Calculate cumulative count of a pandas dataframe column

Question:

I have created this pandas dataframe:

import numpy as np
import pandas as pd

ds = {"col1":[1,2,3,2,2,2,3,4,1,0,0,0,0,0,1,2,3,5]}

df = pd.DataFrame(data=ds)

which looks like this:

print(df)

    col1
0      1
1      2
2      3
3      2
4      2
5      2
6      3
7      4
8      1
9      0
10     0
11     0
12     0
13     0
14     1
15     2
16     3
17     5

I need to create a new column (col2) which contains the cumulative count of the values in col1. So, the resulting dataframe would look like this:

enter image description here

Does anybody know how to do it, please?

Asked By: Giampaolo Levorato

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Source

Answers:

Consider using cumcount() after groupby(). Add +1 to start counting from 1 instead of 0:

df['col2'] = df.groupby('col1').cumcount()+1

Returns:

    col1  col2
0      1     1
1      2     1
2      3     1
3      2     2
4      2     3
5      2     4
6      3     2
7      4     1
8      1     2
9      0     1
10     0     2
11     0     3
12     0     4
13     0     5
14     1     3
15     2     5
16     3     3
17     5     1
Answered By: Celius Stingher

There is precisely a grouby.cumcount function:

df['col2'] = df.groupby('col1').cumcount().add(1)

Output:

    col1  col2
0      1     1
1      2     1
2      3     1
3      2     2
4      2     3
5      2     4
6      3     2
7      4     1
8      1     2
9      0     1
10     0     2
11     0     3
12     0     4
13     0     5
14     1     3
15     2     5
16     3     3
17     5     1
Answered By: mozway