AQsAZ4b0T0p/OMzwPWkqxifXN6rpmNQ0dHB2vWrCEiWLNmjavEGZLUJulhSe2SLhrlvLdICkmLahFXZ7HHQ6bNcmasOcRNEfHb4Z0RsU3SmF+fjbVf5kTuwSnpq8AioJekkvI3EdE7Voy1FhWGTHsOsVl2HnzwQR56aMiuRY8CL9vf60bEXcBd6eONJCtEDz9nJ/BnIzz/CipUqiNiNcnChma2l1asWMHAQPJvbn9/PytXruQDH/CAt1pL92ofcws5SQeSbGN3T61i6yr2MttDps1yZawKcc8+Hiu/2Z0KLATOTvfWLDe4ByfwWZI9OBm2B2cb8HlJhTGu+VXgxSTz/5qBd47x3jIRAQ3Dhkx7lWmz7Bx33HHcfffd5V2zgPUZhWNmVXTHHXfQ15cs+N7X18e6desyjii3xruF3D+QfDbcWYugevsHeG5XnyvEZjkzVoX4FZKeqdAvYMYYzx282QFIKt3syr/9Wwp8In18C3D18D04gV+nwwlL1ZWK10yrJqT995IsNjPplC/1Wih4DrFZVo499lgk0dvby+te9zqOOOKI0vz+FzP0r6qZ1Yk/+IM/YO3atUPalolKW8i9pvwESccBh0fEbZI+PNKFJJ0LnAtwxBFH7FdQXcVkYKEX1TLLl1ET4ogo7Me1x7zZMWwPTknle3DePey5pb02x7qBNpHMfX5fpaAm8sa5TyLK5hA7ITbLyre+9a2K/fPnz38AeHNtozGzWkjWrLPJTlID8Bng7WOdO5FbzG3vTgY/trhCbJYrYw2Znoo+D3w/Iv670sGIuC4iFkXEorlz59Y4tMqLankOsVntHXnkkRV/gJ6IeDTr+GziFAqFUduWHz/4wQ+GtP/7vyt+VLDqG2sLuQNJ1nK4K93G7rXAqmovrNWZVojnuEJslivVTIjHs1/mhO7BKelSYC7Jaq2TUgQIb7tkZlYr/f39o7YtPxYvXjykvWTJkowiyb1Rt5CLiO0RcUhEzE+3sbsbODMiqrq+Q+eOtELc7AqxWZ5UMyEez36ZE7YHp6R3AqeQbBM1aTPMYPeQ6QYl1WJvu2RmVj2uEFvJmWeeOaT95jd7dkQWRtpCTtJlks4c/dnV09XtOcRmeTTWolr7LJ0TXLrZFYAbSjc7YH1ErCLZg/Mr6aJZT5MkuKTnlfbg7CPdgxOg0jXTl/xXku1SfpQujPONiLisWu9vXyUV4oQkphUaXCE2M6siV4itZNWqod/L33rrrd52KSOVtpCLiEtGOPekWsTUVSzNIXZCbJYnVUuIYeyb3UTuwRkRVX0vEyWC0kq2AExrbHCF2MzMrAaGb7P07W9/2wmxDeoq9tLYIA6YPiU+UprZBKnHRbUmtYGyIdMA0xtdITYzM6uF5z//+aO2Ld86i720zGwaUrgws/rnhLjGyhfVAmjykGkzM7OaePLJJ0dtW75t7+7xlktmOeSEuMaSIdO72x4ybWZWXc973vOGtF0VzK/hq0qffPLJGUVik1Hnjl5vuWSWQ06IayyGDZmeVmjwPsRmZlX03HPPDWk/++yzGUViWTvxxBNHbVu+dRZ7mO0tl8xyxwlxjZWvMg1phdhDps3MqqZYLI7atvy4+uqrh7SvuuqqjCKxyWh7tyvEZnnkhLjGImLIYg1NhQZ2OSE2MzOruk2bNo3atnzrLPZ4yyWzHHJCnAFXiM3MzGrv4IMPHtJubW3NKBKbbHb29rOzd8CLapnlkBPiGgvYY9slzyE2MzOrvqeffnpIu6OjI6NIbLLpKvYCMMcJsVnuOCGuseHbLk0reJVpMzMzsyx1FnsAPGTaLIecENdYMod4d9v7EJuZmVneSGqT9LCkdkkXVTj+bkkPSPqZpB9IWljNeEoVYifEZvnjhLjGkiHTZRVizyE2MzOriZe//OVD2q94xSsyiiTfJBWAa4BTgYXA2RUS3q9FxLER8Urg08BnqhlTV6lC7G2XzHLHCXGNVdp2qbc/MovHzMwsLy699NIh7UsuuSSjSHLvBKA9IjZGRA9wI7C0/ISIeKasOYukplA1Xd3pHOJZrhCb5U1j1gHkzcCwIdPTGr3tkpmZmeXKYcDmsvYW4DXDT5L0XuBCYBrwh9UMqNMVYrPccoW4xvYYMl1ooKevP7uAzMzMcuKqq64atW2TS0RcExEvAv4OuLjSOZLOlbRe0vpt27bt82ttL/YyvbGB5mmFfb6GmU1NTohrrNKQaa8ybWZmVn133XXXqG2rma3A4WXteWnfSG4E/qjSgYi4LiIWRcSiuXPn7nNAncUeb7lkllNOiGts+CrT0wqeQ2xmZma5ch9wtKSjJE0DzgJWlZ8g6eiy5unAr6oZUGex1ytMm+WU5xDXWLBnhbh/IOgfCAoNGulpZmZmZnUhIvoknQesBQrADRGxQdJlwPqIWAWcJ2kx0At0AsurGdN2J8RmueWEOAPDt10C6Okb8LwVMzMzy4WIWA2sHtZ3Sdnj99Uyns5iDy+ae0AtX9LMJgkPma6xiBhSIW4q7E6IzWxqk3S4pDslPSRpg6T3pf0HS1on6Vfpn3PSfkm6UlK7pPslHVd2reXp+b+StLys/3hJD6TPuVLl37CZmdk+6eru9ZZLZjnlhLjGIkaoEHthLbN60Ad8MCIWAq8F3itpIXAR8J2IOBr4TtoGOBU4Ov05F7gWkgQauJRkG5ITgEtLSXR6zrvKntdWg/dlVhdmzJgxatvyKSLoKvYw21sumeWSE+IaS7Zd2t2eXnBCbFYvIuKJiPhJ+vhZ4Bck+20uBVakp61g92qpS4GVkbgbaJF0KHAKsC4ino6ITmAd0JYeOygi7o6IAFYywsqrZrannTt3jtq2fCr29NPbH8zxHGKzXHJCXGPDh0yXzyE2s/ohaT7wKuAe4PkR8UR66DfA89PHhwGby562Je0brX9LhX4zM9tHncUeAG+7ZJZTTohrbPiQac8hNqs/kg4A/gN4f0Q8U34srexWfa81SedKWi9p/bZt26r9cmZmU1ZXsReA2a4Qm+WSE+IaG2DokOlShbjXQ6bN6oKkJpJk+KsR8Y20+8l0uDPpn0+l/VuBw8uePi/tG61/XoX+PUTEdRGxKCIWzZ07d//elJlZHSslxK4Qm+WTE+IaG2nI9C5XiM2mvHTF5+uBX0TEZ8oOrWL3HprLgW+W9S9LV5t+LbA9HVq9FjhZ0px0Ma2TgbXpsWckvTZ9rWVl1zIzs31QGjLtfYjN8sn7ENfYHqtMe8i0WT15PfBXwAOSfpb2fQz4JHCzpHOAR4G3psdWA6cB7UAReAdARDwt6R+A+9LzLouIp9PHfwt8GWgGbk9/zMxsH3V1JxViJ8Rm+eSEuMaCGDZkOml4lWmzqS8ifgCMtC/wmyqcH8B7R7jWDcANFfrXAy/bjzDNzKxM1460Quxtl8xyyUOmayxi6Kfl6Y0FAHb19mcTkJmZWU685CUvGbVt+dRZ7GXWtMLgNDYzyxf/zc9AeUJ84IykSP/crr5sgjEzM8uJtra2Ie3TTjsto0hsMunq7qHFC2qZ5ZYT4hobPof4wBnJfJVn0vkrZmZmVh3/8i//MqT9mc98ZoQzrdoktUl6WFK7pIsqHL9Q0kOS7pf0HUlHViuWrmKv5w+b5ZgT4hobPoe4VCF+dqcrxGZmZtWUTNsfuW21IakAXAOcCiwEzpa0cNhpPwUWRcTLgVuAT1crnq5ij7dcMssxJ8Q1lswh3p0RNxUaaG4q8MxOV4jNzMwsF04A2iNiY0T0ADcCS8tPiIg7I6KYNu9m6B7sE6qr2MtsV4jNcssJcY0lQ6Z3t792z2M0FsRPH+via/c8ll1gZmZmZrVxGLC5rL0l7RvJOYywxZykcyWtl7R+27Zt+xRMV3cvc5wQm+WWE+IaGz5kGmBGU4GdXmXazMzMbAhJfwksAv6p0vGIuC4iFkXEorlz5+719QcGwkOmzXLO+xDX2PAh0wAzGhvY2ed9iM3MzCwXtgKHl7XnpX1DSFoM/B/gDRGxqxqBPLuzj4GA2c2uEJvlVVUrxONYQXC6pJvS4/dIml927KNp/8OSThnrmpLOS/tC0iHVfF/7aiCCgD0qxM3TXCE2MzOz3LgPOFrSUZKmAWcBq8pPkPQq4N+AMyPiqWoF0tXdA+AKsVmOVS0hHucKgucAnRGxAPgs8Kn0uQtJbo4vBdqAz0sqjHHN/wEWA49W6z3tr/6BZDXLpoahGfH0RifEZmZmlg8R0QecB6wFfgHcHBEbJF0m6cz0tH8CDgD+XdLPJK0a4XL7pbOYLGrqbZfM8quaQ6YHVxAEkFRaQfChsnOWAp9IH98CXK1kk96lwI3p8JhfS2pPr8dI14yIn6Z9VXxL+6evP0mIC4Wh30PMaCrQ3esh02ZmZpYPEbEaWD2s75Kyx4trEUdXMakQt7hCbJZb1RwyPZ4VBAfPSb8t3A60jvLcvV2VcA8TsRrhvuobSJLexmEV4uamBna5QmxmZmZWU12uEJvlXu5Wmd7f1Qj3R2nI9PCEeEZTgb6BoLffVWIzMzOzWukseg6xWd5VMyEezwqCg+dIagRmAx2jPHdcqxJOVqUh042FPRNiwPOIzczMzGqoVCH2KtNm+VXNhHjMFQTT9vL08Z8C342ISPvPSlehPgo4Grh3nNectPrSCnGhYfgc4qS9y/OIzczMzGqmq9jDQTMaKTRM3jVozKy6qpYQj3MFweuB1nTRrAuBi9LnbgBuJlmAaw3w3ojoH+maAJIukLSFpGp8v6QvVuu97avSHOLhq0yXKsTdrhCbmZmZ1UxXdy9zZnm4tFmeVXOV6fGsILgT+LMRnnsFcMV4rpn2XwlcuZ8hV9XuVaaHJcSN6ZDpPifEZmZmZrXSWeylxcOlzXItd4tqZalvcFGtPbddAtjpIdNmZmZmNbO92OMtl8xyzglxDY207VJpDrEX1TIzMzOrnc5iL3O85ZJZrjkhriGvMm1mZmY2eXS6QmyWe1WdQ2xD9Y8wZHpaYwMNgh27nBCbmVk+XXXVVbS3t9f8dd/3vvdV7doLFizg/PPPr9r1bf/09Q/w7M4+WlwhNss1V4hraKQh0w0Ss5ub6OruySIsMzMzs9zZ3p3sQexFtczyzRXiGhrch7iw5153LTOnDW4Ob2Zmlje1qKSedNJJe/R97nOfq/rr2p4ktQGfAwrAFyPik8OOnwj8C/By4KyIuGWiY+hKE2Jvu2SWb64Q11BpDnFTw56/9jkzm+gqukJsZmZm9U1SAbgGOBVYCJwtaeGw0x4D3g58rVpxlD53zXaF2CzXXCGuocEKcUPlCvGzO/vo6RtgWqO/pzCz+pfVnFHwvNG8uuuuuzjx1BN59qRnOfCuA/n+7d/POqS8OgFoj4iNAJJuBJYCD5VOiIhN6bGq7UnZuSOtEHtRLbNcc+ZVQ4NziCsNmW5uIoDfbN9Z46jMzOrfQPMA20/dzkCz93vPu+IrivQ9v4/iK4pZh5JnhwGby9pb0r69JulcSeslrd+2bdtePXdwyLQTYrNcc4W4hvr6gwYli2gNV1ryf0tXkSNaZ9Y6NDOzmqtVFfWkk04akgQdcPcBnjc6TllW8athV+Mudi3cBYLe3+3l3R98N9P7pmcd1n7L86iEiLgOuA5g0aJFsTfPHRwy7VWmzXLNCXEN9Q/EHlsulZQ2hd/a2V3LkMxsChprMZr9VW9J0EDzALuOTpKgXUfvYubPZ1Z1yHSt1CIJam9v51cbfsoRB9THtoCPvKIb0u+kIwZ45IB7edHPm7MNaj899lwh6xD2xVbg8LL2vLSvprqKvRQaxEEz/HHYLM98B6ihvoGBisOlYfeCDlu7nBCb2cjKFqNZQjLM8D5JqyLiodGfOX7t7e387MFf0D/z4Im6ZKa6Xz20vWMR/PhnT2YTzAQpFJ+uyets3bqV2Kua2+TVM32Ap47sTb5GAqIATx3Ry+G/nM60XVN3BllE8t9pirkPOFrSUSSJ8FnAn9c6iM5iD7Obm1CFkXtmlh9OiGuorz/22IO4pLHQwIEzGl0hNrOxjLkYzf7aunUr9PdSKHZM1CUzM9DcT8+Rnbv/tWuEnvmdzPxJIw07p2RlLdHfV7MkaFe/ePTZKfy7SnW+ZCfDZ5APCB56YQ9z7p2VSUwTYVe/mGrRR0SfpPOAtSRfUdwQERskXQasj4hVkl4N/Ccw9KP4OAAAFORJREFUB3izpL+PiJdOZBxd3b20eLi0We45Ia6hvoGouMJ0ycGzpvHr3+6oYURmNgVVWozmNRP5Ai0tLXR318eXc0+/6unBIbKDBH3HdXPwT6ZyBXwaLS0tVX+VN7zhDXUzfP7eI+6FwrDtDQugI6ZxTPFV2QQ1QRYsWJB1CHstIlYDq4f1XVL2+D6SodRV8/+3d+dRdpR1Gse/T3dnhZBOmoBZgLBkwACyJGFR8aCSkHhExiMeAx5pBSdz3EbhDArHGcRtFHVwYEABAVkUWSJqDuMYQB0dGQkkQjZCQiAsYc/WkYQkvfzmj3o73ly6O+nk9r23+j6fc+p01VtvVf3um0vxvvd9660Nm7fR6FcumdU8N4jLqK29g4b67odljR4+mMWrW+joCOp6aDibme2MpFnALIADDzywV8fecMMNfRFSRZw15yyWr1++Y2I9jJ0yltlfn12ZoHKkP07U1Pn8uCdWs/WbWhk9fHClwzCzCsvvQzM51NbR/ZBpgDHDh7BpWzvPrHUvsZl1a5cmo4mI6yNickRMHjVqVNmCqzazPzCbM5afQdOPm7YvH3zqg8z+gBvDtaq1tZWVK1eydm3+HwmwPdPyRuv2t3yYWe1yD3EZte+kQTy6MZvpcumLGzlk1N7lCsvM8qUqJqMphXLNZr1w4cIdtv/4xz/26SzTtfwKnD1Rru/DihUraGtrY9asWYwb16cjcv1dqHLrN2/zM8Rm5h7icmptjx6HTO8/bBAD6sXSFzeWMSozy5OIaAM6J6NZBtwVEUsrG5VZPrS2ttLW1gbAunXraG1trXBEVilb29rZvK19+2svzax2uYe4jNo7Ohg8oPuZOhvq65iw3zAef8kNYjPrXleT0eRRuXrOTj311Del+fnR6lOO78MVV1yxvYe4vr6eCRMmcMEFF/T5da36tGzOfgwZ7iHTZjXPPcRltLNniAGOGrsPi1dvIPrLix/NzMyqxAMPPLC9h7itrY3777+/whFZpaxPDWL3EJuZG8Rl1NYe1PcwZBpgyviRrN/cypOvvl6mqMzMzGrDaaedRkNDNjiuoaGBqVOnVjgiq5QNm7NXcI1wD7FZzXODuIzaOjp22kN80iFNADz0tGe/NDMrhfr6+h63rXY0NzdTV5dVferr6zn33HMrHJFVSmcP8XC/h9is5rlBXEa7MmT6gJFDGds4xA1iM7MSOe2003rcttrR1NTE9OnTkcT06dNpamqqdEhWIS1vpB7ivdxDbFbr3CAuo7b2oKG+5wYxZL3EDz29zs8Rm5mVwKxZs3rcttrS3NzM0Ucf7d7hGtfZQ9zoHmKzmucGcRll7yHeeZG/47Am1m3axoJn15chKjOz/k/SDn+tdjU1NXHVVVe5d7jGbdjcysD6OoYO9CMUZrXODeIy2pVniG+f9xwtb7QysKGOf/v1E9w+77kyRWdm1j/dcsst20fcRAS33nprhSMyM0nTJS2XtFLSxV3sHyTpzrR/nqTxpbz+hs3bGD50gH8kMzM3iMulvSPoCKjfhSHTgxrqOWZcI4tf2MCW1vYyRGdm1n8Vv1rnvvvuq1AkZgYgqR64BpgBTATOljSxKNv5wPqIOAz4PnB5KWNYv3mbX7lkZoAbxGWzra0DgAG7MGQa4ISDR9LaHsxd+nJfhmVm1u/tv//+PW6bWdmdAKyMiKcjYhtwB3BmUZ4zgVvS+mzgvSphd+6Gza00+pVLZoYbxGWztS3r6a3fyZDpTmMbh3DKhH2Zt2odv1nyUl+GZmbWr73yyis9bptZ2Y0Fni/YXp3SuswTEW1AC/CmB78lzZI0X9L81157bZcDmDx+BKcctm9v4zazfsgN4jLp7CHelVmmO02b+BbGDB/MZXMeZ9PWtr4KzcysX5s6deoOk2pNmzatwhGZWalExPURMTkiJo8aNWqXj7vo9CP43Hsn9GFkZpYXbhCXydbOBvEuDpmGrDf5jGPG8PLGLfz7fSv6KjQzs36tubmZhoYGAAYMGODX7ZhV3gvAAQXb41Jal3kkNQDDgbVlic7MaoobxGXytwZx7x5/OahpLz520kHc9OAq7p7//M4PMDOzHTQ1NTFjxgwkMWPGDL9ux6zyHgEmSDpY0kBgJjCnKM8coDmtnwX8LjqnizczK6GGSgdQK3r7DHGhS8+YyNNrXueLP1/Exi1tnPeO8X5NgJlZLzQ3N/PMM8+4d9isCkREm6TPAnOBeuCmiFgq6WvA/IiYA9wI3CZpJbCOrNFsZlZybhCXyeLVLQDsu/egXh979/zVTH3rW1i/qZWv3/s4dzz8HJ869VBOPXw/Ru7lGRLNzHamqamJq666qtJhmFkSEb8Gfl2UdmnB+hbgw+WOy8xqjxvEZfLAsldpHDqA/ffpfYMYYGBDHeeceCDznl7LfY+/woV3LWRgQx0zpxzARacfzrDBfpeemZmZmZlZb/Rpg1jSdOBKsuEwN0TEt4v2DwJuBSaRTZTwkYh4Ju27hOyl7O3AP0XE3J7OKelgsvfYNQELgI+ld9tV3JbWdv608jWOPaBxj4Y610mcfOi+nHhIEy+1bOHhVeu47c/Pcvf81Rw5Zh9mHD2ag0YOZdzIIYwePoR9Bjd4aLWZmZmZmVk3+qxBLKkeuAaYSvZ+uUckzYmIxwuynQ+sj4jDJM0ELgc+Imki2bMiRwJjgAck/V06prtzXg58PyLukHRtOvcP++rz7UxEEAEtb7Ty4/97hi2tHRzxln1Kcu46ibGNQ/jgcWOZMn4Ef1q5hiUvtjD/2fU75Bs6sJ79hg1i1LBB7DdsMKOGDWJMY/ZXdL6CJMs7oL6OIQPr2WdwA/sNG0x9nQigoyPS54EgqJOor8uWOomGOlGXtjs/dydJ1CmLV+lvXUpzQ93MzMzMzCqtL3uITwBWRsTTAJLuAM4EChvEZwKXpfXZwNXKWkpnAndExFZgVZpQ4YSU703nlLQMeA9wTspzSzpvyRrER39lLm0dQRCpcQikRmJHpAYwWcOxK+8+fBSHjNqrVOFsN27EUGZOOZCIYPO2dtZu2saGzdtoeaOVjW+08tetbax5fRur1mzmr1tat892XS0628Xavq2i7c79O2YsbE6/KU+S/Yvs+G/S3fSUXZ2vq3MWn3v7dhTvL709+QlhT39/KC6HHcuo+t32yRM5/sARlQ7DzMzMzKpMXzaIxwKF7wlaDZzYXZ4042AL2ZDnscBDRceOTetdnbMJ2BARbV3k34GkWcCstPm6pOW9+Ey77ea0FNgXWFOOa5dAXmLNS5yQn1jzEif0EOukr/fqPAeVIphqsmDBgjWSnq10HFUgT99n61v+LmT61f2uhPe6PH4/8hgzOO5yymPMUJq4e7zX1dykWhFxPXB9peOQND8iJlc6jl2Rl1jzEifkJ9a8xAn5irXcImJUpWOoBv6OWCd/F/qnUt3r8vj9yGPM4LjLKY8xQ3niruvDc78AHFCwPS6ldZlHUgMwnGxyre6O7S59LdCYztHdtczMzMzMzMy268sG8SPABEkHSxpINknWnKI8c4DmtH4W8LvIZmWaA8yUNCjNHj0BeLi7c6Zjfp/OQTrnr/rws5mZmZmZmVnO9dmQ6fRM8GeBuWSvSLopIpZK+howPyLmADcCt6VJs9aRNXBJ+e4im4CrDfhMRLQDdHXOdMkvAXdI+gbwaDp3Nav4sO1eyEuseYkT8hNrXuKEfMVqleHviHXyd8F6ksfvRx5jBsddTnmMGcoQt6K7aZHNzMzMzMzM+rG+HDJtZmZmZmZmVrXcIDYzMzMzM7Oa5AZxBUiaLmm5pJWSLi7TNQ+Q9HtJj0taKunzKX2kpPslPZn+jkjpknRVinGRpOMLztWc8j8pqbkgfZKkxemYqyRpD+Ktl/SopHvT9sGS5qVz35kmVSNNvHZnSp8naXzBOS5J6cslnV6QXrLyl9QoabakJyQtk3RyNZappAvSv/sSST+TNLhaylTSTZJelbSkIK3Py7C7a5iZWW0qZf1gN6+fq7paF/Hnou5WFHMu6nFFMVdtna4ozvzU7yLCSxkXssnAngIOAQYCC4GJZbjuaOD4tD4MWAFMBL4DXJzSLwYuT+vvA/4bEHASMC+ljwSeTn9HpPURad/DKa/SsTP2IN4LgduBe9P2XcDMtH4t8Km0/mng2rQ+E7gzrU9MZTsIODiVeX2pyx+4BfhkWh8INFZbmQJjgVXAkIKy/Hi1lCnwLuB4YElBWp+XYXfX8OLFixcvtbeUun6wmzHkqq7WRfy5qLsVxVz19biieKu6TlcUa27qdxW/AdXaApwMzC3YvgS4pAJx/AqYCiwHRqe00cDytH4dcHZB/uVp/9nAdQXp16W00cATBek75OtlbOOA3wLvAe5NX/Q1QENxGZLNOH5yWm9I+VRcrp35Sln+ZO/NXkWanK64rKqlTMluns+nm0lDKtPTq6lMgfHseMPs8zLs7hpe8r+k79My4EfAUuA+YAhwLPAQsAj4Bel/ql763wJ8DfhCwfY3gc8DF5G9wnER8NW0by/gv8gqfkuAj1Q6fi8V+c5URf2sKKaqrat1EWsu6m5FMeeiHlcUW9XX6YriHU8O6nceMl1+nV/kTqtTWtmk4RLHAfOA/SPipbTrZWD/tN5dnD2lr+4ifXf8B/BFoCNtNwEbIqKti3Nvjyftb0n5exv/7jgYeA34cRoidIOkvaiyMo2IF4DvAc8BL5GV0QKqs0w7laMMu7uG9Q8TgGsi4khgA/Ah4FbgSxHxNmAx8JUKxmd96ybgXABJdWQ9Iy+TfS9OIPtxZJKkdwHTgRcj4piIOAr4TWVCtgqreP2sUA7qasXyUncrlIt6XKGc1ukKVWX9zg3iGiNpb+DnZL+cbyzcF9lPKVGRwBJJ7wdejYgFlYxjFzWQDQX5YUQcB2wiG5qxXZWU6QjgTLIb/xiy3pDplYypN8pRhtXw72QltyoiHkvrC4BDgcaI+ENKu4VsOJf1QxHxDLBW0nHANOBRYErB+l+AI8gayIuBqZIul3RKRLRUJmqzTLXX1YrlrO5WKBf1uEJ5r9MVqqb6nRvE5fcCcEDB9riU1uckDSC7wf40Iu5Jya9IGp32jwZe3UmcPaWP6yK9t94BfEDSM8AdZENvrgQaJTV0ce7t8aT9w4G1uxH/7lgNrI6IeWl7NtmNtdrK9DSyxsFrEdEK3ENWztVYpp3KUYbdXcP6h60F6+1kz4VZbbmB7Nm6T5D1GAv4VkQcm5bDIuLGiFhBdu9eDHxD0qUVi9gqqWL1s0I5qasVy1PdrVBe6nGF8linK1SV9Ts3iMvvEWBCmg1uINkwrjl9fdE089qNwLKIuKJg1xygOa03kz2v0pl+bpr17SSgJQ0/mAtMkzQi/Uo1jexZg5eAjZJOStc6t+BcuywiLomIcRExnqxsfhcRHwV+D5zVTZyd8Z+V8kdKn5lm1zuYrBfgYUpY/hHxMvC8pMNT0nuBx6myMiUbVnOSpKHpPJ1xVl2ZFihHGXZ3DeufWoD1kk5J2x8D/tBDfsu/X5D1nEwhu0fMBc5LvW9IGitpP0ljgM0R8RPgu2QVYqs9FamfFcpLXa1YnupuRXHnpR5XKI91ukLVWb/rzYPRXkqzkM2ktoJsFrcvl+ma7yQbMrAIeCwt7yN7juC3wJPAA8DIlF/ANSnGxcDkgnOdB6xMyycK0ieTTUjyFHA1RZMU7EbMp/K3mQoPIfsPdSVwNzAopQ9O2yvT/kMKjv9yimU5BbP6lbL8yZ5Dm5/K9ZdkM+BVXZkCXwWeSOe6jWxWwaooU+BnZM/BtJL9Wnt+Ocqwu2t4yf/Cmyfx+GfgMnacVOuXeFKtfr+Qzbb67YLtz6d7x2Lgz2RD6U/nb/9vfKTwvuKltpZS1g928/q5q6t18RlOpcrrbkXx5qIeVxRz1dbpiuLMTf2u80AzMzOzfkPZZFp/AT4cEU9WOh4zM6tOHjJtZmZm/YqkiWS9Cb91Y9jMzHriHmIzMzMzMzOrSe4hNjMzMzMzs5rkBrGZmZmZmZnVJDeIzczMzMzMrCa5QWy5JWm8pCW9yH+zpLN2ntPMrHpJapL0WFpelvRCwfbAEl+rUdKnS3lOMzOzatJQ6QDMzMxs10XEWrJ3ZyLpMuD1iPjezo6T1BARbb28XCPwaeAHvY3TzMwsD9xDbHnXIOmnkpZJmi1pqKRLJT0iaYmk6yWp+KDu8kj6H0mXS3pY0gpJp6T0eknfS/kXSfpcSp8k6Q+SFkiaK2l0eT++mRlI+od0T1so6eeShqb0myVdK2ke8B1Jh0p6SNJiSd+Q9HrBOS5K51gk6asp+dvAoan3+bsV+GhmZmZ9yg1iy7vDgR9ExFuBjWQ9GVdHxJSIOAoYAry/i+N6ytMQEScAXwC+ktJmAeOBYyPibcBPJQ0A/hM4KyImATcB3yz5JzQz27l70j3tGGAZcH7BvnHA2yPiQuBK4MqIOBpY3ZlB0jRgAnACWe/zJEnvAi4GnoqIYyPiojJ9FjMzs7Jxg9jy7vmIeDCt/wR4J/BuSfMkLQbeAxzZxXE95bkn/V1A1ggGOA24rnO4YUSsI2uMHwXcL+kx4F/IKp5mZuV2lKT/Tfe0j7LjPe3uiGhP6ycDd6f12wvyTEvLo8BfgCPIGshmZmb9mp8htryLLrZ/AEyOiOfT83WDCzNIGryTPFvT33Z6/m9EwNKIOHn3wzczK4mbgb+PiIWSPg6cWrBv0y4cL+BbEXHdDonS+NKEZ2ZmVp3cQ2x5d6CkzgbpOcCf0voaSXsDXc0qPXgX8hS7H/hHSQ0AkkYCy4FRndeXNEBSV73RZmZ9bRjwUnqU46M95HsI+FBan1mQPhc4L90TkTRW0n7AX9O5zczM+iU3iC3vlgOfkbQMGAH8EPgRsISsgvdI8QERsWFnebpwA/AcsEjSQuCciNhG1pi+PKU9Brx9jz+RmVnv/SswD3gQeKKHfF8ALpS0CDgMaAGIiPvIhlD/OQ27ng0MSzNaP5gmFPSkWmZm1u8oonjEqZmZmfVHafbpNyIiJM0Ezo6IMysdl5mZWaX4GWIzM7PaMQm4Or1qbgNwXoXjMTMzqyj3EJuZmZmZmVlN8jPEZmZmZmZmVpPcIDYzMzMzM7Oa5AaxmZmZmZmZ1SQ3iM3MzMzMzKwmuUFsZmZmZmZmNen/AU/RNKZufpa6AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 1152x288 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x288 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x288 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x288 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x288 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x288 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Qtg0wJiuYggX",
        "outputId": "785a971f-2ea8-4600-b342-f91a1be72b6a"
      },
      "source": [
        "# Quantiles\n",
        "for column in int_column:\n",
        "  print(f'For {column}:')\n",
        "\n",
        "  print('Min:', df[column].quantile(q = 0))\n",
        "  print('1º Quartile:', df[column].quantile(q = 0.25))\n",
        "  print('2º Quartile:', df[column].quantile(q = 0.50))\n",
        "  print('3º Quartile:', df[column].quantile(q = 0.75))\n",
        "  print('Max:', df[column].quantile(q = 1.00),'\\n')"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "For age:\n",
            "Min: 18.0\n",
            "1º Quartile: 33.0\n",
            "2º Quartile: 39.0\n",
            "3º Quartile: 48.0\n",
            "Max: 95.0 \n",
            "\n",
            "For balance:\n",
            "Min: -8019.0\n",
            "1º Quartile: 72.0\n",
            "2º Quartile: 448.0\n",
            "3º Quartile: 1428.0\n",
            "Max: 102127.0 \n",
            "\n",
            "For day:\n",
            "Min: 1.0\n",
            "1º Quartile: 8.0\n",
            "2º Quartile: 16.0\n",
            "3º Quartile: 21.0\n",
            "Max: 31.0 \n",
            "\n",
            "For duration:\n",
            "Min: 0.0\n",
            "1º Quartile: 103.0\n",
            "2º Quartile: 180.0\n",
            "3º Quartile: 319.0\n",
            "Max: 4918.0 \n",
            "\n",
            "For campaign:\n",
            "Min: 1.0\n",
            "1º Quartile: 1.0\n",
            "2º Quartile: 2.0\n",
            "3º Quartile: 3.0\n",
            "Max: 63.0 \n",
            "\n",
            "For pdays:\n",
            "Min: -1.0\n",
            "1º Quartile: -1.0\n",
            "2º Quartile: -1.0\n",
            "3º Quartile: -1.0\n",
            "Max: 871.0 \n",
            "\n",
            "For previous:\n",
            "Min: 0.0\n",
            "1º Quartile: 0.0\n",
            "2º Quartile: 0.0\n",
            "3º Quartile: 0.0\n",
            "Max: 275.0 \n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "k0OXEVGHYgdm"
      },
      "source": [
        "df.drop(df[df.age>65].index, inplace=True)\n",
        "df.drop(df[df.balance>10000].index, inplace=True)\n",
        "df.drop(df[df.duration>1000].index, inplace=True)\n",
        "df.drop(df[df.campaign>10].index, inplace=True)\n",
        "df.drop(df[df.pdays>400].index, inplace=True)"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "rXXJ-lB5q2jb",
        "outputId": "58be5861-89fa-4396-e83e-b98cc73e84fa"
      },
      "source": [
        "data = df[df['previous']<10]\n",
        "plt.figure(figsize=(16,4))\n",
        "\n",
        "plt.subplot(1,3,1)\n",
        "sns.distplot(data['previous'])\n",
        "plt.xlabel('previous')\n",
        "plt.ylabel('Density')\n",
        "plt.title(f'previous  Distribution')\n",
        "\n",
        "plt.subplot(1,3,2)\n",
        "sns.boxplot(x='y', y='previous', data =data, showmeans=True )\n",
        "plt.xlabel('Target')\n",
        "plt.ylabel('previous')\n",
        "plt.title(f'previous  Distribution')\n",
        "\n",
        "plt.subplot(1,3,3)\n",
