examples/demo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 安装\n",
    "\n",
    "## Python 2\n",
    "对于Python 2用户，因为有一些包的最新版不再支持Python 2，所以直接根据依赖来安装的话，会有版本错误的提示。需要提前按照好对应的依赖包：\n",
    "```\n",
    "pip install matplotlib==2.2.3\n",
    "pip install seaborn pandas sklearn\n",
    "pip install rosaceae\n",
    "```\n",
    "\n",
    "## Python 3 \n",
    "```\n",
    "pip install rosaceae\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# `rosaceae`使用示例   \n",
    "示例使用的数据集来自Kaggle上的一个项目[GiveMeSomeCredit](https://www.kaggle.com/c/GiveMeSomeCredit)。这个项目也是利用信用评分卡来对用户进行信用评估，下面也只是利用这些数据示范rosaceae的使用方法。\n",
    "使用到的文件一共有3个： \n",
    "+ cs-test.csv  测试数据集\n",
    "+ cs-training.csv  训练数据集\n",
    "+ Data Dictionary.xls  数据指标的说明 \n",
    "\n",
    "这里取了`cs-training.csv`文件前1000行数据用于介绍`rosaceae`的使用，完整数据可以去上面的项目链接下载。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 读取数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = pd.read_csv('cs-training-1000.csv', index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SeriousDlqin2yrs</th>\n",
       "      <th>RevolvingUtilizationOfUnsecuredLines</th>\n",
       "      <th>age</th>\n",
       "      <th>NumberOfTime30-59DaysPastDueNotWorse</th>\n",
       "      <th>DebtRatio</th>\n",
       "      <th>MonthlyIncome</th>\n",
       "      <th>NumberOfOpenCreditLinesAndLoans</th>\n",
       "      <th>NumberOfTimes90DaysLate</th>\n",
       "      <th>NumberRealEstateLoansOrLines</th>\n",
       "      <th>NumberOfTime60-89DaysPastDueNotWorse</th>\n",
       "      <th>NumberOfDependents</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0.766127</td>\n",
       "      <td>45</td>\n",
       "      <td>2</td>\n",
       "      <td>0.802982</td>\n",
       "      <td>9120.0</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0.957151</td>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "      <td>0.121876</td>\n",
       "      <td>2600.0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0.658180</td>\n",
       "      <td>38</td>\n",
       "      <td>1</td>\n",
       "      <td>0.085113</td>\n",
       "      <td>3042.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0.233810</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>0.036050</td>\n",
       "      <td>3300.0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0.907239</td>\n",
       "      <td>49</td>\n",
       "      <td>1</td>\n",
       "      <td>0.024926</td>\n",
       "      <td>63588.0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   SeriousDlqin2yrs  RevolvingUtilizationOfUnsecuredLines  age  \\\n",
       "0                 1                              0.766127   45   \n",
       "1                 0                              0.957151   40   \n",
       "2                 0                              0.658180   38   \n",
       "3                 0                              0.233810   30   \n",
       "4                 0                              0.907239   49   \n",
       "\n",
       "   NumberOfTime30-59DaysPastDueNotWorse  DebtRatio  MonthlyIncome  \\\n",
       "0                                     2   0.802982         9120.0   \n",
       "1                                     0   0.121876         2600.0   \n",
       "2                                     1   0.085113         3042.0   \n",
       "3                                     0   0.036050         3300.0   \n",
       "4                                     1   0.024926        63588.0   \n",
       "\n",
       "   NumberOfOpenCreditLinesAndLoans  NumberOfTimes90DaysLate  \\\n",
       "0                               13                        0   \n",
       "1                                4                        0   \n",
       "2                                2                        1   \n",
       "3                                5                        0   \n",
       "4                                7                        0   \n",
       "\n",
       "   NumberRealEstateLoansOrLines  NumberOfTime60-89DaysPastDueNotWorse  \\\n",
       "0                             6                                     0   \n",
       "1                             0                                     0   \n",
       "2                             0                                     0   \n",
       "3                             0                                     0   \n",
       "4                             1                                     0   \n",
       "\n",
       "   NumberOfDependents  \n",
       "0                 2.0  \n",
       "1                 1.0  \n",
       "2                 0.0  \n",
       "3                 0.0  \n",
       "4                 0.0  "
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "上面的测试数据中，`SeriousDlqin2yrs`是好坏用户的标记。根据`Data Dictionary.xls`文件中的解释，是指用户是否逾期90天，1表示逾期，0表示未逾期。其他列是用户的各个属性变量，变量所代表的含义参考`Data Dictionary.xls`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_info = pd.read_excel('Data Dictionary.xls')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Variable Name</th>\n",
       "      <th>Description</th>\n",
       "      <th>Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SeriousDlqin2yrs</td>\n",
       "      <td>Person experienced 90 days past due delinquenc...</td>\n",
       "      <td>Y/N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RevolvingUtilizationOfUnsecuredLines</td>\n",
       "      <td>Total balance on credit cards and personal lin...</td>\n",
       "      <td>percentage</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>age</td>\n",
       "      <td>Age of borrower in years</td>\n",
       "      <td>integer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NumberOfTime30-59DaysPastDueNotWorse</td>\n",
       "      <td>Number of times borrower has been 30-59 days p...</td>\n",
       "      <td>integer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DebtRatio</td>\n",
       "      <td>Monthly debt payments, alimony,living costs di...</td>\n",
       "      <td>percentage</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>MonthlyIncome</td>\n",
       "      <td>Monthly income</td>\n",
       "      <td>real</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NumberOfOpenCreditLinesAndLoans</td>\n",
       "      <td>Number of Open loans (installment like car loa...</td>\n",
       "      <td>integer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NumberOfTimes90DaysLate</td>\n",
       "      <td>Number of times borrower has been 90 days or m...</td>\n",
       "      <td>integer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>NumberRealEstateLoansOrLines</td>\n",
       "      <td>Number of mortgage and real estate loans inclu...</td>\n",
       "      <td>integer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NumberOfTime60-89DaysPastDueNotWorse</td>\n",
       "      <td>Number of times borrower has been 60-89 days p...</td>\n",
       "      <td>integer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>NumberOfDependents</td>\n",
       "      <td>Number of dependents in family excluding thems...</td>\n",
       "      <td>integer</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Variable Name  \\\n",
       "0                       SeriousDlqin2yrs   \n",
       "1   RevolvingUtilizationOfUnsecuredLines   \n",
       "2                                    age   \n",
       "3   NumberOfTime30-59DaysPastDueNotWorse   \n",
       "4                              DebtRatio   \n",
