You can use the following methods to find the sum of specific rows in a pandas DataFrame:

**Method 1: Sum Specific Rows by Index**

#sum rows in index positions 0, 1, and 4 df.iloc[[0, 1, 4]].sum()

**Method 2: Sum Specific Rows by Label**

#sum rows with index labels 'A', 'B', and 'E' df.loc[['A', 'B', 'E']].sum()

The following examples show how to use each method in practice with the following pandas DataFrame:

import pandas as pd #create DataFrame df = pd.DataFrame({'points': [28, 17, 19, 14, 23, 26, 5], 'rebounds': [5, 6, 4, 7, 14, 12, 9], 'assists': [10, 13, 7, 8, 4, 5, 8]}) #set index df = df.set_index([pd.Index(['A', 'B', 'C', 'D', 'E', 'F', 'G'])]) #view DataFrame print(df) points rebounds assists A 28 5 10 B 17 6 13 C 19 4 7 D 14 7 8 E 23 14 4 F 26 12 5 G 5 9 8

**Example 1: Sum Specific Rows by Index**

The following code shows how to sum the values in the rows with index values 0, 1, and 4 for each column in the DataFrame:

#sum rows in index positions 0, 1, and 4 df.iloc[[0, 1, 4]].sum() points 68 rebounds 25 assists 27 dtype: int64

From the output we can see:

- The sum of rows with index values 0, 1, and 4 for the
**points**column is**68**. - The sum of rows with index values 0, 1, and 4 for the
**rebounds**column is**25**. - The sum of rows with index values 0, 1, and 4 for the
**assists**column is**27**.

Also note that you can sum a specific range of rows by using the following syntax:

#sum rows in index positions between 0 and 4 df.iloc[0:4].sum() points 78 rebounds 22 assists 38 dtype: int64

From the output we can see the sum of the rows with index values between 0 and 4 (not including 4) for each of the columns in the DataFrame.

**Example 2: Sum Specific Rows by Label**

The following code shows how to sum the values in the rows with index labels ‘A’, ‘B’, and ‘E’ for each column in the DataFrame:

#sum rows with index labels 'A', 'B', and 'E' df.loc[['A', 'B', 'E']].sum() points 68 rebounds 25 assists 27 dtype: int64

From the output we can see:

- The sum of rows with index values ‘A’, ‘B’, and ‘E’ for the
**points**column is**68**. - The sum of rows with index values ‘A’, ‘B’, and ‘E’ for the
**rebounds**column is**25**. - The sum of rows with index values ‘A’, ‘B’, and ‘E’ for the
**assists**column is**27**.

**Related:** The Difference Between loc vs. iloc in Pandas

**Additional Resources**

The following tutorials explain how to perform other common operations in pandas:

How to Perform a SUMIF Function in Pandas

How to Perform a GroupBy Sum in Pandas

How to Sum Columns Based on a Condition in Pandas