Pandas: apply different functions to different columns

Question

When using df.mean() I get a result where the mean for each column is given. Now let\'s say I want the mean of the first column, and the sum of the second. Is t

Answer 1

Just faced this situation myself and came up with the following:

In [1]: import pandas as pd

In [2]: df = pd.DataFrame([['one', 'two'], ['three', 'four'], ['five', 'six']], 
   ...:                   columns=['A', 'B'])

In [3]: df
Out[3]: 
       A     B
0    one   two
1  three  four
2   five   six

In [4]: converters = {'A': lambda x: x[:1], 'B': lambda x: x.replace('o', '')}

In [5]: new = pd.DataFrame.from_dict({col: series.apply(converters[col]) 
   ...:                               if col in converters else series
   ...:                               for col, series in df.iteritems()})

In [6]: new
Out[6]: 
   A    B
0  o   tw
1  t  fur
2  f  six