In this article, we will discuss different ways to convert a dataframe column into a list.

Fits of all, create a dataframe object that we are going to use in this example,

import pandas as pd

# List of Tuples
students = [('jack', 34, 'Sydney', 155),
           ('Riti', 31, 'Delhi', 177.5),
           ('Aadi', 16, 'Mumbai', 81),
           ('Mohit', 31, 'Delhi', 167),
           ('Veena', 12, 'Delhi', 144),
           ('Shaunak', 35, 'Mumbai', 135),
           ('Shaun', 35, 'Colombo', 111)
           ]

# Create a DataFrame object
student_df = pd.DataFrame(students, columns=['Name', 'Age', 'City', 'Score'])

print(student_df)

Output:
      Name  Age     City  Score
0     jack   34   Sydney  155.0
1     Riti   31    Delhi  177.5
2     Aadi   16   Mumbai   81.0
3    Mohit   31    Delhi  167.0
4    Veena   12    Delhi  144.0
5  Shaunak   35   Mumbai  135.0
6    Shaun   35  Colombo  111.0

Now how to fetch a single column out of this dataframe and convert it to a python list?

There are different ways to do that, lets discuss them one by one.

Convert a Dataframe column into a list using Series.to_list()

To turn the column ‘Name’ from the dataframe object student_df to a list in a single line,

# select a column as series and then convert it into a column
list_of_names = student_df['Name'].to_list()

print('List of Names: ', list_of_names)
print('Type of listOfNames: ', type(list_of_names))

Output
List of Names:  ['jack', 'Riti', 'Aadi', 'Mohit', 'Veena', 'Shaunak', 'Shaun']
Type of listOfNames:  <class 'list'>

What did happen here?

How did it work?

Let’s break down the above line into steps,

Step 1: Fetch a column as series

Select the column ‘Name’ from the dataframe using [] operator,

# Select column 'Name' as series object
names = student_df['Name']

print(names)
print(type(names))

Output:
0       jack
1       Riti
2       Aadi
3      Mohit
4      Veena
5    Shaunak
6      Shaun
Name: Name, dtype: object
<class 'pandas.core.series.Series'>

It returns a Series object names, and we have confirmed that by printing its type.

Step 2 : Convert the Series object to the list

Series class provides a function Series.to_list(), which returns the contents of Series object as list. Use that to convert series names into a list i.e.

# Convert series object to a list
list_of_names = names.to_list()

print('List of Names: ', list_of_names)
print('Type of listOfNames: ', type(list_of_names))

Output:
List of Names:  ['jack', 'Riti', 'Aadi', 'Mohit', 'Veena', 'Shaunak', 'Shaun']
Type of listOfNames:  <class 'list'>

This is how we converted a dataframe column into a list.

Important Note:

It might be possible that it gives you an error i.e.

AttributeError: 'Series' object has no attribute 'to_list'

If you get that error, then please check your Pandas version, you may be using pandas version less than 24.
Import pandas as pd

print(pd.__version__)

Upgrade you pandas to the latest version using the following command,
pip install --upgrade pandas

Convert a Dataframe column into a list using numpy.ndarray.tolist()

Another way is converting a Dataframe column into a list is,

# Convert column Name to a Numpy Array and then to a list
list_of_names = student_df['Name'].values.tolist()

print('List of Names: ', list_of_names)
print('Type of listOfNames: ', type(list_of_names))

Output
List of Names:  ['jack', 'Riti', 'Aadi', 'Mohit', 'Veena', 'Shaunak', 'Shaun']
Type of listOfNames:  <class 'list'>

We converted the column ‘Name’ into a list in a single line. Let’s see what happened inside it,

How did it work?

Let’s break down the above line into steps,

Step 1: Select a column as a Series object

Select the column ‘Name’ from the dataframe using [] operator,

student_df['Name']

It returns a Series object.

Step 2: Get a Numpy array from a series object using Series.Values

# Select a column from dataframe as series and get a numpy array from that
names = student_df['Name'].values

print('Numpy array: ', names)
print('Type of namesAsNumpy: ', type(names))

Output:
Numpy array:  ['jack' 'Riti' 'Aadi' 'Mohit' 'Veena' 'Shaunak' 'Shaun']
Type of namesAsNumpy:  <class 'numpy.ndarray'>

Names is a numpy array, and we confirmed it by printing its types.

