How to use lambda function just in null rows of a column in pandas

Question

I am trying to put 0 or 1 in place of the null rows of a column using lambda function, but my code doesn't make any changes in the data.

df[df['a'].isnull()]['a']=df[df['a'].isnull()].apply(lambda x:1 if (x.b==0 and x.c==0) else 
                                                      0,axis=1)

Where I am wrong in this?? sample table

df[df['a'].isnull()] makes a copy df[df['a'].isnull()]['a'] accesses the column in that copy. Then the copy gets thrown away since there are no references to it any longer How to deal with SettingWithCopyWarning in Pandas use df.loc[df['a'].isnull(), 'a'] = ... as outlined in the accepted answer — Henry Ecker
– Henry Ecker ♦, Commented Oct 2, 2021 at 20:36

Shivam Roy · Accepted Answer · 2021-10-02 22:08:49Z

2

You can use loc to specifically fill the null value rows in your DataFrame. When you're using the apply method you can use it on the entire DataFrame, you do not need to filter for NULL values there. The loc will take care of only filling the rows which meet the NULL condition. This should work :

df['a'].loc[df['a'].isnull()] = df.apply(lambda x:1 if (x.b==0 and x.c==0) else 
                                                  0,axis=1)

edited Oct 2, 2021 at 22:08

answered Oct 2, 2021 at 20:45

Shivam Roy

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2 Comments

Akansha Over a year ago

In this code only null values are treated and stored in new_df, but then how should I put these replaced values back in my original data frame i.e df ??

Shivam Roy Over a year ago

@Akansha I have edited my answer and tested it. Hope it works for you.

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