How to apply a function to multiple columns in Pandas [duplicate]

Question

I have a bunch of columns which requires cleaning in Pandas. I've written a function which does that cleaning. I'm not sure how to apply the same function to many columns. Here is what I'm trying:

df["Passengers", "Revenue", "Cost"].apply(convert_dash_comma_into_float)

But I'm getting KeyError.

Shouldn't it be df[["Passengers", "Revenue", "Cost"]]? You need to use a list of column names when you index your dataframe. — user3483203
– user3483203, Commented May 25, 2018 at 0:43

Scott Boston · Accepted Answer · 2018-05-25 00:55:59Z

9

Use double brackets [[]] as @chrisz points out:

Here is a MVCE:

df = pd.DataFrame(np.arange(30).reshape(10,-1),columns=['A','B','C'])

def f(x):
    #Clean even numbers from columns.
    return x.mask(x%2==0,0)

df[['B','C']] = df[['B','C']].apply(f)
print(df)

Output

    A   B   C
0   0   1   0
1   3   0   5
2   6   7   0
3   9   0  11
4  12  13   0
5  15   0  17
6  18  19   0
7  21   0  23
8  24  25   0
9  27   0  29

answered May 25, 2018 at 0:55

Scott Boston

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3 Comments

Hannan Over a year ago

Thanks, I made a list of it and now getting TypeError that it cannot convert series to <class 'float'>. But it clearly works when I supply only one column like df["Passengers"].apply(convert_dash_comma_into_float)

mathee Over a year ago

This solution does not work ...

Scott Boston Over a year ago

@mathee This appears to work from this example. Both columns B and C have the even values sub with zeroes. per the function, f.

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