Step 3: Convert a Numpy array into a list

Numpy array provides a function tolist() to convert its contents to a list,

# Convert numpy array to a list
list_of_names = names.tolist()

print('List of Names: ', list_of_names)
print('Type of listOfNames: ', type(list_of_names))

Output:
List of Names:  ['jack', 'Riti', 'Aadi', 'Mohit', 'Veena', 'Shaunak', 'Shaun']
Type of listOfNames:  <class 'list'>

This is how we selected our column ‘Name’ from Dataframe as a Numpy array and then turned it to a list.

The complete example is as follows,

import pandas as pd

def main():
    # List of Tuples
    students = [('jack', 34, 'Sydney', 155),
               ('Riti', 31, 'Delhi', 177.5),
               ('Aadi', 16, 'Mumbai', 81),
               ('Mohit', 31, 'Delhi', 167),
               ('Veena', 12, 'Delhi', 144),
               ('Shaunak', 35, 'Mumbai', 135),
               ('Shaun', 35, 'Colombo', 111)
               ]

    # Create a DataFrame object
    student_df = pd.DataFrame(students, columns=['Name', 'Age', 'City', 'Score'])

    print("Contents of the Dataframe : ")
    print(student_df)

    print('Convert a Dataframe column into a list using Series.to_list()')

    # select a column as series and then convert it into a column
    list_of_names = student_df['Name'].to_list()

    print('List of Names: ', list_of_names)
    print('Type of listOfNames: ', type(list_of_names))

    print('How did it worked ?')

    # Select column 'Name' as series object
    names = student_df['Name']

    print(names)
    print(type(names))

    # Convert series object to a list
    list_of_names = names.to_list()

    print('List of Names: ', list_of_names)
    print('Type of listOfNames: ', type(list_of_names))

    print("Convert a Dataframe column into a list using numpy.ndarray.tolist()")

    # Convert column Name to a Numpy Array and then to a list
    list_of_names = student_df['Name'].values.tolist()

    print('List of Names: ', list_of_names)
    print('Type of listOfNames: ', type(list_of_names))

    print('How did it worked ?')

    # Select a column from dataframe as series and get a numpy array from that
    names = student_df['Name'].values

    print('Numpy array: ', names)
    print('Type of namesAsNumpy: ', type(names))

    # Convert numpy array to a list
    list_of_names = names.tolist()

    print('List of Names: ', list_of_names)
    print('Type of listOfNames: ', type(list_of_names))

if __name__ == '__main__':
   main()

Output:
Contents of the Dataframe :
      Name  Age     City  Score
0     jack   34   Sydney  155.0
1     Riti   31    Delhi  177.5
2     Aadi   16   Mumbai   81.0
3    Mohit   31    Delhi  167.0
4    Veena   12    Delhi  144.0
5  Shaunak   35   Mumbai  135.0
6    Shaun   35  Colombo  111.0
Convert a Dataframe column into a list using Series.to_list()
List of Names:  ['jack', 'Riti', 'Aadi', 'Mohit', 'Veena', 'Shaunak', 'Shaun']
Type of listOfNames:  <class 'list'>
How did it worked ?
0       jack
1       Riti
2       Aadi
3      Mohit
4      Veena
5    Shaunak
6      Shaun
Name: Name, dtype: object
<class 'pandas.core.series.Series'>
List of Names:  ['jack', 'Riti', 'Aadi', 'Mohit', 'Veena', 'Shaunak', 'Shaun']
Type of listOfNames:  <class 'list'>
Convert a Dataframe column into a list using numpy.ndarray.tolist()
List of Names:  ['jack', 'Riti', 'Aadi', 'Mohit', 'Veena', 'Shaunak', 'Shaun']
Type of listOfNames:  <class 'list'>
How did it worked ?
Numpy array:  ['jack' 'Riti' 'Aadi' 'Mohit' 'Veena' 'Shaunak' 'Shaun']
Type of namesAsNumpy:  <class 'numpy.ndarray'>
List of Names:  ['jack', 'Riti', 'Aadi', 'Mohit', 'Veena', 'Shaunak', 'Shaun']
Type of listOfNames:  <class 'list'>

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