How to Sum Rows in Dataframe in Python

This tutorial shows how to sum rows in a dataframe using Pandas in Python.

Example 1: Use sum() for all rows

import pandas as pd

brand_data = {'Brand': ['BrandA', 'BrandB','BrandA','BrandC','BrandA'], 
     'Location': ['CA', 'CA','NY','MA','CA'],
    'Number':[20,30,25,20,20]}
brand_data=pd.DataFrame(data=brand_data)
print(brand_data)

    Brand Location  Number
0  BrandA       CA      20
1  BrandB       CA      30
2  BrandA       NY      25
3  BrandC       MA      20
4  BrandA       CA      20

brand_data["Number"].sum( skipna = True)

brand_data["Number"].sum(axis=0,skipna = True)

Example 2: Use sum() for selected rows

The following code shows how to use sum() for the first two rows.

# sum of the first two rows for the column of "Number"
sum_result=brand_data.loc[0:1,"Number"].sum()
print(sum_result)

# sum of the first two rows for the column of "Number"
sum_result=brand_data["Number"].loc[0:1].sum()
print(sum_result)

You can use minus notation to sum the last few rows. The following is to sum the last two rows.

# the following code will sum last two numbers, namely the last second
sum_result=brand_data["Number"].iloc[-2:].sum()
print(sum_result)

If you add -1 within iloc[], it will only sum the last second number, and ignore the last number.

# the following code will only sum one number, namely the last second
sum_result=brand_data["Number"].iloc[-2:-1].sum()
print(sum_result)