Get Column Names as List in Pandas DataFrame

Python Pandas, the short form from Panel Data (3D container of dataset), is a python library which contains in-built methods to manipulate, transform, visualize and analyze data. The data in the Pandas columns can contain alpha-numerical characters or logical data and can be of the similar type. The following programs illustrate to get DataFrame column headers using various methods. The fastest and simplest way to get column header name is:

DataFrame.columns.values.tolist()

examples: Create a Pandas DataFrame with data

import pandas as pd import numpy as np df = pd.DataFrame() df['Name'] = ['John', 'Doe', 'Bill','Jim','Harry','Ben'] df['TotalMarks'] = [82, 38, 63,22,55,40] df['Grade'] = ['A', 'E', 'B','E','C','D'] df['Promoted'] = [True, False,True,False,True,True] df

Name TotalMarks Grade Promoted 0 John 82 A True 1 Doe 38 E False 2 Bill 63 B True 3 Jim 22 E False 4 Harry 55 C True 5 Ben 40 D True

Get list of column headers from a Pandas DataFrame

df.columns.values.tolist()

['Students_name', 'TotalMarks', 'Grade', 'IsPromoted']

list(df.columns)

['Students_name', 'TotalMarks', 'Grade', 'IsPromoted']

If you want column header names in Python Tuple :

*df,

('Students_name', 'TotalMarks', 'Grade', 'IsPromoted')

When you use *df, please note the trailing comma. If you want column header names in Python Set :

{*df}

{'Grade', 'IsPromoted', 'Students_name', 'TotalMarks'}

If you want column header names in Python List :

[*df]

['Students_name', 'TotalMarks', 'Grade', 'IsPromoted']

Pandas DataFrame follows the dict-like convention of iterating over the "keys" of the objects. So you can get column header names as:

df.keys()

Index(['Students_name', 'TotalMarks', 'Grade', 'IsPromoted'], dtype='object')

If you want sorted column header names :

sorted(df)

['Grade', 'IsPromoted', 'Students_name', 'TotalMarks']

It is important to note that sorted(df) does not preserve the original order of the dataframe column header names. For that, you should use list(df) instead.

Next : How to add new columns to Pandas dataframe?

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