python - Changing certain values in multiple columns of a pandas DataFrame at once

Question

Suppose I have the following DataFrame:

In [1]: df
Out[1]:
  apple banana cherry
0     0      3   good
1     1      4    bad
2     2      5   good

This works as expected:

In [2]: df['apple'][df.cherry == 'bad'] = np.nan
In [3]: df
Out[3]:
  apple banana cherry
0     0      3   good
1   NaN      4    bad
2     2      5   good

But this doesn't:

In [2]: df[['apple', 'banana']][df.cherry == 'bad'] = np.nan
In [3]: df
Out[3]:
  apple banana cherry
0     0      3   good
1     1      4    bad
2     2      5   good

Why? How can I achieve the conversion of both the 'apple' and 'banana' values without having to write out two lines, as in

In [2]: df['apple'][df.cherry == 'bad'] = np.nan
In [3]: df['banana'][df.cherry == 'bad'] = np.nan

Answer 1

You should use loc and do this without chaining:

In [11]: df.loc[df.cherry == 'bad', ['apple', 'banana']] = np.nan

In [12]: df
Out[12]: 
   apple  banana cherry
0      0       3   good
1    NaN     NaN    bad
2      2       5   good

See the docs on returning a view vs a copy, if you chain the assignment is made to the copy (and thrown away) but if you do it in one loc then pandas cleverly realises you want to assign to the original.