        "counts, bins = np.histogram(data['previous'], bins=20, normed=True)\n",
        "cdf = np.cumsum (counts)\n",
        "plt.plot (bins[1:], cdf/cdf[-1])\n",
        "#plt.xticks(range(15,100,5))\n",
        "plt.yticks(np.arange(0,1.1,.1))\n",
        "plt.title(f'previous  cdf')\n",
        "plt.show()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x288 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7CPwJ10IqGDb",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "538348f7-b705-4662-b784-a3fb2cdb0424"
      },
      "source": [
        "df.drop(df[df.previous>10].index, inplace=True)\n",
        "df.y.value_counts()"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "no     36962\n",
              "yes     4049\n",
              "Name: y, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZkQhfUfKuc12"
      },
      "source": [
        "##For object type"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "a1o9gP9QqF5f"
      },
      "source": [
        "dfgrouped = df.groupby('y')"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HVlsRuCEa7Bj"
      },
      "source": [
        "def plot_barh(array,incrementer, bias, text_color ='blue', palette_style = 'darkgrid',palette_color = 'RdBu'):\n",
        "\n",
        "  sns.set_style(palette_style)\n",
        "  sns.set_palette(palette_color)\n",
        "\n",
        "  plt.barh(array.index, width = array.values, height = .5)\n",
        "  plt.yticks(np.arange(len(array)))\n",
        "  plt.xticks( range(0, round(max(array)) +bias, incrementer ))\n",
        "\n",
        "  for index, value in enumerate(array.values):\n",
        "    plt.text(value +.5, index, s= '{:.1f}%'.format(value), color = text_color)\n",
        "\n",
        "  #plt.show()\n",
        "  return plt"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b7oPTzVR2ZDC"
      },
      "source": [
        "def feature_perc(feature,groupby= 'yes'):\n",
        "\n",
        "  count = dfgrouped.get_group(groupby)[feature].value_counts()\n",
        "  total_count = df[feature].value_counts()[count.index]\n",
        "\n",
        "  perc = (count/total_count)*100\n",
        "  return perc "
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DUmxLRH4uRnv",
        "outputId": "892d830e-01e4-442f-b22a-7e3c5f4c466c"
      },
      "source": [
        "obj_column = df.dtypes[df.dtypes == 'object'].index\n",
        "obj_column"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['job', 'marital', 'education', 'default', 'housing', 'loan', 'contact',\n",
              "       'month', 'poutcome', 'y'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UDvh1xXldiQk",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "8ff45987-ff23-42fb-b81a-a450830ccdf4"
      },
      "source": [
        "for column in obj_column[:-1]:\n",
        "\n",
        "  yes_perc = feature_perc(column, groupby='yes')\n",
        "  no_perc = feature_perc(column, groupby='no')\n",
        "\n",
        "  plt.figure(figsize=(16,6))\n",
        "\n",
        "  plt.subplot(1,2,1)\n",
        "  plt.title(f'Success rate by  {column}')\n",
        "  plot_barh(yes_perc.sort_values(),5,10)\n",
        "\n",
        "  plt.subplot(1,2,2)\n",
        "  plt.title(f'Failure rate by  {column}')\n",
        "  plot_barh(no_perc.sort_values(),5,10)\n",
        "  plt.show()\n",
        "  print()\n"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lq3CzzWnwuDB"
      },
      "source": [
        "##Modeling"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dt45S5OgBsS1"
      },
      "source": [
        "df1 = df.copy()\n",
        "df1['y'] = df1.y.apply(lambda x:0 if x=='no' else 1)"
      ],
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_BVL0k_E4B1m",
        "outputId": "6f4c003a-212e-4538-ca31-84def8934797"
      },
      "source": [
        "df1.y.value_counts()"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    36962\n",
              "1     4049\n",
              "Name: y, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9rmyYyTB4npm",
        "outputId": "97afd5fb-da2e-45e4-fe06-5ee4a27e9005"
      },
      "source": [
        "from sklearn.utils import resample\n",
        "\n",
        "# Separate majority and minority classes\n",
        "df1_majority = df1[df1.y==0]\n",
        "df1_minority = df1[df1.y==1]\n",
        " \n",
        "# Upsample minority class\n",
        "df1_minority_upsampled = resample(df1_minority, \n",
        "                                 replace=True,     # sample with replacement\n",
        "                                 n_samples=36962,    # to match majority class\n",
        "                                 random_state=42) # reproducible results\n",
        " \n",
        "# Combine majority class with upsampled minority class\n",
        "df = pd.concat([df1_majority, df1_minority_upsampled])\n",
        " \n",
        "# Display new class counts\n",
        "df.y.value_counts()"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1    36962\n",
              "0    36962\n",
              "Name: y, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "dwSoFfTe5FEp",
        "outputId": "157c9f18-b01a-4093-b9f4-153d9aa4dda2"
      },
      "source": [
        "df"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>age</th>\n",
              "      <th>job</th>\n",
              "      <th>marital</th>\n",
              "      <th>education</th>\n",
              "      <th>default</th>\n",
              "      <th>balance</th>\n",
              "      <th>housing</th>\n",
              "      <th>loan</th>\n",
              "      <th>contact</th>\n",
