python信用评分卡（附代码，博主录制）
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1. Data Lending Club 2016年Q3数据：https://www.lendingclub.com/info/download-data.action
参考：http://kldavenport.com/lending-club-data-analysis-revisted-with-python/
import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns %matplotlib inline讯享网
讯享网df = pd.read_csv("./LoanStats_2016Q3.csv",skiprows=1,low_memory=False)
df.info()讯享网df.head(3)
| id | member_id | loan_amnt | funded_amnt | funded_amnt_inv | term | int_rate | installment | grade | sub_grade | … | sec_app_earliest_cr_line | sec_app_inq_last_6mths | sec_app_mort_acc | sec_app_open_acc | sec_app_revol_util | sec_app_open_il_6m | sec_app_num_rev_accts | sec_app_chargeoff_within_12_mths | sec_app_collections_12_mths_ex_med | sec_app_mths_since_last_major_derog | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | NaN | NaN | 15000.0 | 15000.0 | 15000.0 | 36 months | 13.99% | 512.60 | C | C3 | … | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| 1 | NaN | NaN | 2600.0 | 2600.0 | 2600.0 | 36 months | 8.99% | 82.67 | B | B1 | … | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| 2 | NaN | NaN | 32200.0 | 32200.0 | 32200.0 | 60 months | 21.49% | 880.02 | D | D5 | … | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
3 rows × 122 columns
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