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)?

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