Pandas, group by count and add count to original dataframe?

Question

When trying to count rows with similar \'kind\' in data frame:

import pandas as pd

items = [(\'aaa\',\'aaa text 1\'), (\'aaa\',\'aaa text 2\'), (\'aaa\',\'a         


        

Answer 1

IIUC

In [247]: df['count'] = df.groupby('kind').transform('count')

In [248]: df
Out[248]:
    kind          msg  count
0    aaa   aaa text 1      3
1    aaa   aaa text 2      3
2    aaa   aaa text 3      3
3     bb    bb text 1      4
4     bb    bb text 2      4
5     bb    bb text 3      4
6     bb    bb text 4      4
7   cccc  cccc text 1      2
8   cccc  cccc text 2      2
9     dd    dd text 1      1
10     e     e text 1      1
11   fff   fff text 1      1

sorting:

In [249]: df.sort_values('count', ascending=False)
Out[249]:
    kind          msg  count
3     bb    bb text 1      4
4     bb    bb text 2      4
5     bb    bb text 3      4
6     bb    bb text 4      4
0    aaa   aaa text 1      3
1    aaa   aaa text 2      3
2    aaa   aaa text 3      3
7   cccc  cccc text 1      2
8   cccc  cccc text 2      2
9     dd    dd text 1      1
10     e     e text 1      1
11   fff   fff text 1      1

Answer 2

Here is the simple code to count the frequencies and add a column to the data frame.

df['count'] = df.groupby('kind')['Kind'].transform('count')