Python Pandas – Display all the column names in a DataFrame

To display all the column names in a Pandas DataFrame, use the DataFrame.columns attribute. This returns an Index object containing all column names.

Creating a DataFrame

First, let's create a sample DataFrame ?

import pandas as pd

# Create a DataFrame
dataFrame = pd.DataFrame({
    "Car": ['BMW', 'Audi', 'BMW', 'Lexus', 'Tesla', 'Lexus', 'Mustang'],
    "Place": ['Delhi','Bangalore','Hyderabad','Chandigarh','Pune', 'Mumbai', 'Jaipur'],
    "Units": [100, 150, 50, 110, 90, 120, 80]
})

print("DataFrame:")
print(dataFrame)

DataFrame:
       Car       Place  Units
0      BMW       Delhi    100
1     Audi   Bangalore    150
2      BMW   Hyderabad     50
3    Lexus  Chandigarh    110
4    Tesla        Pune     90
5    Lexus      Mumbai    120
6  Mustang      Jaipur     80

Using DataFrame.columns

Display all column names using the columns attribute ?

import pandas as pd

dataFrame = pd.DataFrame({
    "Car": ['BMW', 'Audi', 'BMW', 'Lexus', 'Tesla', 'Lexus', 'Mustang'],
    "Place": ['Delhi','Bangalore','Hyderabad','Chandigarh','Pune', 'Mumbai', 'Jaipur'],
    "Units": [100, 150, 50, 110, 90, 120, 80]
})

# Get all column names
print("Column names:")
print(dataFrame.columns)

Column names:
Index(['Car', 'Place', 'Units'], dtype='object')

Converting to List

Convert column names to a list for easier manipulation ?

import pandas as pd

dataFrame = pd.DataFrame({
    "Car": ['BMW', 'Audi', 'BMW', 'Lexus', 'Tesla', 'Lexus', 'Mustang'],
    "Place": ['Delhi','Bangalore','Hyderabad','Chandigarh','Pune', 'Mumbai', 'Jaipur'],
    "Units": [100, 150, 50, 110, 90, 120, 80]
})

# Convert column names to list
column_list = dataFrame.columns.tolist()
print("Column names as list:")
print(column_list)

Column names as list:
['Car', 'Place', 'Units']

Alternative Methods

Other ways to access column names ?

import pandas as pd

dataFrame = pd.DataFrame({
    "Car": ['BMW', 'Audi'],
    "Place": ['Delhi', 'Bangalore'],
    "Units": [100, 150]
})

# Method 1: Using columns attribute
print("Method 1 - columns:")
print(dataFrame.columns)

# Method 2: Using list() function
print("\nMethod 2 - list(columns):")
print(list(dataFrame.columns))

# Method 3: Using keys() method
print("\nMethod 3 - keys():")
print(dataFrame.keys())

Method 1 - columns:
Index(['Car', 'Place', 'Units'], dtype='object')

Method 2 - list(columns):
['Car', 'Place', 'Units']

Method 3 - keys():
Index(['Car', 'Place', 'Units'], dtype='object')

Comparison

Conclusion

Use DataFrame.columns to access column names as an Index object. Convert to list with tolist() when needed for further processing.