2 Easy Methods For Installing Pandas on Your Windows Machine

If you‘re a developer, you’ll need to install tools to help in the development process. However, when it comes to installing pandas in Python, things can get complex. But don‘t worry, we’ve got your back! In this post, we'll show you how to install pandas in Python using the two most common methods step-by-step.

Before we get started, it‘s important to note that this post assumes you already have Python installed. If you don’t, head over to the Python website and download the installer. Once you have Python installed, you're ready to get started with installing pandas.

So, let‘s get started with installing pandas. We’ll also share resources to help you troubleshoot any installation errors you may encounter.

How to Install Pandas Using PIP

Begin by opening your CMD terminal with the newest version of Python installed. If you can‘t locate it, try the Windows search bar. After you’ve found and run the program, you should see something like this.

With the command prompt open and your terminal ready, the only thing left to do is type the following command:

pip install pandas

The command is straightforward, but let's dissect it to see how it works. Pip is an abbreviation that stands for “preferred installer program.” This refers to a package manager that comes with new versions of Python. It allows you to effortlessly install any Python module for software development.

The next term is a directive that informs the package management of your intentions. The term following that is the name of the package you want to edit; in this example, the package is named pandas.

This piece of code instructs Python pip to find and install the panda‘s package. Once you’ve entered it, press the enter key and wait for the installation to complete.

When the installation is finished, you will receive a notification informing you of the process's success or failure. The image below depicts what your message may look like if the installation is successful.

The above command indicates that the procedure installed pandas and any dependencies successfully.

Here's an example of code you can use to test that Pandas is installed:

However, this is not the only package manager available for installing pandas. There is another popular among Python developers. We'll explore this alternative below.

How to Install Pandas in Anaconda

The Python community has endorsed the Anaconda package. This tool has numerous useful capabilities for working with big volumes of data. It also allows you to create environments to help you isolate tasks with various tools.

Anaconda reduces software dependencies that may not be required for some applications, which are outside the scope of this post.

Let's take a look at the installation process for the Anaconda program. To begin, you must first go to the Anaconda website. Then, download the necessary installation for Windows and your current Python version.

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Once you've found the installation page for your setup, download and install the software. Then, as seen below, go through the setup procedure and uncheck the option Add Anaconda to my PATH environment variable. See below.

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To complete the installation at this stage, click the install button and follow the remaining instructions. After completing these steps, you will have instant access to the panda's library and any dependencies.

To begin utilizing Anaconda in your work, launch the application and navigate to your dashboard to access your panda's installation.

Using Pandas on Windows

So which installation method should you use?

They each serve distinct functions. Installing Anaconda is strongly advised if you work with big volumes of data, such as data analysis or machine learning. However, in most other circumstances, installing pandas using the pip manager should be an acceptable choice.

Your next step may be to create your own Panda data frame or to learn more about Panda syntax. If you used Anaconda to set up your pandas installation, spend some time becoming acquainted with the program's capabilities and functions.