       "5                          MonthlyIncome   \n",
       "6        NumberOfOpenCreditLinesAndLoans   \n",
       "7                NumberOfTimes90DaysLate   \n",
       "8           NumberRealEstateLoansOrLines   \n",
       "9   NumberOfTime60-89DaysPastDueNotWorse   \n",
       "10                    NumberOfDependents   \n",
       "\n",
       "                                          Description        Type  \n",
       "0   Person experienced 90 days past due delinquenc...         Y/N  \n",
       "1   Total balance on credit cards and personal lin...  percentage  \n",
       "2                            Age of borrower in years     integer  \n",
       "3   Number of times borrower has been 30-59 days p...     integer  \n",
       "4   Monthly debt payments, alimony,living costs di...  percentage  \n",
       "5                                      Monthly income        real  \n",
       "6   Number of Open loans (installment like car loa...     integer  \n",
       "7   Number of times borrower has been 90 days or m...     integer  \n",
       "8   Number of mortgage and real estate loans inclu...     integer  \n",
       "9   Number of times borrower has been 60-89 days p...     integer  \n",
       "10  Number of dependents in family excluding thems...     integer  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(data_info)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这些变量可以简单划分成下面几类\n",
    "\n",
    "+ **基本属性：**age（年龄）\n",
    "+ **财产状况：**NumberOfOpenCreditLinesAndLoans（开放式贷款和信贷），NumberRealEstateLoansOrLines（不动产抵押贷款或房屋将会信贷额度）\n",
    "+ **信用状况：**NumberOfTimes90DaysLate（逾期>=90天），NumberOfTime60-89DaysPastDueNotWorse（逾期60-89天的次数），NumberOfTime30-59DaysPastDueNotWorse（逾期30-59天的次数）\n",
    "+ **偿还能力：**MonthlyIncome（月收入），DebtRatio（负债率）\n",
    "+ **其他因素：**NumberOfDependents（家属数量）\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 查看数据\n",
    "这里只是演示`rosaceae`的使用方法，并没有任何对数据做特征工程。  \n",
    "`summary`函数简单统计了各个指标的一些统计指标，对数据有一个快速的了解。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from rosaceae.utils import summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "summ = summary(train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Field</th>\n",
       "      <th>Type</th>\n",
       "      <th>Recs</th>\n",
       "      <th>Miss</th>\n",
       "      <th>Min</th>\n",
       "      <th>Q25</th>\n",
       "      <th>Q50</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SeriousDlqin2yrs</td>\n",
       "      <td>int64</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0570</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.2320</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RevolvingUtilizationOfUnsecuredLines</td>\n",
       "      <td>float64</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.03236</td>\n",
       "      <td>0.1597</td>\n",
       "      <td>4.7180</td>\n",
       "      <td>0.5334</td>\n",
       "      <td>2340.0</td>\n",
       "      <td>98.6500</td>\n",
       "      <td>865</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>age</td>\n",
       "      <td>int64</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>40.00000</td>\n",
       "      <td>52.0000</td>\n",
       "      <td>51.7900</td>\n",
       "      <td>62.2500</td>\n",
       "      <td>97.0</td>\n",
       "      <td>15.1700</td>\n",
       "      <td>71</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NumberOfTime30-59DaysPastDueNotWorse</td>\n",
       "      <td>int64</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.2660</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.7719</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DebtRatio</td>\n",
       "      <td>float64</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.16730</td>\n",
       "      <td>0.3604</td>\n",
       "      <td>353.8000</td>\n",
       "      <td>0.7505</td>\n",
       "      <td>15466.0</td>\n",
       "      <td>1168.0000</td>\n",
       "      <td>966</td>\n",
       "      <td>0</td>\n",
       "      <td>206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>MonthlyIncome</td>\n",
       "      <td>float64</td>\n",
       "      <td>1000</td>\n",
       "      <td>181</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3300.00000</td>\n",
       "      <td>5217.0000</td>\n",
       "      <td>6618.0000</td>\n",
       "      <td>8332.0000</td>\n",
       "      <td>208333.0</td>\n",
       "      <td>8818.0000</td>\n",
       "      <td>493</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NumberOfOpenCreditLinesAndLoans</td>\n",
       "      <td>int64</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.00000</td>\n",
       "      <td>8.0000</td>\n",
       "      <td>8.5230</td>\n",
       "      <td>11.0000</td>\n",
       "      <td>31.0</td>\n",
       "      <td>5.1690</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NumberOfTimes90DaysLate</td>\n",
       "      <td>int64</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0810</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.3723</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>NumberRealEstateLoansOrLines</td>\n",
       "      <td>int64</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0.9740</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.0190</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NumberOfTime60-89DaysPastDueNotWorse</td>\n",
       "      <td>int64</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0560</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.2949</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>NumberOfDependents</td>\n",
       "      <td>float64</td>\n",
       "      <td>1000</td>\n",
       "      <td>33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.7229</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0700</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   Field     Type  Recs Miss   Min  \\\n",
       "0                       SeriousDlqin2yrs    int64  1000    0   0.0   \n",
       "1   RevolvingUtilizationOfUnsecuredLines  float64  1000    0   0.0   \n",
       "2                                    age    int64  1000    0  22.0   \n",
       "3   NumberOfTime30-59DaysPastDueNotWorse    int64  1000    0   0.0   \n",
       "4                              DebtRatio  float64  1000    0   0.0   \n",
       "5                          MonthlyIncome  float64  1000  181   0.0   \n",
       "6        NumberOfOpenCreditLinesAndLoans    int64  1000    0   0.0   \n",
       "7                NumberOfTimes90DaysLate    int64  1000    0   0.0   \n",
       "8           NumberRealEstateLoansOrLines    int64  1000    0   0.0   \n",
       "9   NumberOfTime60-89DaysPastDueNotWorse    int64  1000    0   0.0   \n",
       "10                    NumberOfDependents  float64  1000   33   0.0   \n",
       "\n",
       "           Q25        Q50        Avg        Q75       Max       StDv Uniq  \\\n",
       "0      0.00000     0.0000     0.0570     0.0000       1.0     0.2320    2   \n",
       "1      0.03236     0.1597     4.7180     0.5334    2340.0    98.6500  865   \n",
       "2     40.00000    52.0000    51.7900    62.2500      97.0    15.1700   71   \n",
       "3      0.00000     0.0000     0.2660     0.0000      10.0     0.7719    8   \n",
       "4      0.16730     0.3604   353.8000     0.7505   15466.0  1168.0000  966   \n",
       "5   3300.00000  5217.0000  6618.0000  8332.0000  208333.0  8818.0000  493   \n",
