Here’s how to calculate sum of rows and columns in Pandas dataframe.

In this post, I will show you how to easily prepare a summary of columns and rows in a dataframe.

## How to calculate sum of rows

You can simply use the sum function to calculate the sum of the rows. As a parameter, add only axis=1 to indicate that you want to sum the rows.

import pandas as pd my_df = pd.DataFrame({'Exam1': [2, 5, 7, 46], 'Exam2': [12, 21, 5, 22], 'Exam3': [8, 22, 9, 12]}) my_df['Sum_of_Rows'] = my_df.sum(axis=1) print(f'Sum of rows: \n {my_df}')

The summary is displayed in a separate column that I created.

## How to calculate sum of columns

Also use the sum function to calculate the sum of the columns. As a parameter, add axis=0, which indicates that Pandas is supposed to sum the columns.

import pandas as pd my_df = pd.DataFrame({'Exam1': [2, 5, 7, 46], 'Exam2': [12, 21, 5, 22], 'Exam3': [8, 22, 9, 12]}) sum_of_columns = my_df.sum(axis=0) print(f'Sum of columns: \n{sum_of_columns}')

Pandas displays a summary of the columns along with the data type they contain.

## How to calculate cumsum of column

It is also possible to calculate a cumulative sum for a column in the dataframe. To do this, create a new column and indicate for which column you want to calculate the cumulative total.

import pandas as pd my_df = pd.DataFrame({'Column1': [2, 5, 7, 46], 'Column2': [12, 21, 5, 22], 'Column3': [8, 22, 9, 12]}) my_df['Cumsum_of_Column1'] = my_df['Column1'].cumsum() print(f'Cumsum of Column1: \n {my_df}')

See also:

How to calculate cumulative sum in Pandas

How to count specific value in column

How to add a column

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