Cumsum as a new column in an existing Pandas data

I have a pandas dataframe defined as:

A B SUM_C 1 1 10 1 2 20

I would like to do a cumulative sum of SUM_C and add it as a new column to the same dataframe. In other words, my end goal is to have a dataframe that looks like below:

A B SUM_C CUMSUM_C 1 1 10 10 1 2 20 30

Using cumsum in pandas on group() shows the possibility of generating a new dataframe where column name SUM_C is replaced with cumulative sum. However, my ask is to add the cumulative sum as a new column to the existing dataframe.

Thank you

1 Answer
1

Just apply cumsum on the pandas.Series df['SUM_C'] and assign it to a new column:

cumsum

pandas.Series

df['SUM_C']

df['CUMSUM_C'] = df['SUM_C'].cumsum(axis = 0)

Result:

df Out[34]: A B SUM_C CUMSUM_C 0 1 1 10 10 1 1 2 20 30

Thank you. Correct answer for the question that was posed. I would like to also add that if we have more than two columns and would like to do the same, they process is below: Step:1: obviously work with a sorted data frame 2. Use df['CUM_D'] = df.groupby(['A','B'])['D'].cumsum(axis = 0). skipped 'C' in groupby as it is the column on which cumulative summation is being done.
– user1124702
Jan 25 '17 at 19:53

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