Pandas DataFrame: Get list from DataFrame column headers

Last update on May 01 2025 12:54:48 (UTC/GMT +8 hours)

22. Getting List from Column Headers

Write a Pandas program to get list from DataFrame column headers.

Sample data:
exam_data = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],
'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],
'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],
'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}
labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']

Sample Solution :

Python Code :

import pandas as pd
import numpy as np
exam_data  = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],
        'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],
        'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],
        'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}
labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']
df = pd.DataFrame(exam_data , index=labels)
print(list(df.columns.values))

Sample Output:

['attempts', 'name', 'qualify', 'score']

Explanation:

The above code defines a dictionary 'exam_data' with keys 'name', 'score', 'attempts', and 'qualify' and their corresponding values as lists. It then defines a list of 'labels' and creates a Pandas DataFrame 'df' from the dictionary with the index set to the list of labels.

print(list(df.columns.values)): This line prints the list of column names in the DataFrame df.

For more Practice: Solve these Related Problems:

Write a Pandas program to get a list of all column headers and then convert them to uppercase.
Write a Pandas program to extract column names into a list and then sort this list alphabetically.
Write a Pandas program to retrieve column headers and then filter the list to only include headers that start with a given letter.
Write a Pandas program to get a list of column names and then create a mapping of each column to its data type.

Go to:

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Python-Pandas Code Editor:

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