Replace values in pandas column based on nan in another column

Question

For pairs of columns, i want to replace the values of the second columns with nan if the values in the first is nan. I have tried without success

>import pandas as pd
> 
> df=pd.DataFrame({'a': ['r', np.nan, np.nan, 's'], 'b':[0.5, 0.5, 0.2,
> 0.02],  'c':['n','r', np.nan, 's' ], 'd':[1,0.5,0.2,0.05]})
> 
>listA=['a','c']

>listB=['b','d']

>for color, ratio in zip(listA, listB):

>>df.loc[df[color].isnull(), ratio] == np.nan

df remain unchanged

other test using def (failed)

>def Test(df):
>> if df[color]== np.nan:
>> >> return df[ratio]== np.nan
>> else:
>> >>return


    
>for color, ratio in zip(listA, listB):
>>>>df[ratio]=df.apply(Test, axis=1)

Thanks

jezrael · Accepted Answer · 2017-05-23 12:59:19Z

1

It seems you have typo, change == to =:

for color, ratio in zip(listA, listB):
    df.loc[df[color].isnull(), ratio] = np.nan
print (df)
     a     b    c     d
0    r  0.50    n  1.00
1  NaN   NaN    r  0.50
2  NaN   NaN  NaN   NaN
3    s  0.02    s  0.05

Another solution with mask for replace True values of mask to NaN by default:

for color, ratio in zip(listA, listB):
    df[ratio] = df[ratio].mask(df[color].isnull())
print (df)
     a     b    c     d
0    r  0.50    n  1.00
1  NaN   NaN    r  0.50
2  NaN   NaN  NaN   NaN
3    s  0.02    s  0.05

answered May 23, 2017 at 12:59

jezrael

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1 Comment

Guy Over a year ago

Great! Thanks a lot, this completely answers my question

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