Skip to content
Related Articles

Related Articles

How to sum values of Pandas dataframe by rows?

View Discussion
Improve Article
Save Article
  • Last Updated : 26 Mar, 2021
View Discussion
Improve Article
Save Article

While working on the python pandas module there may be a need, to sum up, the rows of a Dataframe. Below are the examples of summing the rows of a Dataframe. A Dataframe is a 2-dimensional data structure in form of a table with rows and columns. It can be created by loading the datasets from existing storage, storage can be SQL Database, CSV file, an Excel file, or from a python list or dictionary as well.

Pandas dataframe.sum() function returns the sum of the values for the requested axis.

Syntax: DataFrame.sum(axis)

Parameters:

  • axis : {index (0), columns (1)}

Sum of each row:

df.sum(axis=1)

Example 1:

Summing all the rows of a Dataframe using the sum function and setting the axis value to 1 for summing up the row values and displaying the result as output.

Python3




# importing pandas module as pd
import pandas as pd
  
# creating a dataframe using dictionary
df = pd.DataFrame({'X':[1, 2, 3, 4, 5],
                   'Y':[54, 12, 57, 48, 96]})
  
# sum() method sums up the rows and columns of a dataframe
# axis = 1 sums up the rows
df = df.sum(axis = 1)
print(df)

Output : 

Sum of all the rows by index

Example 2:

Summing all the rows or some rows of the Dataframe as per requirement using loc function and the sum function and setting the axis to 1 for summing up rows. It sums up only the rows specified and puts NaN values in the remaining places.

Python3




# importing pandas as pd
import pandas as pd
  
# creating the dataframe using pandas DataFrame
df = pd.DataFrame({'X':[1, 2, 3, 4, 5],
                   'Y':[54, 12, 57, 48, 96],
                   'Z':['a', 'b', 'c', 'd', 'e']})
  
# df['column_name'] = df.loc[start_row_index:end_row_index,
# ['column1','column2']].sum(axis = 1)
# summing columns X and Y for row from 1 - 3
df['Sum_of_row'] = df.loc[1 : 3,['X' , 'Y']].sum(axis = 1)
print(df)

Output :

Summing all rows from row 1 to 3

Example 3 :

Summing the rows using the eval function to evaluate the sum of the rows with the specified expression as a parameter.

Python3




# importing pandas as pd
import pandas as pd
  
# creating the dataframe using pandas DataFrame
df = pd.DataFrame({'X':[1, 2, 3, 4, 5],
                   'Y':[54, 12, 57, 48, 96],
                   'Z':['a', 'b', 'c', 'd', 'e']})
  
# eval('expression') calculates the sum of the specified columns of that row
df = df.eval('Sum = X + Y')
print(df)

Output : 

Sum of rows using the eval function

Example 4 :

Summing the rows using the eval function to evaluate the sum of the rows with specified rows using loc with the expression to calculate the sum as a parameter to eval function. It only returns the rows which are being specified in the loc and chops off the remaining.

Python3




# importing pandas as pd
import pandas as pd
  
# creating the dataframe using pandas DataFrame
df = pd.DataFrame({'X':[1, 2, 3, 4, 5],
                   'Y':[54, 12, 57, 48, 96],
                   'Z':['a', 'b', 'c', 'd', 'e']})
  
# eval('expression') calculates the sum
# of the specified columns of that row
# using loc for specified rows
df = df.loc[2:4].eval('Sum = X + Y')
display(df)

Output : 

Summing specified rows only using eval


My Personal Notes arrow_drop_up
Recommended Articles
Page :

Start Your Coding Journey Now!