无法用所有列的列值填充缺失值

Question

我有一个如下所示的数据框

df = pd.DataFrame({'Credit_History':['Yes','ABC','DEF', 'JKL'],
                   'Loan_Status':['T1','T2',np.nan,np.nan],
                   'subject_status':['DUMMA','CHUMMA',np.nan,np.nan],
                   'test_status':['test',np.nan,np.nan,np.nan]})

我的 objective 是在所有行和列中用相应的 credit_history 值填充缺失值

我尝试了以下方法，但它不起作用

cols = ['Loan_Status','subject_status','test_status']
df[cols] = df[cols].fillna(df['Credit_History'])

我希望我的输出如下所示。基本上，无论哪一行丢失，它都应该从 credit_history 列

中选择相应的值

Answer 1

使用DataFrame.apply, so is used Series.fillna:

cols = ['Loan_Status','subject_status','test_status']
df[cols] = df[cols].apply(lambda x: x.fillna(df['Credit_History']))

print (df)
  Credit_History Loan_Status subject_status test_status
0            Yes          T1          DUMMA        test
1            ABC          T2         CHUMMA         ABC
2            DEF         DEF            DEF         DEF
3            JKL         JKL            JKL         JKL

或转置：

cols = ['Loan_Status','subject_status','test_status']
df[cols] = df[cols].T.fillna(df['Credit_History']).T

print (df)
  Credit_History Loan_Status subject_status test_status
0            Yes          T1          DUMMA        test
1            ABC          T2         CHUMMA         ABC
2            DEF         DEF            DEF         DEF
3            JKL         JKL            JKL         JKL

无法用所有列的列值填充缺失值

Unable to fill missing values with column value across all columns

python

pandas

dataframe

series

fillna