You can use one of the following four methods to list all column names of a pandas DataFrame:

Method 1: Use Brackets

[column for column in df]

Method 2: Use tolist()

df.columns.values.tolist()

Method 3: Use list()

list(df)

Method 4: Use list() with column values

list(df.columns.values)

The following examples show how to use each of these methods with the following pandas DataFrame:

import pandas as pd
#create DataFrame
df = pd.DataFrame({'points': [25, 12, 15, 14, 19, 23],
                   'assists': [5, 7, 7, 9, 12, 9],
                   'rebounds': [11, 8, 10, 6, 6, 5],
                   'blocks': [6, 6, 3, 2, 7, 9]})

#view DataFrame
df

	points	assists	rebounds blocks
0	25	5	11	 6
1	12	7	8	 6
2	15	7	10	 3
3	14	9	6	 2
4	19	12	6	 7
5	23	9	5	 9

Method 1: Use Brackets

The following code shows how to list all column names of a pandas DataFrame using brackets:

[column for column in df]

['points', 'assists', 'rebounds', 'blocks']

Method 2: Use tolist()

The following code shows how to list all column names using the .tolist() function:

df.columns.values.tolist()

['points', 'assists', 'rebounds', 'blocks'] 

Method 3: Use list()

The following code shows how to list all column names using the list() function:

list(df)

['points', 'assists', 'rebounds', 'blocks']

Method 4: Use list() with column values

The following code shows how to list all column names using the list() function with column values:

list(df.columns.values)

['points', 'assists', 'rebounds', 'blocks']

Notice that all four methods return the same results.

Note that for extremely large DataFrames, the df.columns.values.tolist() method tends to perform the fastest.

The following tutorials explain how to perform other common functions with columns of a pandas DataFrame: