熊猫：使用“索引超出范围”错误的模式填充缺少的值

Question

Suppose I have a following DataFrame:

Sample=pd.DataFrame({'Gender':['Male','Male','Male','Male','Female','Female','Male','Male'],
          'Married':['No','Yes','Yes','Yes','No','No','Yes','Yes'],
          'Dependents':['1','1','1','0','3+','3+','1','1'],
          'Education':['Not Graduate','Graduate','Graduate','Graduate','Not Graduate','Not Graduate','Graduate','Graduate'],
          'ApplicantIncome':[3596,3717,4166,2400,3333,6000,1234,4567],
          'Credit_History':['1',np.nan,'0','1',np.nan,'1',np.nan,'0']})

    ApplicantIncome   Credit_History   Dependents    Education       Gender   Married
0     3596                 1               1         Not Graduate    Male    No
1     3717               NaN               1         Graduate        Male    Yes
2     4166                 0               1         Graduate        Male    Yes
3     2400                 1               0         Graduate        Male    Yes
4     3333               NaN               3+        Not Graduate    Female  No  
5     6000                 1               3+        Not Graduate    Female  No
6     1234               NaN               1         Graduate        Male    Yes   
7     4567                 0               1         Graduate        Male    Yes

I would like to fill in NaN with Mode value in ['Gender','Married','Dependents','Education'] group.

I wrote the code below:

Sample['Credit_History']=Sample.groupby(['Gender','Married','Dependents','Education']).transform(lambda x:
                     x.fillna(x.mode()[0]))['Credit_History']

An error message about out of bounds popped up:

IndexError: ('index out of bounds', 'occurred at index ApplicantIncome')

Any idea about how to fix my code above? Thanks!

Answer 1

You can use a simple code to achieve what you want. df["credithistory"].fillna(df["credithistory"].mode())

Don't forget to import numpy.