Pandas - Convert Cumulative Value To Actual Value

Let's say my dataframe looks something like this: date,site,country_code,kind,ID,rank,votes,sessions,avg_score,count 2017-03-20,website1,US,0,84,226,0.0,15.0,3.370812,53.0 2017-03-

Solution 1:

Use groupby + diff, the inverse of cumsum.

cols = ['site', 'country_code', 'kind', 'ID']
df['count'] = df.groupby(cols)['count'].diff().fillna(0)

print(df['count'])
0     0.0
1     0.0
2     0.0
3     1.0
4     0.0
5     0.0
6     0.0
7     0.0
8     3.0
9     0.0
10    3.0
11    2.0
Name: count, dtype: float64

Thanks to MaxU for pointing out the error!