Nilani Algiriyage Nilani Algiriyage - 4 months ago 10
Python Question

Pandas DataFrame Groupby two columns and get counts

I have a pandas dataframe in the following format:

df = pd.DataFrame([[1.1, 1.1, 1.1, 2.6, 2.5, 3.4,2.6,2.6,3.4,3.4,2.6,1.1,1.1,3.3], list('AAABBBBABCBDDD'), [1.1, 1.7, 2.5, 2.6, 3.3, 3.8,4.0,4.2,4.3,4.5,4.6,4.7,4.7,4.8], ['x/y/z','x/y','x/y/z/n','x/u','x','x/u/v','x/y/z','x','x/u/v/b','-','x/y','x/y/z','x','x/u/v/w'],['1','3','3','2','4','2','5','3','6','3','5','1','1','1']]).T
df.columns = ['col1','col2','col3','col4','col5']


df:

col1 col2 col3 col4 col5
0 1.1 A 1.1 x/y/z 1
1 1.1 A 1.7 x/y 3
2 1.1 A 2.5 x/y/z/n 3
3 2.6 B 2.6 x/u 2
4 2.5 B 3.3 x 4
5 3.4 B 3.8 x/u/v 2
6 2.6 B 4 x/y/z 5
7 2.6 A 4.2 x 3
8 3.4 B 4.3 x/u/v/b 6
9 3.4 C 4.5 - 3
10 2.6 B 4.6 x/y 5
11 1.1 D 4.7 x/y/z 1
12 1.1 D 4.7 x 1
13 3.3 D 4.8 x/u/v/w 1


Now I want to group this by two columns like following:

df.groupby(['col5','col2']).reset_index()


OutPut:

index col1 col2 col3 col4 col5
col5 col2
1 A 0 0 1.1 A 1.1 x/y/z 1
D 0 11 1.1 D 4.7 x/y/z 1
1 12 1.1 D 4.7 x 1
2 13 3.3 D 4.8 x/u/v/w 1
2 B 0 3 2.6 B 2.6 x/u 2
1 5 3.4 B 3.8 x/u/v 2
3 A 0 1 1.1 A 1.7 x/y 3
1 2 1.1 A 2.5 x/y/z/n 3
2 7 2.6 A 4.2 x 3
C 0 9 3.4 C 4.5 - 3
4 B 0 4 2.5 B 3.3 x 4
5 B 0 6 2.6 B 4 x/y/z 5
1 10 2.6 B 4.6 x/y 5
6 B 0 8 3.4 B 4.3 x/u/v/b 6


I want to get the count by each row like following.
Expected Output:

col5 col2 count
1 A 1
D 3
2 B 2
etc...


How to get my expected output? And I want to find largest count for each 'col2' value?

Answer

Followed by @Andy's answer, you can do following to solve your second question:

In [56]: df.groupby(['col5','col2']).size().reset_index().groupby('col2')[[0]].max()
Out[56]: 
      0
col2   
A     3
B     2
C     1
D     3
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