              "      <th>day</th>\n",
              "      <th>month</th>\n",
              "      <th>duration</th>\n",
              "      <th>campaign</th>\n",
              "      <th>pdays</th>\n",
              "      <th>previous</th>\n",
              "      <th>poutcome</th>\n",
              "      <th>y</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>58</td>\n",
              "      <td>management</td>\n",
              "      <td>married</td>\n",
              "      <td>tertiary</td>\n",
              "      <td>no</td>\n",
              "      <td>2143</td>\n",
              "      <td>yes</td>\n",
              "      <td>no</td>\n",
              "      <td>unknown</td>\n",
              "      <td>5</td>\n",
              "      <td>may</td>\n",
              "      <td>261</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>44</td>\n",
              "      <td>technician</td>\n",
              "      <td>single</td>\n",
              "      <td>secondary</td>\n",
              "      <td>no</td>\n",
              "      <td>29</td>\n",
              "      <td>yes</td>\n",
              "      <td>no</td>\n",
              "      <td>unknown</td>\n",
              "      <td>5</td>\n",
              "      <td>may</td>\n",
              "      <td>151</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>33</td>\n",
              "      <td>entrepreneur</td>\n",
              "      <td>married</td>\n",
              "      <td>secondary</td>\n",
              "      <td>no</td>\n",
              "      <td>2</td>\n",
              "      <td>yes</td>\n",
              "      <td>yes</td>\n",
              "      <td>unknown</td>\n",
              "      <td>5</td>\n",
              "      <td>may</td>\n",
              "      <td>76</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>47</td>\n",
              "      <td>blue-collar</td>\n",
              "      <td>married</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "      <td>1506</td>\n",
              "      <td>yes</td>\n",
              "      <td>no</td>\n",
              "      <td>unknown</td>\n",
              "      <td>5</td>\n",
              "      <td>may</td>\n",
              "      <td>92</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>33</td>\n",
              "      <td>unknown</td>\n",
              "      <td>single</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "      <td>1</td>\n",
              "      <td>no</td>\n",
              "      <td>no</td>\n",
              "      <td>unknown</td>\n",
              "      <td>5</td>\n",
              "      <td>may</td>\n",
              "      <td>198</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21858</th>\n",
              "      <td>40</td>\n",
              "      <td>admin.</td>\n",
              "      <td>single</td>\n",
              "      <td>tertiary</td>\n",
              "      <td>no</td>\n",
              "      <td>27</td>\n",
              "      <td>no</td>\n",
              "      <td>no</td>\n",
              "      <td>cellular</td>\n",
              "      <td>20</td>\n",
              "      <td>aug</td>\n",
              "      <td>467</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41199</th>\n",
              "      <td>45</td>\n",
              "      <td>housemaid</td>\n",
              "      <td>married</td>\n",
              "      <td>secondary</td>\n",
              "      <td>no</td>\n",
              "      <td>4068</td>\n",
              "      <td>no</td>\n",
              "      <td>no</td>\n",
              "      <td>cellular</td>\n",
              "      <td>20</td>\n",
              "      <td>aug</td>\n",
              "      <td>184</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43503</th>\n",
              "      <td>30</td>\n",
              "      <td>student</td>\n",
              "      <td>single</td>\n",
              "      <td>tertiary</td>\n",
              "      <td>no</td>\n",
              "      <td>7529</td>\n",
              "      <td>no</td>\n",
              "      <td>no</td>\n",
              "      <td>cellular</td>\n",
              "      <td>20</td>\n",
              "      <td>apr</td>\n",
              "      <td>175</td>\n",
              "      <td>6</td>\n",
              "      <td>183</td>\n",
              "      <td>1</td>\n",
              "      <td>success</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44327</th>\n",
              "      <td>64</td>\n",
              "      <td>retired</td>\n",
              "      <td>married</td>\n",
              "      <td>secondary</td>\n",
              "      <td>no</td>\n",
              "      <td>1574</td>\n",
              "      <td>no</td>\n",
              "      <td>no</td>\n",
              "      <td>telephone</td>\n",
              "      <td>29</td>\n",
              "      <td>jul</td>\n",
              "      <td>301</td>\n",
              "      <td>3</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40219</th>\n",
              "      <td>31</td>\n",
              "      <td>management</td>\n",
              "      <td>single</td>\n",
              "      <td>tertiary</td>\n",
              "      <td>no</td>\n",
              "      <td>5205</td>\n",
              "      <td>no</td>\n",
              "      <td>no</td>\n",
              "      <td>cellular</td>\n",
              "      <td>9</td>\n",
              "      <td>jun</td>\n",
              "      <td>529</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>73924 rows × 17 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       age           job  marital  education  ... pdays  previous poutcome  y\n",
