You can try fillna
or combine_first
:
df.Credit_History = df.Credit_History.fillna(df.Loan_Status)
Or:
df.Credit_History = df.Credit_History.combine_first(df.Loan_Status)
Sample:
import pandas as pd
import numpy as np
df = pd.DataFrame({'Credit_History':[1,2,np.nan, np.nan],
'Loan_Status':[4,5,6,8]})
print (df)
Credit_History Loan_Status
0 1.0 4
1 2.0 5
2 NaN 6
3 NaN 8
df.Credit_History = df.Credit_History.combine_first(df.Loan_Status)
print (df)
Credit_History Loan_Status
0 1.0 4
1 2.0 5
2 6.0 6
3 8.0 8
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