Josue Barrantes
Josue Barrantes

Reputation: 49

python group by and count() multiple columns

I have a data frame like this:

Country  A B C
UK       1 0 1
US       1 1 1
GB       0 1 1
UK       1 1 1
US       0 1 1
GB       0 1 1

I need to groupby country and count in all columns where value is 1. I'm stuck on setting the condition of columns == 1 for all them.

The result should be something like:

Country  A B C
UK       2 0 2
US       1 2 2
GB       0 2 2

Upvotes: 2

Views: 143

Answers (1)

Prageeth Jayathissa
Prageeth Jayathissa

Reputation: 2116

Because you are counting 1's you can just groupby([]).sum()

df['country'] = df.index # to generate a new column
result = df.groupby(['country']).sum()

This gives you the result:

         a  b  c
country         
GB       0  2  2
UK       2  1  2
US       1  2  2

More information https://pandas.pydata.org/pandas-docs/stable/user_guide/groupby.html

Upvotes: 2

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