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If you’re working with Python for the first time, you might be interested in learning how to store data. For example, you might want to collect a list of exam scores, so you can average them. If so, the list data structure gets the job done. But, how do you create a list in Python? That’s the topic of today’s article.

As it turns out, there are a few different ways to create a list. First, we could create a list directly as follows: my_list = [0, 1, 2]. Alternatively, we could build that same list using a list comprehension: my_list = [i for in range(0, 3)]. Finally, if we need more control, we could build up our list using a loop and append(). In the remainder of this article, we’ll look at each solution in detail.

Table of Contents

Problem Description

When it comes to working with different types of data in Python, it’s helpful to have some way to manage it. Luckily, Python supports and easy-to-use data structure for storing all kinds of data: the list.

In Python, the list is an array-like data structure which is dynamic in size. In other words, we don’t have to worry about knowing how many items we have before we create our list. For those of us who work in languages like Java or C, we’re used to being stuck with the following syntax:

Luckily, Python has a much cleaner syntax. Specifically, we have two options:

1. Create a list using the constructor: my_list = list()
2. Or, create a list using an empty list: my_list = []

But, what if we want to populate that list? That’s the problem we’ll be tackling today. Fortunately, there are several solutions.

Solutions

At this point, we’ll take a look at a few ways to create a list in Python. As always, we’ll work our way from straightforward to more complex solutions. After that, we’ll compare each solution’s performance. At any rate, let’s dive in!

Create a List by Hand

One of the nice things about Python is that we can create a list by hand. In other words, if we know how we want to populate the list, we can write those contents out directly:

In one line, we managed to create a variable called my_list. Then, we assigned it a literal list which contains a few Penguins players.

Now, if we want to interact with this list, we can. For instance, we could get any of the following information:

• First player: my_list[0]
• Last player: my_list[-1]
• First two players: my_list[:2]
• Every other player: my_list[::2]

If you’re interested in articles on list interaction, I’ve written a thing or two:

Otherwise, let’s look at a few other solutions.

Create a List with a Loop

Since lists in Python are dynamic, we don’t actually have to define them by hand. In other words, we can create an empty list and add items to it with a loop:

Create A List online, free

Here, we’ve created an empty list and assigned it to my_list. Then, we run a loop over a range of numbers between 0 and 9. Each number is then added to the list using append().

When this code snippet is all said and done, we’ll have a list that looks something like the following:

As we can probably image, we could use this loop to populate a list in just about any way we want. For example, we could modify our range to give us only even values:

In this case, my_list would only contain even numbers between 0 and 9:

Likewise, there are a ton of different ways to add items to lists as well. If you’re interested in that sort of thing, I have an article on that.

Create a List with a List Comprehension

One of my favorite ways to create a list is using the list comprehension functionality. Essentially, it’s a compressed loop syntax that lets us generate simple lists. For instance, the first loop example could be written as a list comprehension as follows:

Now, instead of manually appending items to a list, this expression handles all the heavy lifting. As a result, we can focus on modifying the expression to do fun things like scale all values in the range by 3:

This expression will generate a list that looks like the following:

While I’d be happy to dig into all the details, I already have a fun article and even a video which cover list comprehensions in depth. Check those resources out if you’re interested.

Performance

Now that we have a few solutions, let’s compare their performance. To do that, we’ll need to generate some strings:

At this point, all we have to do is import the timeit library, so we can begin testing:

And, there you have it! The quickest way to create a list is to declare it statically. That said, if you have to generate a list, the list comprehension seems to be the way to go.

Challenge

Now that you know how to create a list, I have a little challenge for you: create a list which contains the first 100 terms of the fibonacci sequence. For the purposes of this exercise, we’ll assume the first two terms are 1 and 1.

Feel free to use any solution from this article to generate your list. For example, you could compute the first 100 terms by hand and build up your list statically, Alternatively, you might choose to use a loop or even recursion to populate your list.

If you manage to generate the list using a list comprehension, let me know! I have no idea if that’s possible–at least not without doing some really nasty stuff. After all, you can’t access elements of the list as you’re building it, so it would be tough to track the previous values. That said, you may be able to take advantage of the new walrus operator or some outside state tracking mechanism.

To kick things off, here’s a solution by our friend, Muhimen:

If you come up with something different, feel free to post it on Twitter using the #RenegadePython hashtag! If I see it, I’ll be sure to give it a share.

A Little Recap

At this point, we’ve reached the end of the article. As always, I like to share a list of all the solutions for your perusal:

And with that, all I ask is that you take a trip over to my post about different ways to support the site. If you could chip in, that would really help the site grow. Otherwise, check out some of these Python resources on Amazon (ad):

While you’re here, consider checking out some of these related articles:

Thanks for sticking around! I appreciate it.

How to Python (40 Articles)—Series Navigation

The How to Python tutorial series strays from the usual in-depth coding articles by exploring byte-sized problems in Python. In this series, students will dive into unique topics such as How to Invert a Dictionary, How to Sum Elements of Two Lists, and How to Check if a File Exists.

Each problem is explored from the naive approach to the ideal solution. Occasionally, there’ll be some just-for-fun solutions too. At the end of every article, you’ll find a recap full of code snippets for your own use. Don’t be afraid to take what you need!

If you’re not sure where to start, I recommend checking out our list of Python Code Snippets for Everyday Problems. In addition, you can find some of the snippets in a Jupyter notebook format on GitHub,

If you have a problem of your own, feel free to ask. Someone else probably has the same problem. Enjoy How to Python!

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

Step 2 : Convert the Series object to the list

Make A 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.
Output:
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.
If you get that error, then please check your Pandas version, you may be using pandas version less than 24.
Upgrade you pandas to the latest version using the following command,

Make A List In R

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

Another way is converting a Dataframe column into a list is,
Output
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,
It returns a Series object.

Step 2: Get a Numpy array from a series object using Series.Values
Output:
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,
Output:
This is how we selected our column ‘Name’ from Dataframe as a Numpy array and then turned it to a list.

Make A Listing

The complete example is as follows,
Output:

How To Create A Sharepoint List