You can use the following basic syntax to find the intersection between two Series in pandas:

set(series1) & set(series2)

Recall that the intersection of two sets is simply the set of values that are in *both* sets.

The following examples show how to calculate the intersection between pandas Series in practice.

**Example 1: Calculate Intersection Between Two Pandas Series**

The following code shows how to calculate the intersection between two pandas Series:

import pandas as pd #create two Series series1 = pd.Series([4, 5, 5, 7, 10, 11, 13]) series2 = pd.Series([4, 5, 6, 8, 10, 12, 15]) #find intersection between the two series set(series1) & set(series2) {4, 5, 10}

The result is a set that contains the values **4**, **5**, and **10**.

These are the only three values that are in both the first and second Series.

Also note that this syntax works with pandas Series that contain strings:

import pandas as pd #create two Series series1 = pd.Series(['A', 'B', 'C', 'D', 'E']) series2 = pd.Series(['A', 'B', 'B', 'B', 'F']) #find intersection between the two series set(series1) & set(series2) {'A', 'B'}

The only strings that are in both the first and second Series are **A** and **B**.

**Example 2: Calculate Intersection Between Three Pandas Series**

The following code shows how to calculate the intersection between three pandas Series:

import pandas as pd #create three Series series1 = pd.Series([4, 5, 5, 7, 10, 11, 13]) series2 = pd.Series([4, 5, 6, 8, 10, 12, 15]) series3 = pd.Series([3, 5, 6, 8, 10, 18, 21]) #find intersection between the three series set(series1) & set(series2) & set(series3) {5, 10}

The result is a set that contains the values **5 **and **10**.

These are the only values that are in all three Series.

**Additional Resources**

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

How to Convert Pandas Series to DataFrame

How to Convert Pandas Series to NumPy Array

How to Merge Two or More Series in Pandas