       "6      5.00000     8.0000     8.5230    11.0000      31.0     5.1690   30   \n",
       "7      0.00000     0.0000     0.0810     0.0000       3.0     0.3723    4   \n",
       "8      0.00000     1.0000     0.9740     2.0000       8.0     1.0190    8   \n",
       "9      0.00000     0.0000     0.0560     0.0000       5.0     0.2949    4   \n",
       "10     0.00000     0.0000     0.7229     1.0000       6.0     1.0700    8   \n",
       "\n",
       "   OutLo OutHi  \n",
       "0      0    57  \n",
       "1      0     5  \n",
       "2      0     1  \n",
       "3      0   161  \n",
       "4      0   206  \n",
       "5      0    35  \n",
       "6      0    30  \n",
       "7      0    55  \n",
       "8      0     2  \n",
       "9      0    45  \n",
       "10     0    78  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summ"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Field', 'Type', 'Recs', 'Miss', 'Min', 'Q25', 'Q50', 'Avg', 'Q75',\n",
       "       'Max', 'StDv', 'Uniq', 'OutLo', 'OutHi'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summ.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1000, 11)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "结果中各列的说明可以参考函数的帮助信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function summary in module rosaceae.utils:\n",
      "\n",
      "summary(data, verbose=False)\n",
      "    Generates descriptive statistics for a dataset\n",
      "    \n",
      "    Generates descriptive statistics that summarize the central tendency,\n",
      "    dispersion and shape of a dataset's distribution. When data is categorious \n",
      "    or datatime format, some statistics values will be replaced by NA. \n",
      "    \n",
      "    Parameters\n",
      "    ----------\n",
      "    data : pandas data frame\n",
      "    verbose : True or False\n",
      "            Print verbose message, default is False.\n",
      "    \n",
      "    Returns\n",
      "    -------\n",
      "    A pandas data frame with statistics values for each column.\n",
      "    Field: Field name.\n",
      "    Type: object, numeric, integer, other.\n",
      "    Recs: Number of records.\n",
      "    Miss: Number of missing records.\n",
      "    Min: Minimum value.\n",
      "    Q25: First quartile. It splits off the lowest 25\\% of data from the highest 75\\%.\n",
      "    Q50: Median or second quartile. It cuts data set in half.\n",
      "    Avg: Average value.\n",
      "    Q75: Third quartile. It splits off the lowest 75\\% of data from the highest 25\\%.\n",
      "    Max: Maximum value.\n",
      "    StDv: Standard deviation of a sample.\n",
      "    Neg: Number of negative values.\n",
      "    Pos: Number of positive values.\n",
      "    OutLo: Number of outliers. Records below Q25-1.5*IQR, where IQR=Q75-Q25. \n",
      "    OutHi: Number of outliers. Records above Q75+1.5*IQR, where IQR=Q75-Q25.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(summary)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据分箱  \n",
    "\n",
    "在`rosaceae.bins`中提供一些常见的分箱方法：\n",
    "\n",
    "+ `bin_distince`，按照步长进行划分分箱，适用数值型变量  \n",
    "+ `bin_frequency`，按照等频分箱，适用数值型变量  \n",
    "+ `bin_tree`，决策树分箱，利用`sklearn`中的决策树分类模型，适用于数值变量 \n",
    "+ `bin_chi2`，卡方分箱，适用数值和类别型变量  \n",
    "+ `bin_custom`，自定义分箱，按照自定义的分箱标准进行划分，适用于数值和类别型变量   \n",
    "\n",
    "在上面的分箱方法中，有`na_omit`参数来对缺失的数据进行处理，设为`False`时将保留缺失数据并放到单独的Miss分箱，若为`True`，则将缺失数据去除，同时对应的好坏用户数据也会去除。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "from rosaceae.bins import bin_distance, bin_frequency, bin_tree, bin_chi2, bin_custom"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### bin_distance\n",
    "\n",
    "以月收入MonthlyIncome 指标来进行测试，先进行等距分箱，这里是按照分箱的数目，数据中的最大值和最小值，把数据分成距离相等的几个分箱。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 分成5个箱,缺失值另外为个分组， 返回一个字典，包括对应的分箱区间和对应的数据索引\n",
    "# na_omit 为True，将把缺失值部分去掉。\n",
    "mon_dis = bin_distance(train['MonthlyIncome'], 5, na_omit=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['[166666.4,inf)', '[-inf,41666.6)', 'Miss', '[83333.2,124999.79999999999)', '[41666.6,83333.2)', '[124999.79999999999,166666.4)'])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mon_dis.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Distance: 41666.6\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "dict_keys(['[83333.2,124999.79999999999)', '[166666.4,inf)', '[41666.6,83333.2)', '[-inf,41666.6)', '[124999.79999999999,166666.4)'])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bin_distance(train['MonthlyIncome'], 5, na_omit=True, verbose=True).keys()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### bin_frequency\n",
    "\n",
    "等频分箱先将数据从小到大排序，按照给定的分箱数，将数据放入到每个分箱中，每个分箱中的元素个数是接近的。如果将缺失单独为一分箱，那会将剩下的数据按照分箱数进行划分。如果将缺失数据排除，那会把排除后的数据分成对应的几个分箱。最后一个分箱的数目可能与其他分箱有差距，这是因为不能整除的问题，所以把剩下的数据放到最后的一个分箱中。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Step: 163\n",
      "Freq1 163\n",
      "Freq2 163\n",
      "Freq3 163\n",
      "Freq4 163\n",
      "Freq5 167\n",
      "Miss 181\n"
     ]
    }
   ],
   "source": [
    "mon_freq = bin_frequency(train['MonthlyIncome'], 5, na_omit=False, verbose=True)\n",
    "\n",
    "for k in sorted(mon_freq.keys()):\n",
    "    print(k, len(mon_freq[k]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Step: 163\n",
      "Freq1 163\n",
      "Freq2 163\n",
      "Freq3 163\n",
      "Freq4 163\n",
      "Freq5 167\n"
     ]
    }
   ],
   "source": [
    "mon_freq = bin_frequency(train['MonthlyIncome'], 5, na_omit=True, verbose=True)\n",
    "\n",
    "for k in sorted(mon_freq.keys()):\n",
    "    print(k, len(mon_freq[k]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### bin_tree  \n",
    "\n",
    "决策树分箱是利用`sklearn`中的[`DecisionTreeClassifier`分类函数](https://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeClassifier.html)。使用到的一些参数设置如下：\n",
    "\n",
    "```python\n",
    "clf = DecisionTreeClassifier(random_state=0, \n",
    "                                criterion='entropy',\n",
    "                                min_samples_split=0.2,\n",
    "                                max_leaf_nodes=6, \n",
    "                                min_impurity_decrease=0.001,\n",
    "                                **kwargs)\n",
    "```\n",
    "\n",
    "如果还需要设置其他参数，可以通过`**kwargs`进行设置。决策树会根据数据划分叶子节点，我们会把相应的节点信息记录下来。关于决策树的的节点信息可以参考[]()。如果某个叶子节点中的数据占比小于`min_samples_node`设置的阈值，会将该节点合并回父节点上。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[6202.0:7480.0) 75\n",
      "[-inf:1702.5) 62\n",
      "[1702.5:6202.0) 428\n",
      "[7480.0:inf) 254\n"
     ]
    }
   ],
   "source": [
    "mon_tree = bin_tree(train['MonthlyIncome'], train['SeriousDlqin2yrs'], na_omit=True)\n",
    "\n",
    "for k in mon_tree.keys():\n",
    "    print(k, len(mon_tree[k]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[6202.0:7480.0) 75\n",
      "[-inf:1702.5) 62\n",
      "Miss 181\n",
      "[1702.5:6202.0) 428\n",
      "[7480.0:inf) 254\n"
     ]
    }
   ],
   "source": [
    "mon_tree = bin_tree(train['MonthlyIncome'], train['SeriousDlqin2yrs'], na_omit=False)\n",
    "\n",
    "for k in mon_tree.keys():\n",
    "    print(k, len(mon_tree[k]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### bin_custom\n",
    "\n",
    "自定义分箱可以按照提供的区间进行分箱。`groups`参数接受自定义区间，类别型变量的的输入形式类似：`groups=['A', 'B', ('C', 'D')]`，如果多个类别想放到一个分箱中，可以使将多个类别放到元组中。数值型变量的输入形式类似：`groups=['(-inf:4]', '(4:10]', (10:inf)']`，这里第一个和最后一个是分界是包括了无穷大的。 是否保存缺失数据使用的参数是`na_omit`，设置为`True`将去除缺失，`False`将缺失单独分组。  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Keep NA data\n",
