How to groupby with certain condition in pandas dataframe

Question

I have dataframe like this

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

I want to get result below(1row*4column dataframe),

A_count_all means the number of rows in dataframe   df.A.count()

A_sum_all means the df.A.sum()

A_count_a is df.loc[df.B==a,"A"].count()

A_sum_a is df.loc[df.B==a,"A"].sum()


    A_count_all   A_sum_all  A_count_a   A_sum_a  
0      5            15          3            8

how can I get this result dataframe?

Answer 1

You can use DataFrame constructor:

A_count_all = df.A.count()
A_sum_all = df.A.sum()
A_count_a = df.loc[df.B=='a',"A"].count()
A_sum_a = df.loc[df.B=='a',"A"].sum()

print (pd.DataFrame({'A_count_all':A_count_all, 
                     'A_sum_all':A_sum_all,
                     'A_count_a':A_count_a,
                     'A_sum_a':A_sum_a},
                      index=[0],
                      columns=['A_count_all','A_sum_all','A_count_a','A_sum_a']))

   A_count_all  A_sum_all  A_count_a  A_sum_a
0            5         15          3        8

Thank you Kris for another solution:

print (pd.DataFrame(data=[[df.A.count(),
                          df.A.sum(),
                          df.loc[df.B=='a',"A"].count(),
                          df.loc[df.B=='a',"A"].sum()]],
                          columns=['A_count_all','A_sum_all','A_count_a','A_sum_a']))

   A_count_all  A_sum_all  A_count_a  A_sum_a
0            5         15          3        8