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
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.
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