      "Missing data: 0\n",
      "* Handling (-inf:40]\n",
      "* Handling (40:50]\n",
      "* Handling [50:60)\n",
      "* Handling [60:inf)\n",
      "(40:50] 199\n",
      "[60:inf) 301\n",
      "(-inf:40] 275\n",
      "[50:60) 246\n"
     ]
    }
   ],
   "source": [
    "age_cus = bin_custom(train['age'], groups=['(-inf:40]', '(40:50]', '[50:60)', '[60:inf)'], na_omit=False, verbose=True)\n",
    "\n",
    "for k in age_cus.keys():\n",
    "    print(k, len(age_cus[k]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    943\n",
       "1     57\n",
       "Name: SeriousDlqin2yrs, dtype: int64"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train['SeriousDlqin2yrs'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('0',) 943\n",
      "('1',) 57\n"
     ]
    }
   ],
   "source": [
    "label_cus = bin_custom(train['SeriousDlqin2yrs'], groups=['1','0'])\n",
    "\n",
    "for k in label_cus.keys():\n",
    "    print(k, len(label_cus[k]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## WOE和IV的计算\n",
    "WOE和IV的计算是使用了`rosaceae.scorecard`的`woe_iv`函数。该函数可以同时处理多个变量或单个变量的WOE和IV值，将相应的结果以DataFrame的格式返回。  \n",
    "使用时需要提前对变量进行分箱，把变量的分箱结果保存在字典中，以对应的变量为键，分箱结果为值。   \n",
    "也可以提供需要计算WOE和IV的变量名组成的列表，不过这些变量中数值型的箱是使用决策树进行分箱的，类型型的变量按照不同类别进行分类。  \n",
    "\n",
    "如果将变量的分箱数据保存在字典 bin_info 中\n",
    "```python\n",
    "\n",
    "bin_info = {'age': bins_result，  # bins 中分箱函数的结果\n",
    "            'MonthlyIncome':['(-inf:3000]', '(3000:5000]', '(5000:8500]', '[8500:inf)'],  # 自定义的数值分箱区间\n",
    "           'NumberOfOpenCreditLinesAndLoans' : [], # 提供一个空列表，说明没有提供相关的分箱信息\n",
    "                                                   # 将会按照默认的分箱方法进行处理\n",
    "            ...\n",
    "           }\n",
    "```\n",
    "\n",
    "对于缺失数据的处理，`na_omit`参数只对bin_info中没有提分箱信息用的变量才会生效。`[]`是说明该变量没有提供相关的分箱信息。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count       819.000000\n",
       "mean       6617.976801\n",
       "std        8818.220170\n",
       "min           0.000000\n",
       "25%        3300.000000\n",
       "50%        5217.000000\n",
       "75%        8332.500000\n",
       "max      208333.000000\n",
       "Name: MonthlyIncome, dtype: float64"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train['MonthlyIncome'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "from rosaceae.scorecard import woe_iv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "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>Variable</th>\n",
       "      <th>Bin</th>\n",
       "      <th>Good</th>\n",
       "      <th>Bad</th>\n",
       "      <th>pnt_0</th>\n",
       "      <th>pnt_1</th>\n",
       "      <th>WOE</th>\n",
       "      <th>IV_i</th>\n",
       "      <th>IV</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>age</td>\n",
       "      <td>[-inf:36.5)</td>\n",
       "      <td>180</td>\n",
       "      <td>9</td>\n",
       "      <td>0.19088</td>\n",
       "      <td>0.157895</td>\n",
       "      <td>-0.189717</td>\n",
       "      <td>0.00625791</td>\n",
       "      <td>0.423641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>age</td>\n",
       "      <td>[36.5:51.5)</td>\n",
       "      <td>276</td>\n",
       "      <td>31</td>\n",
       "      <td>0.292683</td>\n",
       "      <td>0.54386</td>\n",
       "      <td>0.619601</td>\n",
       "      <td>0.155629</td>\n",
       "      <td>0.423641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>age</td>\n",
       "      <td>[51.5:57.5)</td>\n",
       "      <td>148</td>\n",
       "      <td>3</td>\n",
       "      <td>0.156946</td>\n",
       "      <td>0.0526316</td>\n",
       "      <td>-1.09258</td>\n",
       "      <td>0.113972</td>\n",
       "      <td>0.423641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>age</td>\n",
       "      <td>[57.5:63.5)</td>\n",
       "      <td>125</td>\n",
       "      <td>10</td>\n",
       "      <td>0.132556</td>\n",
       "      <td>0.175439</td>\n",
       "      <td>0.280286</td>\n",
       "      <td>0.0120195</td>\n",
       "      <td>0.423641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>age</td>\n",
       "      <td>[63.5:67.5)</td>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0593849</td>\n",
       "      <td>0.0175439</td>\n",
       "      <td>-1.21934</td>\n",
       "      <td>0.0510184</td>\n",
       "      <td>0.423641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>age</td>\n",
       "      <td>[67.5:inf)</td>\n",
       "      <td>158</td>\n",
       "      <td>4</td>\n",
       "      <td>0.16755</td>\n",
       "      <td>0.0701754</td>\n",
       "      <td>-0.870286</td>\n",
       "      <td>0.084744</td>\n",
       "      <td>0.423641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>MonthlyIncome</td>\n",
       "      <td>[-inf:1702.5)</td>\n",
       "      <td>61</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0646872</td>\n",
       "      <td>0.0175439</td>\n",
       "      <td>-1.30486</td>\n",
       "      <td>0.0615154</td>\n",
       "      <td>0.244331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>MonthlyIncome</td>\n",
       "      <td>[1702.5:6202.0)</td>\n",
       "      <td>393</td>\n",
       "      <td>35</td>\n",
       "      <td>0.416755</td>\n",
       "      <td>0.614035</td>\n",
       "      <td>0.387553</td>\n",
       "      <td>0.0764566</td>\n",
       "      <td>0.244331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>MonthlyIncome</td>\n",
       "      <td>[6202.0:7480.0)</td>\n",
       "      <td>75</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0795334</td>\n",
       "      <td>0.0175439</td>\n",
       "      <td>-1.51147</td>\n",
       "      <td>0.0936955</td>\n",
       "      <td>0.244331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>MonthlyIncome</td>\n",
       "      <td>[7480.0:inf)</td>\n",
       "      <td>242</td>\n",
       "      <td>12</td>\n",
       "      <td>0.256628</td>\n",
       "      <td>0.210526</td>\n",
       "      <td>-0.198016</td>\n",
       "      <td>0.00912883</td>\n",
       "      <td>0.244331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>MonthlyIncome</td>\n",
       "      <td>Miss</td>\n",
       "      <td>172</td>\n",
       "      <td>9</td>\n",
       "      <td>0.182397</td>\n",
       "      <td>0.157895</td>\n",
       "      <td>-0.144255</td>\n",
       "      <td>0.00353451</td>\n",
       "      <td>0.244331</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Variable              Bin Good Bad      pnt_0      pnt_1       WOE  \\\n",
       "0             age      [-inf:36.5)  180   9    0.19088   0.157895 -0.189717   \n",
       "1             age      [36.5:51.5)  276  31   0.292683    0.54386  0.619601   \n",
       "2             age      [51.5:57.5)  148   3   0.156946  0.0526316  -1.09258   \n",
       "3             age      [57.5:63.5)  125  10   0.132556   0.175439  0.280286   \n",
       "4             age      [63.5:67.5)   56   1  0.0593849  0.0175439  -1.21934   \n",
       "5             age       [67.5:inf)  158   4    0.16755  0.0701754 -0.870286   \n",
       "6   MonthlyIncome    [-inf:1702.5)   61   1  0.0646872  0.0175439  -1.30486   \n",
       "7   MonthlyIncome  [1702.5:6202.0)  393  35   0.416755   0.614035  0.387553   \n",
       "8   MonthlyIncome  [6202.0:7480.0)   75   1  0.0795334  0.0175439  -1.51147   \n",
