Get a List of all Column Names in Pandas DataFrame

Here are two approaches to get a list of all the column names in Pandas DataFrame:

(1) Using list(df)

my_list = list(df)

(2) Using df.columns.values.tolist()

my_list = df.columns.values.tolist()

The Example

To start with a simple example, let’s create a DataFrame with 3 columns:

import pandas as pd

data = {'Name': ['Bill', 'Maria', 'David', 'James', 'Mary'],
        'Age': [32, 45, 27, 59, 37],
        'Country': ['Spain', 'Canada', 'Brazil', 'UK', 'France']
        }

df = pd.DataFrame(data)

print(df)

Once you run the above code, you’ll see the following DataFrame with the 3 columns:

    Name  Age  Country
0   Bill   32    Spain
1  Maria   45   Canada
2  David   27   Brazil
3  James   59       UK
4   Mary   37   France

Using list(df)

You may use the first approach by adding my_list = list(df) to the code:

import pandas as pd

data = {'Name': ['Bill', 'Maria', 'David', 'James', 'Mary'],
        'Age': [32, 45, 27, 59, 37],
        'Country': ['Spain', 'Canada', 'Brazil', 'UK', 'France']
        }

df = pd.DataFrame(data)

my_list = list(df)

print(my_list)

You’ll now see the List that contains the 3 column names:

['Name', 'Age', 'Country']

Optionally, you can quickly verify that you got a list by adding print (type(my_list)) at the bottom of the code:

import pandas as pd

data = {'Name': ['Bill', 'Maria', 'David', 'James', 'Mary'],
        'Age': [32, 45, 27, 59, 37],
        'Country': ['Spain', 'Canada', 'Brazil', 'UK', 'France']
        }

df = pd.DataFrame(data)

my_list = list(df)

print(my_list)
print(type(my_list))

You’ll then be able to confirm that you got a list:

['Name', 'Age', 'Country']
<class 'list'>

Using df.columns.values.tolist()

Alternatively, you may apply the second approach by adding my_list = df.columns.values.tolist() to the code:

import pandas as pd

data = {'Name': ['Bill', 'Maria', 'David', 'James', 'Mary'],
        'Age': [32, 45, 27, 59, 37],
        'Country': ['Spain', 'Canada', 'Brazil', 'UK', 'France']
        }

df = pd.DataFrame(data)

my_list = df.columns.values.tolist()

print(my_list)
print(type(my_list))

As before, you’ll now get the list with the column names:

['Name', 'Age', 'Country']
<class 'list'>
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