How can I replace is.null values with condition using pandas/numpy?

January 19, 2022

My dataset:

data={'A':['1210226','1210226','1210226','1210302','1210336','1210336','1210336'],'B':['','','2@.com','1@.com','','','1@.com']}
df=pd.DataFrame(data)
print(df)

I filter the column to blanks in excel == python( used is.null)

Data set in excel

The condition I want to apply in pandas is =IF(A1=A3,B3,"") formula is written in excel ( please review the image), and sheet is filtered with blanks. I know O have to use is.null() then i want to apply condition to the is.null in order to get required output.

Final output should be something like below image

>Solution :

You can try the following:

data={'A':['1210226','1210226','1210226','1210302','1210336','1210336','1210336'],'B':['','','2@.com','1@.com','','','1@.com']}
df=pd.DataFrame(data)

df.drop("B", axis=1).merge(df.groupby("A").max(), on="A")

Output:

    A            B
0   1210226     2@.com
1   1210226     2@.com
2   1210226     2@.com
3   1210302     1@.com
4   1210336     1@.com
5   1210336     1@.com
6   1210336     1@.com