       "9   MonthlyIncome     [7480.0:inf)  242  12   0.256628   0.210526 -0.198016   \n",
       "10  MonthlyIncome             Miss  172   9   0.182397   0.157895 -0.144255   \n",
       "\n",
       "          IV_i        IV  \n",
       "0   0.00625791  0.423641  \n",
       "1     0.155629  0.423641  \n",
       "2     0.113972  0.423641  \n",
       "3    0.0120195  0.423641  \n",
       "4    0.0510184  0.423641  \n",
       "5     0.084744  0.423641  \n",
       "6    0.0615154  0.244331  \n",
       "7    0.0764566  0.244331  \n",
       "8    0.0936955  0.244331  \n",
       "9   0.00912883  0.244331  \n",
       "10  0.00353451  0.244331  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 只是提供变量名列表的话，会按照默认的分箱方法进行分箱并计算woe和iv。\n",
    "woe_iv(train, 'SeriousDlqin2yrs', var=['age', 'MonthlyIncome'], na_omit=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "bin_info = {'age': bin_tree(train['age'], train['SeriousDlqin2yrs'], na_omit=False),\n",
    "            'MonthlyIncome':['(-inf:3000]', '(3000:5000]', '(5000:8500]', '[8500:inf)', 'Miss'],\n",
    "           'RevolvingUtilizationOfUnsecuredLines':[], # 其他变量就按照默认的处理方法好了\n",
    "           'NumberOfTime30-59DaysPastDueNotWorse':[],\n",
    "           'DebtRatio':[], \n",
    "           'NumberOfOpenCreditLinesAndLoans':[],\n",
    "           'NumberOfTimes90DaysLate':[],\n",
    "           'NumberRealEstateLoansOrLines':[],\n",
    "           'NumberOfTime60-89DaysPastDueNotWorse':[],\n",
    "           'NumberOfDependents':[]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "woe_df = woe_iv(train, 'SeriousDlqin2yrs', var=bin_info, na_omit=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "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>Variable</th>\n",
       "      <th>Bin</th>\n",
       "      <th>Good</th>\n",
       "      <th>Bad</th>\n",
       "      <th>pnt_0</th>\n",
       "      <th>pnt_1</th>\n",
       "      <th>WOE</th>\n",
       "      <th>IV_i</th>\n",
       "      <th>IV</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>RevolvingUtilizationOfUnsecuredLines</td>\n",
       "      <td>[-inf:0.2302175909280777)</td>\n",
       "      <td>562</td>\n",
       "      <td>12</td>\n",
       "      <td>0.59597</td>\n",
       "      <td>0.210526</td>\n",
       "      <td>-1.04058</td>\n",
       "      <td>0.401085</td>\n",
       "      <td>1.251684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RevolvingUtilizationOfUnsecuredLines</td>\n",
       "      <td>[0.2302175909280777:0.3137817233800888)</td>\n",
       "      <td>66</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0699894</td>\n",
       "      <td>0.0175439</td>\n",
       "      <td>-1.38364</td>\n",
       "      <td>0.0725657</td>\n",
       "      <td>1.251684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>RevolvingUtilizationOfUnsecuredLines</td>\n",
       "      <td>[0.3137817233800888:0.6355679929256439)</td>\n",
       "      <td>140</td>\n",
       "      <td>8</td>\n",
       "      <td>0.148462</td>\n",
       "      <td>0.140351</td>\n",
       "      <td>-0.0561859</td>\n",
       "      <td>0.00045575</td>\n",
       "      <td>1.251684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>RevolvingUtilizationOfUnsecuredLines</td>\n",
       "      <td>[0.6355679929256439:1.003534197807312)</td>\n",
       "      <td>168</td>\n",
       "      <td>28</td>\n",
       "      <td>0.178155</td>\n",
       "      <td>0.491228</td>\n",
       "      <td>1.01426</td>\n",
       "      <td>0.317536</td>\n",
       "      <td>1.251684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RevolvingUtilizationOfUnsecuredLines</td>\n",
       "      <td>[1.003534197807312:inf)</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "      <td>0.00742312</td>\n",
       "      <td>0.157895</td>\n",
       "      <td>3.05733</td>\n",
       "      <td>0.460041</td>\n",
       "      <td>1.251684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NumberOfTime60-89DaysPastDueNotWorse</td>\n",
       "      <td>[-inf:0.5)</td>\n",
       "      <td>913</td>\n",
       "      <td>42</td>\n",
       "      <td>0.968187</td>\n",
       "      <td>0.736842</td>\n",
       "      <td>-0.273051</td>\n",
       "      <td>0.0631689</td>\n",
       "      <td>0.551969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NumberOfTime60-89DaysPastDueNotWorse</td>\n",
       "      <td>[0.5:inf)</td>\n",
       "      <td>30</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0318134</td>\n",
       "      <td>0.263158</td>\n",
       "      <td>2.11287</td>\n",
       "      <td>0.4888</td>\n",
       "      <td>0.551969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>DebtRatio</td>\n",
       "      <td>[-inf:0.12926051020622253)</td>\n",
       "      <td>198</td>\n",
       "      <td>3</td>\n",
       "      <td>0.209968</td>\n",
       "      <td>0.0526316</td>\n",
       "      <td>-1.38364</td>\n",
       "      <td>0.217697</td>\n",
       "      <td>0.487792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DebtRatio</td>\n",
       "      <td>[0.12926051020622253:0.4607849717140198)</td>\n",
       "      <td>382</td>\n",
       "      <td>21</td>\n",
       "      <td>0.40509</td>\n",
       "      <td>0.368421</td>\n",
       "      <td>-0.0948832</td>\n",
       "      <td>0.00347928</td>\n",
       "      <td>0.487792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>DebtRatio</td>\n",
       "      <td>[0.4607849717140198:1.7644871473312378)</td>\n",
       "      <td>167</td>\n",
       "      <td>23</td>\n",
       "      <td>0.177094</td>\n",
       "      <td>0.403509</td>\n",
       "      <td>0.823515</td>\n",
       "      <td>0.186456</td>\n",
       "      <td>0.487792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>DebtRatio</td>\n",
       "      <td>[1.7644871473312378:3219.5)</td>\n",
       "      <td>170</td>\n",
       "      <td>6</td>\n",
       "      <td>0.180276</td>\n",
       "      <td>0.105263</td>\n",
       "      <td>-0.538024</td>\n",
       "      <td>0.0403586</td>\n",
       "      <td>0.487792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>DebtRatio</td>\n",
       "      <td>[3219.5:inf)</td>\n",
       "      <td>26</td>\n",
       "      <td>4</td>\n",
       "      <td>0.0275716</td>\n",
       "      <td>0.0701754</td>\n",
       "      <td>0.934213</td>\n",
       "      <td>0.0398011</td>\n",
       "      <td>0.487792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>NumberOfTime30-59DaysPastDueNotWorse</td>\n",
       "      <td>[-inf:0.5)</td>\n",
       "      <td>807</td>\n",
       "      <td>32</td>\n",
       "      <td>0.855779</td>\n",
       "      <td>0.561404</td>\n",
       "      <td>-0.421573</td>\n",
       "      <td>0.124101</td>\n",
       "      <td>0.451516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>NumberOfTime30-59DaysPastDueNotWorse</td>\n",
       "      <td>[0.5:inf)</td>\n",
       "      <td>136</td>\n",
       "      <td>25</td>\n",
       "      <td>0.144221</td>\n",
       "      <td>0.438596</td>\n",
       "      <td>1.11224</td>\n",
       "      <td>0.327415</td>\n",
       "      <td>0.451516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>age</td>\n",
       "      <td>[-inf:36.5)</td>\n",
       "      <td>180</td>\n",
       "      <td>9</td>\n",
       "      <td>0.19088</td>\n",
       "      <td>0.157895</td>\n",
       "      <td>-0.189717</td>\n",