              "0       58    management  married   tertiary  ...    -1         0  unknown  0\n",
              "1       44    technician   single  secondary  ...    -1         0  unknown  0\n",
              "2       33  entrepreneur  married  secondary  ...    -1         0  unknown  0\n",
              "3       47   blue-collar  married    unknown  ...    -1         0  unknown  0\n",
              "4       33       unknown   single    unknown  ...    -1         0  unknown  0\n",
              "...    ...           ...      ...        ...  ...   ...       ...      ... ..\n",
              "21858   40        admin.   single   tertiary  ...    -1         0  unknown  1\n",
              "41199   45     housemaid  married  secondary  ...    -1         0  unknown  1\n",
              "43503   30       student   single   tertiary  ...   183         1  success  1\n",
              "44327   64       retired  married  secondary  ...    -1         0  unknown  1\n",
              "40219   31    management   single   tertiary  ...    -1         0  unknown  1\n",
              "\n",
              "[73924 rows x 17 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YLKnDTUWDw0R"
      },
      "source": [
        "from sklearn.tree import DecisionTreeClassifier\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from xgboost import XGBClassifier\n",
        "from sklearn.preprocessing import LabelEncoder\n",
        "\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import classification_report, confusion_matrix"
      ],
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pevKH7GkxT9V"
      },
      "source": [
        "obj_column = df.dtypes[df.dtypes == 'object'].index\n",
        "mapingdf = pd.DataFrame()\n",
        "\n",
        "for column in obj_column:\n",
        "\n",
        "  labelencoder = LabelEncoder()\n",
        "  df[column] = labelencoder.fit_transform(df[column])\n",
        "  mapingdf[column] = df[column]\n",
        "  mapingdf['_'+column] =  labelencoder.inverse_transform(df[column])\n"
      ],
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aNcoDkDFy-62"
      },
      "source": [
        "#for reference\n",
        "#mapingdf"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "lqPWGJqVzrHm",
        "outputId": "69853896-f4ec-4a41-d732-b24d04cc903e"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>age</th>\n",
              "      <th>job</th>\n",
              "      <th>marital</th>\n",
              "      <th>education</th>\n",
              "      <th>default</th>\n",
              "      <th>balance</th>\n",
              "      <th>housing</th>\n",
              "      <th>loan</th>\n",
              "      <th>contact</th>\n",
              "      <th>day</th>\n",
              "      <th>month</th>\n",
              "      <th>duration</th>\n",
              "      <th>campaign</th>\n",
              "      <th>pdays</th>\n",
              "      <th>previous</th>\n",
              "      <th>poutcome</th>\n",
              "      <th>y</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>58</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>2143</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>8</td>\n",
              "      <td>261</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>44</td>\n",
              "      <td>9</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>29</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>8</td>\n",
              "      <td>151</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>33</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>8</td>\n",
              "      <td>76</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>47</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>1506</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>8</td>\n",
              "      <td>92</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>33</td>\n",
              "      <td>11</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>8</td>\n",
              "      <td>198</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   age  job  marital  education  ...  pdays  previous  poutcome  y\n",
              "0   58    4        1          2  ...     -1         0         3  0\n",
              "1   44    9        2          1  ...     -1         0         3  0\n",
              "2   33    2        1          1  ...     -1         0         3  0\n",
              "3   47    1        1          3  ...     -1         0         3  0\n",
              "4   33   11        2          3  ...     -1         0         3  0\n",
              "\n",
              "[5 rows x 17 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mpm5O6351kRm",
        "outputId": "e27ad8b1-e7b3-41e8-9b65-72a20cf85d52"
      },
      "source": [
        "df.corr().y.sort_values()"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "contact     -0.287678\n",
              "housing     -0.234987\n",
              "campaign    -0.140778\n",
              "loan        -0.128360\n",
              "poutcome    -0.125167\n",
              "age         -0.044686\n",
              "day         -0.041679\n",
              "month       -0.036743\n",
              "default     -0.030869\n",
              "job          0.072338\n",
              "marital      0.096899\n",
              "balance      0.115064\n",
              "education    0.140118\n",
              "pdays        0.142358\n",
              "previous     0.207097\n",
