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Pandas – Find Column Names that End with Specific String

In this tutorial, we will look at how to get the column names in a pandas dataframe that end with a specific string (in the column name) with the help of some examples.

How to find columns whose name ends with a specific string?

pandas column names that end with a specific string

You can apply the string endswith() function with the help of the .str accessor on df.columns to check if column names (of a pandas dataframe) end with a specific string.

You can use the .str accessor to apply string functions to all the column names in a pandas dataframe.

Pass the end string as an argument to the endswith() function. The following is the syntax.

# get column names that end with a specific string, s
df.columns[df.columns.str.endswith(s)]

The idea is to get a boolean array using df.columns.str.endswith() and then use it to filter the column names in df.columns.

Alternatively, you can use a list comprehension to iterate through the column names and check if the column name ends with the specified string or not.

Examples

Let’s now look at some examples of using the above syntax.

First, we will create a pandas dataframe that we will be using throughout this tutorial.

import pandas as pd

# employee data
data = {
    "Name_Emp": ["Jim", "Dwight", "Angela", "Tobi"],
    "Age_Emp": [26, 28, 27, 32],
    "Department": ["Sales", "Sales", "Accounting", "HR"]
}

# create pandas dataframe
df = pd.DataFrame(data)

# display the dataframe
df

Output:

employee dataframe with some column names ending in "_Emp"

Here, we created a dataframe with information about some employees in an office. The dataframe has the columns – “Name_Emp”, “Age_Emp”, and “Department”.

Example 1 – Get column names that end with a specific string

Let’s get the column names in the above dataframe that end with the string “_Emp” in their column labels.

We’ll apply the string endswith() function with the help of the .str accessor to df.columns.

# check if column name ends with the string, "_Emp"
df.columns.str.endswith("_Emp")

Output:

array([ True,  True, False])

You can see that we get a boolean array indicating which columns in the dataframe end with the string “_Emp”.

We can use the above boolean array to filter df.columns to get only the columns that end with the specified string (in this example, “_Emp”)

# get column names that end with the string, "_Emp"
df.columns[df.columns.str.endswith("_Emp")]

Output:

Index(['Name_Emp', 'Age_Emp'], dtype='object')

We get the column names ending with “_Emp” in the above dataframe.

Example 2 – Get column names that end with a specific string using list comprehension

Alternatively, we can use a list comprehension to iterate through the column names in df.columns and select the ones that end with the given string.

# get column names that end with the string, "_Emp"
[col for col in df.columns if col.endswith("_Emp")]

Output:

['Name_Emp', 'Age_Emp']

We get the column names that end with “_Emp”. The “Name_Emp” and the “Age_Emp” columns are the only ones that end with the string “_Emp” in the above dataframe.

Summary

In this tutorial, we looked at how to get the column names that end with a specified string in a pandas dataframe. The following are the key takeaways –

  • Use the string endswith() function (applied using the .str accessor on df.columns) to check if a column name ends with a given string or not (and use this result to filter df.columns).
  • You can also get column names that end with a specified string with the help of a list comprehension.

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Author

  • Piyush

    Piyush is a data scientist passionate about using data to understand things better and make informed decisions. In the past, he's worked as a Data Scientist for ZS and holds an engineering degree from IIT Roorkee. His hobbies include watching cricket, reading, and working on side projects.