       "      <td>0.00625791</td>\n",
       "      <td>0.423641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>age</td>\n",
       "      <td>[36.5:51.5)</td>\n",
       "      <td>276</td>\n",
       "      <td>31</td>\n",
       "      <td>0.292683</td>\n",
       "      <td>0.54386</td>\n",
       "      <td>0.619601</td>\n",
       "      <td>0.155629</td>\n",
       "      <td>0.423641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>age</td>\n",
       "      <td>[51.5:57.5)</td>\n",
       "      <td>148</td>\n",
       "      <td>3</td>\n",
       "      <td>0.156946</td>\n",
       "      <td>0.0526316</td>\n",
       "      <td>-1.09258</td>\n",
       "      <td>0.113972</td>\n",
       "      <td>0.423641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>age</td>\n",
       "      <td>[57.5:63.5)</td>\n",
       "      <td>125</td>\n",
       "      <td>10</td>\n",
       "      <td>0.132556</td>\n",
       "      <td>0.175439</td>\n",
       "      <td>0.280286</td>\n",
       "      <td>0.0120195</td>\n",
       "      <td>0.423641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>age</td>\n",
       "      <td>[63.5:67.5)</td>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0593849</td>\n",
       "      <td>0.0175439</td>\n",
       "      <td>-1.21934</td>\n",
       "      <td>0.0510184</td>\n",
       "      <td>0.423641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>age</td>\n",
       "      <td>[67.5:inf)</td>\n",
       "      <td>158</td>\n",
       "      <td>4</td>\n",
       "      <td>0.16755</td>\n",
       "      <td>0.0701754</td>\n",
       "      <td>-0.870286</td>\n",
       "      <td>0.084744</td>\n",
       "      <td>0.423641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>NumberOfTimes90DaysLate</td>\n",
       "      <td>[-inf:0.5)</td>\n",
       "      <td>900</td>\n",
       "      <td>45</td>\n",
       "      <td>0.954401</td>\n",
       "      <td>0.789474</td>\n",
       "      <td>-0.189717</td>\n",
       "      <td>0.0312895</td>\n",
       "      <td>0.365948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>NumberOfTimes90DaysLate</td>\n",
       "      <td>[0.5:1.5)</td>\n",
       "      <td>31</td>\n",
       "      <td>4</td>\n",
       "      <td>0.0328738</td>\n",
       "      <td>0.0701754</td>\n",
       "      <td>0.758322</td>\n",
       "      <td>0.0282867</td>\n",
       "      <td>0.365948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>NumberOfTimes90DaysLate</td>\n",
       "      <td>[1.5:inf)</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>0.0127253</td>\n",
       "      <td>0.140351</td>\n",
       "      <td>2.40055</td>\n",
       "      <td>0.306371</td>\n",
       "      <td>0.365948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>NumberOfDependents</td>\n",
       "      <td>[-inf:0.5)</td>\n",
       "      <td>559</td>\n",
       "      <td>21</td>\n",
       "      <td>0.592789</td>\n",
       "      <td>0.368421</td>\n",
       "      <td>-0.475612</td>\n",
       "      <td>0.106712</td>\n",
       "      <td>0.237358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>NumberOfDependents</td>\n",
       "      <td>[0.5:inf)</td>\n",
       "      <td>352</td>\n",
       "      <td>35</td>\n",
       "      <td>0.373277</td>\n",
       "      <td>0.614035</td>\n",
       "      <td>0.497732</td>\n",
       "      <td>0.119833</td>\n",
       "      <td>0.237358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>NumberOfDependents</td>\n",
       "      <td>Miss</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0339343</td>\n",
       "      <td>0.0175439</td>\n",
       "      <td>-0.659721</td>\n",
       "      <td>0.0108131</td>\n",
       "      <td>0.237358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>NumberOfOpenCreditLinesAndLoans</td>\n",
       "      <td>[-inf:10.5)</td>\n",
       "      <td>677</td>\n",
       "      <td>31</td>\n",
       "      <td>0.717922</td>\n",
       "      <td>0.54386</td>\n",
       "      <td>-0.277669</td>\n",
       "      <td>0.0483316</td>\n",
       "      <td>0.223575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>NumberOfOpenCreditLinesAndLoans</td>\n",
       "      <td>[10.5:17.5)</td>\n",
       "      <td>207</td>\n",
       "      <td>20</td>\n",
       "      <td>0.219512</td>\n",
       "      <td>0.350877</td>\n",
       "      <td>0.469028</td>\n",
       "      <td>0.0616139</td>\n",
       "      <td>0.223575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>NumberOfOpenCreditLinesAndLoans</td>\n",
       "      <td>[17.5:18.5)</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0127253</td>\n",
       "      <td>0.0175439</td>\n",
       "      <td>0.321108</td>\n",
       "      <td>0.00154727</td>\n",
       "      <td>0.223575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>NumberOfOpenCreditLinesAndLoans</td>\n",
       "      <td>[18.5:20.5)</td>\n",
       "      <td>18</td>\n",
       "      <td>5</td>\n",
       "      <td>0.019088</td>\n",
       "      <td>0.0877193</td>\n",
       "      <td>1.52508</td>\n",
       "      <td>0.104668</td>\n",
       "      <td>0.223575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>NumberOfOpenCreditLinesAndLoans</td>\n",
       "      <td>[20.5:inf)</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0307529</td>\n",
       "      <td>0.0175439</td>\n",
       "      <td>-0.561281</td>\n",
       "      <td>0.00741399</td>\n",
       "      <td>0.223575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>NumberRealEstateLoansOrLines</td>\n",
       "      <td>[-inf:0.5)</td>\n",
       "      <td>363</td>\n",
       "      <td>21</td>\n",
       "      <td>0.384942</td>\n",
       "      <td>0.368421</td>\n",
       "      <td>-0.0438654</td>\n",
       "      <td>0.000724683</td>\n",
       "      <td>0.208901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>NumberRealEstateLoansOrLines</td>\n",
       "      <td>[0.5:1.5)</td>\n",
       "      <td>341</td>\n",
       "      <td>12</td>\n",
       "      <td>0.361612</td>\n",
       "      <td>0.210526</td>\n",
       "      <td>-0.540961</td>\n",
       "      <td>0.0817314</td>\n",
       "      <td>0.208901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>NumberRealEstateLoansOrLines</td>\n",
       "      <td>[1.5:2.5)</td>\n",
       "      <td>187</td>\n",
       "      <td>15</td>\n",
       "      <td>0.198303</td>\n",
       "      <td>0.263158</td>\n",
       "      <td>0.282957</td>\n",
       "      <td>0.018351</td>\n",
       "      <td>0.208901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>NumberRealEstateLoansOrLines</td>\n",
       "      <td>[2.5:inf)</td>\n",
       "      <td>52</td>\n",
       "      <td>9</td>\n",
       "      <td>0.0551432</td>\n",
       "      <td>0.157895</td>\n",
       "      <td>1.052</td>\n",
       "      <td>0.108094</td>\n",
       "      <td>0.208901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>MonthlyIncome</td>\n",
       "      <td>(-inf:3000]</td>\n",
       "      <td>162</td>\n",
       "      <td>12</td>\n",
       "      <td>0.171792</td>\n",
       "      <td>0.210526</td>\n",
       "      <td>0.203325</td>\n",
       "      <td>0.00787564</td>\n",
       "      <td>0.067619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>MonthlyIncome</td>\n",
       "      <td>(3000:5000]</td>\n",
       "      <td>207</td>\n",
       "      <td>17</td>\n",