              "duration     0.473165\n",
              "y            1.000000\n",
              "Name: y, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M44UNRUBFfQh"
      },
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(df.drop('y',axis=1),\n",
        "                                                    df['y'],\n",
        "                                                    test_size=.3, random_state = 42,\n",
        "                                                    stratify= df['y'])"
      ],
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iS1vLYpADwxp"
      },
      "source": [
        "scaler = MinMaxScaler()\n",
        "X_train = scaler.fit_transform(X_train)\n",
        "X_test = scaler.transform(X_test)"
      ],
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PzdG77KKDwu5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6a42eed0-b502-4d3b-d0ae-8fbb3fce8ae7"
      },
      "source": [
        "models = [DecisionTreeClassifier(),\n",
        "          RandomForestClassifier(),\n",
        "          XGBClassifier()]\n",
        "\n",
        "names = [ 'DecisionTreeClassifier',\n",
        "          'RandomForestClassifier',\n",
        "          'XGBClassifier']\n",
        "\n",
        "for model,name in zip(models,names):\n",
        "  m = model.fit(X_train,y_train)\n",
        "  print(name, 'report:')\n",
        "  print('Train score',model.score(X_train,y_train))\n",
        "  print('Test score',model.score(X_test,y_test))\n",
        "  print()\n",
        "  print(\"Train confusion matrix:\\n\",confusion_matrix(y_train, model.predict(X_train)),'\\n')\n",
        "  print(\"Test confusion matrix:\\n\",confusion_matrix(y_test, model.predict(X_test)))\n",
        "  print('*'*50)\n"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "DecisionTreeClassifier report:\n",
            "Train score 1.0\n",
            "Test score 0.9626657047524574\n",
            "\n",
            "Train confusion matrix:\n",
            " [[25873     0]\n",
            " [    0 25873]] \n",
            "\n",
            "Test confusion matrix:\n",
            " [[10270   819]\n",
            " [    9 11080]]\n",
            "**************************************************\n",
            "RandomForestClassifier report:\n",
            "Train score 1.0\n",
            "Test score 0.9752457390206511\n",
            "\n",
            "Train confusion matrix:\n",
            " [[25873     0]\n",
            " [    0 25873]] \n",
            "\n",
            "Test confusion matrix:\n",
            " [[10546   543]\n",
            " [    6 11083]]\n",
            "**************************************************\n",
            "XGBClassifier report:\n",
            "Train score 0.8589649441502725\n",
            "Test score 0.861168725764271\n",
            "\n",
            "Train confusion matrix:\n",
            " [[21351  4522]\n",
            " [ 2776 23097]] \n",
            "\n",
            "Test confusion matrix:\n",
            " [[9185 1904]\n",
            " [1175 9914]]\n",
            "**************************************************\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5bbKcM5_kW2e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 846
        },
        "outputId": "0919fa2d-cc2e-4a5e-9ae0-b750e2cc269c"
      },
      "source": [
        "model = DecisionTreeClassifier(max_depth=3)\n",
        "model.fit(X_train, y_train)"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 1440x1080 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fQgH67R3NvmJ",
        "outputId": "6a7693ff-0d1a-499b-b04c-560bb69c8614"
      },
      "source": [
        "importances = model.feature_importances_\n",
        "importances"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0.        , 0.        , 0.        , 0.        , 0.        ,\n",
              "       0.        , 0.        , 0.        , 0.12608547, 0.        ,\n",
              "       0.0403823 , 0.67411934, 0.        , 0.        , 0.08096314,\n",
              "       0.07844975])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JlLUz7LmN4oA",
        "outputId": "62c20c28-eb53-4f22-b377-7e9a8137458b"
      },
      "source": [
        "indices = np.argsort(importances)[::-1]\n",
        "indices"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([11,  8, 14, 15, 10, 13, 12,  9,  7,  6,  5,  4,  3,  2,  1,  0])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DNzvzjDTN2RM",
        "outputId": "4ddac28e-9220-4a60-85f6-11c8ce549c82"
      },
      "source": [
        "columns = df.drop('y', axis=1).columns\n",
        "columns"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['age', 'job', 'marital', 'education', 'default', 'balance', 'housing',\n",
              "       'loan', 'contact', 'day', 'month', 'duration', 'campaign', 'pdays',\n",
              "       'previous', 'poutcome'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "8KvGThXhN2Od",
        "outputId": "0f623a77-4070-4aeb-c691-9346e623f047"
      },
      "source": [
        "columns[0]"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'age'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UxA9XBmhNvdk",
        "outputId": "591af3aa-18e0-4384-cad9-a279a40fae72"
      },
      "source": [
        "names = [columns[i] for i in indices]\n",
        "names"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['duration',\n",
              " 'contact',\n",
              " 'previous',\n",
              " 'poutcome',\n",
              " 'month',\n",
              " 'pdays',\n",
              " 'campaign',\n",
              " 'day',\n",
