In this program, we are trying to check whether the specified column in the given data frame ends with the specified string or not. Pandas endswith() is yet another method to search and filter text data in a DataFrame. This method is similar to Pandas.startwith() method.
Syntax: string.endswith(value)
Creating Dataframe to Check If a Column Ends with a given String or Not
Let’s try to understand this using an example suppose we have an employee dataset named Company_id, Joining_Date, Company, companyEmp_id.
Python3
# importing library pandas as pd import pandas as pd # creating data frame for employee df = pd.DataFrame({ 'Company_id': ['IF101', 'IF103', 'GFG671', 'GFG881', 'CAPG961', 'WPR981'], 'Company': ['Infosys', 'Infosys', 'Lazyroar', 'Lazyroar', 'Capgemini', 'Wipro'], 'Joining_Date': ['12/12/2011', '07/12/2012', '11/11/2014', '09/12/2015', '01/01/2016', '01/01/2009'], 'Company_Emp_id': ['abc@infosys.com', 'xyz@infosys.com', 'acd@gfg.com', 'aed@gfg.com', 'klm@capg.com', 'xyz@wipro.com'] }) # printing the given data frame print("Printing Original Student DataFrame:") df |
Output:
Example 1:
The endswith() method in Python returns True if the string ends with the gfg.com, if not it returns False.
Python3
# joining new column in dataframe # endwith function used to check df['GFG_Emp'] = list( map(lambda x: x.endswith('gfg.com'), df['Company_Emp_id'])) # printing new data frame df |
Output:
Example 2:
The endswith() method in Python returns True if the string ends with infosys.com, if not it returns False.
Python3
# joining new column in dataframe # .startswith function used to check df['GFG_Emp'] = list( map(lambda x: x.endswith('Infosys'), df['Company'])) # printing new data frame df |
Output:
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