How to create a list from a series in Pandas?

In this tutorial we’ll learn how to use Python in order to convert a Pandas Series object to a Python list. We’ll then explore additional cases such as casting a list to a Set and to a Numpy array.

Creating an Example Series object

Let’s start by creating some example data:

# import the Pandas library into your Python environment
import pandas as pd

# define list
names = ['C-Sharp', 'Go', 'Java', 'Javascript', 

# use Pandas to create a series
languages  = pd.Series(names)


Here is the Series object that we have constructed:

0       C-Sharp
1            Go
2          Java
3    Javascript
4    Javascript

dtype: object

Convert Series to list

In order to convert our Series to a list, we use the Series method to_list(); as shown below:

lang_lst = languages.values.tolist()

Here’s our list of strings:

['C-Sharp', 'Go', 'Java', 'Javascript', 

Series to list with index

Next, we would like to go ahead and convert the Series index to a list and then zip it with the Series values list that we have exported in the previous step.

lang_idx_list = languages.index.tolist()

This will result in the following:\ list

[0, 1, 2, 3, 4]

Now we can go ahead and zip the Series index and value lists, to a list of tuples:

merge_lang_list = list(zip(lang_idx_list,lang_lst))

Here’s the result:

[(0, 'C-Sharp'), (1, 'Go'), (2, 'Java'), (3, 'Javascript'), (4, 'Javascript')]

Pandas Series to Python set

As needed, we can convert our Series to a Python set. THis is helpful for example, if we would like to find unique occurrences in the Series. Here’s a simple example:

languages_set = set(languages.tolist())
{'Javascript', 'Go', 'Java', 'C-Sharp'}

Pandas Series to Numpy Array

Converting a Series object to a Numpy array is relatively simple with the to_numpy Series method.

lang_array = pd.Series.to_numpy(languages)

Additional learning