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sanaz sanaz - 9 months ago 28
Python Question

Group by two columns and count the occurrences of each combination in pandas

I have the following data frame:

data = pd.DataFrame({'user_id' : ['a1', 'a1', 'a1', 'a2','a2','a2','a3','a3','a3'], 'product_id' : ['p1','p1','p2','p1','p1','p1','p2','p2','p3']})

product_id user_id
p1 a1
p1 a1
p2 a1
p1 a2
p1 a2
p1 a2
p2 a3
p2 a3
p3 a3

in real case there might be some other columns as well, but what i need to do is to group by data frame by product_id and user_id columns and count number of each combination and add it as a new column in a new dat frame

output should be something like this:

user_id product_id count
a1 p1 2
a1 p2 1
a2 p1 3
a3 p2 2
a3 p3 1

I have tried the following code:


but the result is:

user_id product_id
a1 p1
a2 p1
a3 p2

actually the most important thing for me is to have a column names count that has the number of occurrences , i need to use the column later.


Maybe this is what you want?

>>> data = pd.DataFrame({'user_id' : ['a1', 'a1', 'a1', 'a2','a2','a2','a3','a3','a3'], 'product_id' : ['p1','p1','p2','p1','p1','p1','p2','p2','p3']})
>>> count_series = data.groupby(['user_id', 'product_id']).size()
>>> count_series
user_id  product_id
a1       p1            2
         p2            1
a2       p1            3
a3       p2            2
         p3            1
dtype: int64
>>> new_df = count_series.to_frame(name = 'size').reset_index()
>>> new_df
  user_id product_id  size
0      a1         p1     2
1      a1         p2     1
2      a2         p1     3
3      a3         p2     2
4      a3         p3     1
>>> new_df['size']
0    2
1    1
2    3
3    2
4    1
Name: size, dtype: int64