CODEWITHSUNDEEP
pythonpandasdataframe
Sayyor Y
Sayyor Y

Reputation: 1314

Make each column a sum of all previous columns for Pandas Dataframe

I have the following pandas dataframe:

           2019 Jan  2019 Mar  2019 Apr  2019 May  2019 Jun
 CASC\n         2.0       2.0       2.0       1.0       2.0
 SpaceX\n       1.0       1.0       1.0       2.0       2.0

which you can get using the following code:

import pandas as pd

data_dict = {
    '2019 Jan': {' CASC\n': 2.0, ' SpaceX\n': 1.0},
    '2019 Mar': {' CASC\n': 2.0, ' SpaceX\n': 1.0},
    '2019 Apr': {' CASC\n': 2.0, ' SpaceX\n': 1.0},
    '2019 May': {' CASC\n': 1.0, ' SpaceX\n': 2.0},
    '2019 Jun': {' CASC\n': 2.0, ' SpaceX\n': 2.0}
 }

pd.DataFrame.from_dict(data_dict)

I wanted to make each column to be a sum of all the previous columns, so the final dataframe would be like this:

           2019 Jan  2019 Mar  2019 Apr  2019 May  2019 Jun
 CASC\n         2.0       4.0       6.0       7.0       9.0
 SpaceX\n       1.0       2.0       3.0       5.0       7.0

I could get a sum of all the columns and make it a new column with this code:

df['Total'] = df.iloc[:,:].sum(axis=1)

which would result in the following dataframe:

           2019 Jan  2019 Mar  2019 Apr  2019 May  2019 Jun  Total
 CASC\n         2.0       2.0       2.0       1.0       2.0    9.0
 SpaceX\n       1.0       1.0       1.0       2.0       2.0    7.0

but it is obviously not what I want. Instead I want each column act as "Total" for the previous columns and itself. Does anybody know how to do it?

Upvotes: 1

Views: 536

Answers (1)

Алексей Р
Алексей Р

Reputation: 7627

df=df.cumsum(axis=1)
print(df)

Prints:

           2019 Jan  2019 Mar  2019 Apr  2019 May  2019 Jun
 CASC\n         2.0       4.0       6.0       7.0       9.0
 SpaceX\n       1.0       2.0       3.0       5.0       7.0

Upvotes: 2

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