       "      <td>0.219512</td>\n",
       "      <td>0.298246</td>\n",
       "      <td>0.30651</td>\n",
       "      <td>0.0241325</td>\n",
       "      <td>0.067619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>MonthlyIncome</td>\n",
       "      <td>(5000:8500]</td>\n",
       "      <td>221</td>\n",
       "      <td>9</td>\n",
       "      <td>0.234358</td>\n",
       "      <td>0.157895</td>\n",
       "      <td>-0.394923</td>\n",
       "      <td>0.0301973</td>\n",
       "      <td>0.067619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>MonthlyIncome</td>\n",
       "      <td>[8500:inf)</td>\n",
       "      <td>183</td>\n",
       "      <td>10</td>\n",
       "      <td>0.194062</td>\n",
       "      <td>0.175439</td>\n",
       "      <td>-0.100886</td>\n",
       "      <td>0.00187879</td>\n",
       "      <td>0.067619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>MonthlyIncome</td>\n",
       "      <td>Miss</td>\n",
       "      <td>172</td>\n",
       "      <td>9</td>\n",
       "      <td>0.182397</td>\n",
       "      <td>0.157895</td>\n",
       "      <td>-0.144255</td>\n",
       "      <td>0.00353451</td>\n",
       "      <td>0.067619</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Variable  \\\n",
       "0   RevolvingUtilizationOfUnsecuredLines   \n",
       "1   RevolvingUtilizationOfUnsecuredLines   \n",
       "2   RevolvingUtilizationOfUnsecuredLines   \n",
       "3   RevolvingUtilizationOfUnsecuredLines   \n",
       "4   RevolvingUtilizationOfUnsecuredLines   \n",
       "5   NumberOfTime60-89DaysPastDueNotWorse   \n",
       "6   NumberOfTime60-89DaysPastDueNotWorse   \n",
       "7                              DebtRatio   \n",
       "8                              DebtRatio   \n",
       "9                              DebtRatio   \n",
       "10                             DebtRatio   \n",
       "11                             DebtRatio   \n",
       "12  NumberOfTime30-59DaysPastDueNotWorse   \n",
       "13  NumberOfTime30-59DaysPastDueNotWorse   \n",
       "14                                   age   \n",
       "15                                   age   \n",
       "16                                   age   \n",
       "17                                   age   \n",
       "18                                   age   \n",
       "19                                   age   \n",
       "20               NumberOfTimes90DaysLate   \n",
       "21               NumberOfTimes90DaysLate   \n",
       "22               NumberOfTimes90DaysLate   \n",
       "23                    NumberOfDependents   \n",
       "24                    NumberOfDependents   \n",
       "25                    NumberOfDependents   \n",
       "26       NumberOfOpenCreditLinesAndLoans   \n",
       "27       NumberOfOpenCreditLinesAndLoans   \n",
       "28       NumberOfOpenCreditLinesAndLoans   \n",
       "29       NumberOfOpenCreditLinesAndLoans   \n",
       "30       NumberOfOpenCreditLinesAndLoans   \n",
       "31          NumberRealEstateLoansOrLines   \n",
       "32          NumberRealEstateLoansOrLines   \n",
       "33          NumberRealEstateLoansOrLines   \n",
       "34          NumberRealEstateLoansOrLines   \n",
       "35                         MonthlyIncome   \n",
       "36                         MonthlyIncome   \n",
       "37                         MonthlyIncome   \n",
       "38                         MonthlyIncome   \n",
       "39                         MonthlyIncome   \n",
       "\n",
       "                                         Bin Good Bad       pnt_0      pnt_1  \\\n",
       "0                  [-inf:0.2302175909280777)  562  12     0.59597   0.210526   \n",
       "1    [0.2302175909280777:0.3137817233800888)   66   1   0.0699894  0.0175439   \n",
       "2    [0.3137817233800888:0.6355679929256439)  140   8    0.148462   0.140351   \n",
       "3     [0.6355679929256439:1.003534197807312)  168  28    0.178155   0.491228   \n",
       "4                    [1.003534197807312:inf)    7   9  0.00742312   0.157895   \n",
       "5                                 [-inf:0.5)  913  42    0.968187   0.736842   \n",
       "6                                  [0.5:inf)   30  15   0.0318134   0.263158   \n",
       "7                 [-inf:0.12926051020622253)  198   3    0.209968  0.0526316   \n",
       "8   [0.12926051020622253:0.4607849717140198)  382  21     0.40509   0.368421   \n",
       "9    [0.4607849717140198:1.7644871473312378)  167  23    0.177094   0.403509   \n",
       "10               [1.7644871473312378:3219.5)  170   6    0.180276   0.105263   \n",
       "11                              [3219.5:inf)   26   4   0.0275716  0.0701754   \n",
       "12                                [-inf:0.5)  807  32    0.855779   0.561404   \n",
       "13                                 [0.5:inf)  136  25    0.144221   0.438596   \n",
       "14                               [-inf:36.5)  180   9     0.19088   0.157895   \n",
       "15                               [36.5:51.5)  276  31    0.292683    0.54386   \n",
       "16                               [51.5:57.5)  148   3    0.156946  0.0526316   \n",
       "17                               [57.5:63.5)  125  10    0.132556   0.175439   \n",
       "18                               [63.5:67.5)   56   1   0.0593849  0.0175439   \n",
       "19                                [67.5:inf)  158   4     0.16755  0.0701754   \n",
       "20                                [-inf:0.5)  900  45    0.954401   0.789474   \n",
       "21                                 [0.5:1.5)   31   4   0.0328738  0.0701754   \n",
       "22                                 [1.5:inf)   12   8   0.0127253   0.140351   \n",
       "23                                [-inf:0.5)  559  21    0.592789   0.368421   \n",
       "24                                 [0.5:inf)  352  35    0.373277   0.614035   \n",
       "25                                      Miss   32   1   0.0339343  0.0175439   \n",
       "26                               [-inf:10.5)  677  31    0.717922    0.54386   \n",
       "27                               [10.5:17.5)  207  20    0.219512   0.350877   \n",
       "28                               [17.5:18.5)   12   1   0.0127253  0.0175439   \n",
       "29                               [18.5:20.5)   18   5    0.019088  0.0877193   \n",
       "30                                [20.5:inf)   29   1   0.0307529  0.0175439   \n",
       "31                                [-inf:0.5)  363  21    0.384942   0.368421   \n",
       "32                                 [0.5:1.5)  341  12    0.361612   0.210526   \n",
       "33                                 [1.5:2.5)  187  15    0.198303   0.263158   \n",
       "34                                 [2.5:inf)   52   9   0.0551432   0.157895   \n",
       "35                               (-inf:3000]  162  12    0.171792   0.210526   \n",
       "36                               (3000:5000]  207  17    0.219512   0.298246   \n",
       "37                               (5000:8500]  221   9    0.234358   0.157895   \n",
       "38                                [8500:inf)  183  10    0.194062   0.175439   \n",
       "39                                      Miss  172   9    0.182397   0.157895   \n",
       "\n",
       "          WOE         IV_i        IV  \n",
       "0    -1.04058     0.401085  1.251684  \n",
       "1    -1.38364    0.0725657  1.251684  \n",
