You can use the following methods to check if a column of a pandas DataFrame contains a string:

**Method 1: Check if Exact String Exists in Column**

(df['col'].eq('exact_string')).any()

**Method 2: Check if Partial String Exists in Column**

df['col'].str.contains('partial_string').any()

**Method 3: Count Occurrences of Partial String ****in Column**

df['col'].str.contains('partial_string').sum()

This tutorial explains how to use each method in practice with the following DataFrame:

import pandas as pd #create DataFrame df = pd.DataFrame({'team': ['A', 'A', 'A', 'B', 'B', 'C'], 'conference': ['East', 'East', 'South', 'West', 'West', 'East'], 'points': [11, 8, 10, 6, 6, 5]}) #view DataFrame df team conference points 0 A East 11 1 A East 8 2 A South 10 3 B West 6 4 B West 6 5 C East 5

**Example 1: Check if Exact String Exists in Column**

The following code shows how to check if the exact string ‘Eas’ exists in the **conference** column of the DataFrame:

#check if exact string 'Eas' exists in conference column (df['conference'].eq('Eas')).any() False

The output returns **False**, which tells us that the exact string ‘Eas’ does not exist in the **conference** column of the DataFrame.

**Example 2: Check if Partial String Exists in Column**

The following code shows how to check if the partial string ‘Eas’ exists in the **conference** column of the DataFrame:

#check if partial string 'Eas' exists in conference column df['conference'].str.contains('Eas').any() True

The output returns **True**, which tells us that the partial string ‘Eas’ does exist in the **conference** column of the DataFrame.

**Example 3: Count Occurrences of Partial String in Column**

The following code shows how to count the number of times the partial string ‘Eas’ occurs in the **conference** column of the DataFrame:

#count occurrences of partial string 'Eas' in conference column df['conference'].str.contains('East').sum() 3

The output returns **3**, which tells us that the partial string ‘Eas’ occurs 3 times in the **conference** column of the DataFrame.

**Additional Resources**

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

How to Drop Rows in Pandas DataFrame Based on Condition

How to Filter a Pandas DataFrame on Multiple Conditions

How to Use “NOT IN” Filter in Pandas DataFrame