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 pdimport pandas as pd # creating a dataframe using dictionarydf = 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 rowsdf = 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 pdimport pandas as pd # creating the dataframe using pandas DataFramedf = 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 - 3df['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 pdimport pandas as pd # creating the dataframe using pandas DataFramedf = 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 rowdf = 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 pdimport pandas as pd # creating the dataframe using pandas DataFramedf = 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 rowsdf = df.loc[2:4].eval('Sum = X + Y')display(df) |
Output :
Summing specified rows only using eval
