How to fill a pandas column with a list?

In this tutorial we will learn how to append the contents of a Python list to a pandas DataFrame.

We will start by creating a simple DataFrame and a Python list. You can use both to follow along with this example.

import pandas as pd

stamps = pd.date_range(start='4/1/2023', periods = 6, freq = 'B' )
interviews = [261, 183, 232, 271, 267, 275]

#Initialize the DataFrame
campaign  = pd.DataFrame (dict (interview_date = stamps, num_interviews = interviews))

# create a Python list
domain = ['Python', 'R', 'Javascript']*2

#visualize the DataFrame
campaign .head()

Assign a Python list to a DataFrame

From my experience, the easiest ways to append a list as a column of a Pandas DataFrame is to use the assign() df method.

The syntax goes as following:

campaign = campaign.assign(domain = domain)

This effectively adds a new column to the DataFrame and assigns the list values to it. If we take a look at the DataFrame head we’ll see the following:

campaign.head()

	interview_date	num_interviews	domain
0	2023-04-03	261	Python
1	2023-04-04	183	R
2	2023-04-05	232	Javascript
3	2023-04-06	271	Python
4	2023-04-07	267	R
5	2023-04-10	275	Javascript

A common error that happens when using assign, is that you don’t pass the correct parameters to assign. This render the following TypeError exception:

# TypeError: assign() takes 1 positional argument but 2 were given

Replace column with list values

You can use the assign method also to replace an existing column values with another list.

Let’s define a new list:

lang = ['Python', 'R', ]*3

We can assign the lang list to the already populated domain column:

campaign =  campaign.assign(domain=lang)

Here’s the result – Note the new values in the domain column:

	interview_date	num_interviews	domain
0	2023-04-03	261	Python
1	2023-04-04	183	R
2	2023-04-05	232	Python
3	2023-04-06	271	R
4	2023-04-07	267	Python
5	2023-04-10	275	R

Replace column with random values from list

Next case is that you would like to replace values in a new or existing column / Series with random picks from a list. We will use the random module of Python to generate a random list of languages which we will then assign to our column.

import random
# generate a list of random entries - number of entries equal to the number of df rows.
random_lang = random.sample(domain, len(campaign))

# assign to the df column
campaign.assign(domain=random_lang)

Export column values to a list of strings

You can easily list all column values by exporting those:

campaign['domain'].tolist()

This will return a Python list containing the Series values:

['Python', 'R', 'Python', 'R', 'Python', 'R']

Fill DataFrame columns with a value

You can insert a single value to all your DataFrame column cells.

campaign = campaign.assign(domain = 'Python')

Assign list content to a cell

We can use the at function to assign the contents of a list to a specific cell in our DataFrame. Note that we are converting the list to a string before inserting into the cell:

campaign.at[2,'domain'] = str(['Python', 'R',])

Note: As you can see, we are not able to insert a list directly into a DataFrame cell; and need to convert lists to Python strings, before storing its value in the DataFrame. But that said – that is not a recommended modeling practice which can lead to performance issues when querying and analyzing our data. When in need to included lists in a tabular format, consider working with dictionaries.

Follow up learning:

How to verify if a DataFrame cell contains a specific value?