              " 'loan',\n",
              " 'housing',\n",
              " 'balance',\n",
              " 'default',\n",
              " 'education',\n",
              " 'marital',\n",
              " 'job',\n",
              " 'age']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 618
        },
        "id": "CzMyUDTwQiIf",
        "outputId": "a495d930-d3f0-46d6-a167-2c864e3b46b8"
      },
      "source": [
        "import graphviz\n",
        "from sklearn import tree\n",
        "# DOT data\n",
        "dot_data = tree.export_graphviz(model, out_file=None, \n",
        "                                feature_names= df1.drop('y', axis=1).columns,  \n",
        "                                class_names= ['yes','no'],\n",
        "                                filled=True)\n",
        "\n",
        "# Draw graph\n",
        "graph = graphviz.Source(dot_data, format=\"png\") \n",
        "graph"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<graphviz.files.Source at 0x7fd087ff5f90>"
            ],
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font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.5</text>\n<text text-anchor=\"middle\" x=\"449.5\" y=\"-141.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">samples = 4863</text>\n<text text-anchor=\"middle\" x=\"449.5\" y=\"-126.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">value = [2497, 2366]</text>\n<text text-anchor=\"middle\" x=\"449.5\" y=\"-111.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">class = yes</text>\n</g>\n<!-- 1&#45;&gt;5 -->\n<g id=\"edge5\" class=\"edge\">\n<title>1&#45;&gt;5</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M449.5,-222.8796C449.5,-214.6838 449.5,-205.9891 449.5,-197.5013\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"453.0001,-197.298 449.5,-187.2981 446.0001,-197.2981 453.0001,-197.298\"/>\n</g>\n<!-- 3 -->\n<g id=\"node4\" class=\"node\">\n<title>3</title>\n<polygon fill=\"#ea985d\" stroke=\"#000000\" points=\"147,-68 0,-68 0,0 147,0 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          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ijsg7HB1QiGC"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pdZuAX5tQiDk",
        "outputId": "7d5d1db8-e188-4931-d2c3-404611fb23dd"
      },
      "source": [
        "model = RandomForestClassifier(max_depth=3)\n",
        "model.fit(X_train, y_train)"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,\n",
              "                       criterion='gini', max_depth=3, max_features='auto',\n",
              "                       max_leaf_nodes=None, max_samples=None,\n",
              "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
              "                       min_samples_leaf=1, min_samples_split=2,\n",
              "                       min_weight_fraction_leaf=0.0, n_estimators=100,\n",
              "                       n_jobs=None, oob_score=False, random_state=None,\n",
              "                       verbose=0, warm_start=False)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i13bVr1vR-R0",
        "outputId": "d97d79cd-1c7b-41d8-9f07-91b69f8a0d3b"
      },
      "source": [
        "importances = model.feature_importances_\n",
        "importances"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1.06132043e-02, 1.14134613e-03, 5.42843470e-03, 5.59219052e-03,\n",
              "       3.17105792e-05, 1.19895883e-02, 7.97586080e-02, 6.95496313e-03,\n",
              "       1.57138856e-01, 8.12174282e-04, 4.65015996e-02, 4.21463065e-01,\n",
              "       5.12493157e-03, 9.70176534e-02, 5.05244375e-02, 9.99072375e-02])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CpkPPltWSQl9",
        "outputId": "0e47ea79-3c25-4a74-90f8-14b91c2941fe"
      },
      "source": [
        "indices = np.argsort(importances)[::-1]\n",
        "indices"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([11,  8, 15, 13,  6, 14, 10,  5,  0,  7,  3,  2, 12,  1,  9,  4])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KpzfYWiLR-O7",
        "outputId": "dd80ac72-c36e-43ab-e8b1-054b17ef5785"
      },
      "source": [
        "columns = df.drop('y', axis=1).columns\n",
        "columns"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['age', 'job', 'marital', 'education', 'default', 'balance', 'housing',\n",
              "       'loan', 'contact', 'day', 'month', 'duration', 'campaign', 'pdays',\n",
              "       'previous', 'poutcome'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Dd8Fpb01R-MY",
        "outputId": "33d55c48-568e-41ee-f60f-9c389476f300"
      },
      "source": [
        "names = [columns[i] for i in indices]\n",
        "names"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['duration',\n",
              " 'contact',\n",
              " 'poutcome',\n",
              " 'pdays',\n",
              " 'housing',\n",
              " 'previous',\n",
              " 'month',\n",
              " 'balance',\n",
              " 'age',\n",
              " 'loan',\n",
              " 'education',\n",
              " 'marital',\n",
              " 'campaign',\n",
              " 'job',\n",
              " 'day',\n",
              " 'default']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 305
        },
        "id": "snF65rvER-J0",
        "outputId": "c16efac5-6691-40ab-8b67-0520b9e991d5"
      },
      "source": [
        "plt.figure(figsize=(8,4))\n",
        "plt.bar(names,np.sort(importances)[::-1])\n",
        "plt.xticks(rotation=90)\n",
        "plt.show()"
      ],
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    }
  ]
}