README.md

XXDScorecard

安装

pip install XXDScorecard

使用

scorecard developing utilities.

import XXDScorecard.XXDBinning as binning

from sklearn.model_selection import train_test_split

df = pd.read_csv('data.csv')

train_df, test_df = train_test_split(df,test_size=0.3,random_state=100,stratify=df.flgGood)

数值型

nb = binning.XXDNumberBin()

1. 数值型等频分箱

nb.pct_bin(train_df,'req_inc_ratio','flgGood',max_bin=10)

2. 分箱结果

nb.get_bin_stats()

3. WOE图

nb.plot_woe()

4. 测试集转woe

nb.trans_to_woe(test_df['req_inc_ratio'])

5. 手动调整分箱

nb.manual_bin(train_df,'req_inc_ratio','flgGood',[20,30,40])

6. 自动单调分箱

nb.monotone_bin(train_df,'req_inc_ratio','flgGood',max_bin=3)

字符型

1. 自动分箱

cb = binning.XXDCharBin()

cb.pct_bin(train_df,'name','flgGood')

2. woe图

cb.plot_woe()

3. 分箱结果

cb.get_bin_stats()

4. 字符型手动分箱

cb.manual_bin(train_df,'name','flgGood',[['yuqing','xuxiaodong'],['jack ma'],['yq','dd','xxd','qq']])

5. 测试集转woe

cb.trans_to_woe(test_df['name'])

更多内容请关注微信公众号

如果对建模感兴趣，也可以学习整套信用风险建模课程