       "2  -0.0561859   0.00045575  1.251684  \n",
       "3     1.01426     0.317536  1.251684  \n",
       "4     3.05733     0.460041  1.251684  \n",
       "5   -0.273051    0.0631689  0.551969  \n",
       "6     2.11287       0.4888  0.551969  \n",
       "7    -1.38364     0.217697  0.487792  \n",
       "8  -0.0948832   0.00347928  0.487792  \n",
       "9    0.823515     0.186456  0.487792  \n",
       "10  -0.538024    0.0403586  0.487792  \n",
       "11   0.934213    0.0398011  0.487792  \n",
       "12  -0.421573     0.124101  0.451516  \n",
       "13    1.11224     0.327415  0.451516  \n",
       "14  -0.189717   0.00625791  0.423641  \n",
       "15   0.619601     0.155629  0.423641  \n",
       "16   -1.09258     0.113972  0.423641  \n",
       "17   0.280286    0.0120195  0.423641  \n",
       "18   -1.21934    0.0510184  0.423641  \n",
       "19  -0.870286     0.084744  0.423641  \n",
       "20  -0.189717    0.0312895  0.365948  \n",
       "21   0.758322    0.0282867  0.365948  \n",
       "22    2.40055     0.306371  0.365948  \n",
       "23  -0.475612     0.106712  0.237358  \n",
       "24   0.497732     0.119833  0.237358  \n",
       "25  -0.659721    0.0108131  0.237358  \n",
       "26  -0.277669    0.0483316  0.223575  \n",
       "27   0.469028    0.0616139  0.223575  \n",
       "28   0.321108   0.00154727  0.223575  \n",
       "29    1.52508     0.104668  0.223575  \n",
       "30  -0.561281   0.00741399  0.223575  \n",
       "31 -0.0438654  0.000724683  0.208901  \n",
       "32  -0.540961    0.0817314  0.208901  \n",
       "33   0.282957     0.018351  0.208901  \n",
       "34      1.052     0.108094  0.208901  \n",
       "35   0.203325   0.00787564  0.067619  \n",
       "36    0.30651    0.0241325  0.067619  \n",
       "37  -0.394923    0.0301973  0.067619  \n",
       "38  -0.100886   0.00187879  0.067619  \n",
       "39  -0.144255   0.00353451  0.067619  "
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "woe_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "得到的woe_df 中会按照IV值的大小从大到小排序，同时还会对区间由大到小排序。   \n",
    "这里需要注意的地方是，如果某个区间里，坏用户数目0，为了防止后面的计算过程中出现除以0的情况发生，这里会在代码里面重新定义为1，以便后面的计算。   \n",
    "这里的区间`[63.5:67.5)`表示的是`x >= 63.6 and x < 67.5`，也就是`[63,5, 67.5)`， `-inf`和`inf`分别表示负无穷和正无穷。  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 评分卡模型创建  \n",
    "\n",
    "分箱结果后，需要将变量的原始取值替换为对应区间的WOE值，以进行后续的连续回归分析。  \n",
    "\n",
    "`replaceWOE`函数提供了WOE替换功能，这里需要提供一个`woe_iv`生成的WOE数据框结果和原始数据。这里只会替换存在WOE数据框中的变量。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "from rosaceae.scorecard import replaceWOE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "woe_data = replaceWOE(woe_df, train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RevolvingUtilizationOfUnsecuredLines</th>\n",
       "      <th>age</th>\n",
       "      <th>NumberOfTime30-59DaysPastDueNotWorse</th>\n",
       "      <th>DebtRatio</th>\n",
       "      <th>MonthlyIncome</th>\n",
       "      <th>NumberOfOpenCreditLinesAndLoans</th>\n",
       "      <th>NumberOfTimes90DaysLate</th>\n",
       "      <th>NumberRealEstateLoansOrLines</th>\n",
       "      <th>NumberOfTime60-89DaysPastDueNotWorse</th>\n",
       "      <th>NumberOfDependents</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3.057329</td>\n",
       "      <td>-0.189717</td>\n",
       "      <td>1.112236</td>\n",
       "      <td>0.823515</td>\n",
       "      <td>-0.100886</td>\n",
       "      <td>0.469028</td>\n",
       "      <td>-0.189717</td>\n",
       "      <td>1.051996</td>\n",
       "      <td>-0.273051</td>\n",
       "      <td>0.497732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3.057329</td>\n",
       "      <td>-0.189717</td>\n",
       "      <td>-0.421573</td>\n",
       "      <td>-1.383640</td>\n",
       "      <td>0.203325</td>\n",
       "      <td>-0.277669</td>\n",
       "      <td>-0.189717</td>\n",
       "      <td>-0.043865</td>\n",
       "      <td>-0.273051</td>\n",
       "      <td>0.497732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.057329</td>\n",
       "      <td>-0.189717</td>\n",
       "      <td>1.112236</td>\n",
       "      <td>-1.383640</td>\n",
       "      <td>0.306510</td>\n",
       "      <td>-0.277669</td>\n",
       "      <td>0.758322</td>\n",
       "      <td>-0.043865</td>\n",
       "      <td>-0.273051</td>\n",
       "      <td>-0.475612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-1.383640</td>\n",
       "      <td>-0.189717</td>\n",
       "      <td>-0.421573</td>\n",
       "      <td>-1.383640</td>\n",
       "      <td>0.306510</td>\n",
       "      <td>-0.277669</td>\n",
       "      <td>-0.189717</td>\n",
       "      <td>-0.043865</td>\n",
       "      <td>-0.273051</td>\n",
       "      <td>-0.475612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3.057329</td>\n",
       "      <td>-0.189717</td>\n",
       "      <td>1.112236</td>\n",
       "      <td>-1.383640</td>\n",
       "      <td>-0.100886</td>\n",
       "      <td>-0.277669</td>\n",
       "      <td>-0.189717</td>\n",
       "      <td>-0.540961</td>\n",
       "      <td>-0.273051</td>\n",
       "      <td>-0.475612</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   RevolvingUtilizationOfUnsecuredLines       age  \\\n",
       "0                              3.057329 -0.189717   \n",
       "1                              3.057329 -0.189717   \n",
       "2                              3.057329 -0.189717   \n",
       "3                             -1.383640 -0.189717   \n",
       "4                              3.057329 -0.189717   \n",
       "\n",
       "   NumberOfTime30-59DaysPastDueNotWorse  DebtRatio  MonthlyIncome  \\\n",
       "0                              1.112236   0.823515      -0.100886   \n",
       "1                             -0.421573  -1.383640       0.203325   \n",
       "2                              1.112236  -1.383640       0.306510   \n",
       "3                             -0.421573  -1.383640       0.306510   \n",
       "4                              1.112236  -1.383640      -0.100886   \n",
       "\n",
       "   NumberOfOpenCreditLinesAndLoans  NumberOfTimes90DaysLate  \\\n",
       "0                         0.469028                -0.189717   \n",
       "1                        -0.277669                -0.189717   \n",
       "2                        -0.277669                 0.758322   \n",
       "3                        -0.277669                -0.189717   \n",
       "4                        -0.277669                -0.189717   \n",
       "\n",
       "   NumberRealEstateLoansOrLines  NumberOfTime60-89DaysPastDueNotWorse  \\\n",
       "0                      1.051996                             -0.273051   \n",
       "1                     -0.043865                             -0.273051   \n",
       "2                     -0.043865                             -0.273051   \n",
       "3                     -0.043865                             -0.273051   \n",
       "4                     -0.540961                             -0.273051   \n",
       "\n",
       "   NumberOfDependents  \n",
       "0            0.497732  \n",
       "1            0.497732  \n",
       "2           -0.475612  \n",
       "3           -0.475612  \n",
       "4           -0.475612  "
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "woe_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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