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