Pandas DataFrame: apply function to all columns

Question

I can use .map(func) on any column in a df, like:

df=DataFrame({'a':[1,2,3,4,5,6],'b':[2,3,4,5,6,7]})

df['a']=df['a'].map(lambda x: x > 1)

I could also:

df['a'],df['b']=df['a'].map(lambda x: x > 1),df['b'].map(lambda x: x > 1)

Is there a more pythonic way to apply a function to all columns or the entire frame (without a loop)?

Asked By: root

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Source

Answer 1

If I understand you right, you’re looking for the applymap method.

>>> print df
   A  B  C
0 -1  0  0
1 -4  3 -1
2 -1  0  2
3  0  3  2
4  1 -1  0
>>> print df.applymap(lambda x: x>1)
       A      B      C
0  False  False  False
1  False   True  False
2  False  False   True
3  False   True   True
4  False  False  False

Answered By: BrenBarn

Answer 2

From 0.20.0 onwards, you can use transform

In [578]: df.transform(lambda x: x > 1)
Out[578]:
       A      B      C
0  False  False  False
1  False   True  False
2  False  False   True
3  False   True   True
4  False  False  False

In [579]: df
Out[579]:
   A  B  C
0 -1  0  0
1 -4  3 -1
2 -1  0  2
3  0  3  2
4  1 -1  0

And, for this simplistic case, why not just use df > 1 ?

In [582]: df > 1
Out[582]:
       A      B      C
0  False  False  False
1  False   True  False
2  False  False   True
3  False   True   True
4  False  False  False

Answered By: Zero

Pandas DataFrame: apply function to all columns

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