Pandas: How can I use the apply() function for a s

问题:

I have a pandas data frame with two columns. I need to change the values of the first column without affecting the second one and get back the whole data frame with just first column values changed. How can I do that using apply in pandas?

回答1:

Given a sample dataframe df as:

a,b
1,2
2,3
3,4
4,5

what you want is:

df['a'] = df['a'].apply(lambda x: x + 1)

that returns:

   a  b
0  2  2
1  3  3
2  4  4
3  5  5

回答2:

You don't need a function at all. You can work on a whole column directly.

Example data:

>>> df = pd.DataFrame({'a': [100, 1000], 'b': [200, 2000], 'c': [300, 3000]})
>>> df

      a     b     c
0   100   200   300
1  1000  2000  3000

Half all the values in column a:

>>> df.a = df.a / 2
>>> df

     a     b     c
0   50   200   300
1  500  2000  3000

回答3:

For a single column better to use map(), like this:

df = pd.DataFrame([{'a': 15, 'b': 15, 'c': 5}, {'a': 20, 'b': 10, 'c': 7}, {'a': 25, 'b': 30, 'c': 9}])

    a   b  c
0  15  15  5
1  20  10  7
2  25  30  9



df['a'] = df['a'].map(lambda a: a / 2.)

      a   b  c
0   7.5  15  5
1  10.0  10  7
2  12.5  30  9