Pandas groupby cumulative sum

by

This should do it, need groupby() twice:

df.groupby(['name', 'day']).sum() \
  .groupby(level=0).cumsum().reset_index()

Explanation:

print(df)
   name        day   no
0  Jack     Monday   10
1  Jack    Tuesday   20
2  Jack    Tuesday   10
3  Jack  Wednesday   50
4  Jill     Monday   40
5  Jill  Wednesday  110

# sum per name/day
print( df.groupby(['name', 'day']).sum() )
                 no
name day           
Jack Monday      10
     Tuesday     30
     Wednesday   50
Jill Monday      40
      Wednesday  110

# cumulative sum per name/day
print( df.groupby(['name', 'day']).sum() \
         .groupby(level=0).cumsum() )
                 no
name day           
Jack Monday      10
     Tuesday     40
     Wednesday   90
Jill Monday      40
     Wednesday  150

The dataframe resulting from the first sum is indexed by 'name' and by 'day'. You can see it by printing 

df.groupby(['name', 'day']).sum().index

When computing the cumulative sum, you want to do so by 'name', corresponding to the first index (level 0).

Finally, use reset_index to have the names repeated.

df.groupby(['name', 'day']).sum().groupby(level=0).cumsum().reset_index()

   name        day   no
0  Jack     Monday   10
1  Jack    Tuesday   40
2  Jack  Wednesday   90
3  Jill     Monday   40
4  Jill  Wednesday  150

More Related Contents:

  1. How can I pivot a dataframe?
  2. How to group dataframe rows into list in pandas groupby
  3. Concatenate strings from several rows using Pandas groupby
  4. Groupby value counts on the dataframe pandas
  5. Split pandas dataframe based on groupby
  6. Pandas: filling missing values by mean in each group
  7. GroupBy pandas DataFrame and select most common value
  8. Converting a Pandas GroupBy output from Series to DataFrame
  9. pandas GroupBy columns with NaN (missing) values
  10. Count unique values per groups with Pandas [duplicate]
  11. Multiple aggregations of the same column using pandas GroupBy.agg()
  12. Python Pandas max value in a group as a new column
  13. pandas dataframe groupby datetime month
  14. How to loop over grouped Pandas dataframe?
  15. How to move pandas data from index to column after multiple groupby
  16. Python – rolling functions for GroupBy object
  17. Pandas GroupBy and select rows with the minimum value in a specific column
  18. Use pandas.shift() within a group
  19. Pandas Groupby and Sum Only One Column
  20. Python Pandas Conditional Sum with Groupby
  21. Identifying statistical outliers with pandas: groupby and reduce rows into different dataframe
  22. Pandas Groupby / List to Multiple Rows
  23. Sample each group after pandas groupby
  24. Pandas groupby with categories with redundant nan
  25. pandas groupby where you get the max of one column and the min of another column
  26. Bar graph from dataframe groupby
  27. pandas group by and assign a group id then ungroup
  28. Is there an “ungroup by” operation opposite to .groupby in pandas?
  29. get first and last values in a groupby
  30. How to get number of groups in a groupby object in pandas?

Leave a Comment