How to Set Up Your Python Environment

4 minutes read


Hello developers, Python, a friendly yet powerful language, shines in many fields, including data analysis. In our data-rich world, deriving insights from data is an in-demand skill, and Python, with its wide array of tools and libraries, is a top pick for data analysts around the globe.

In this article, we’ll guide you through setting up your Python environment, from picking the right Python version to setting up your code editor and the Jupiter Notebook. Whether you’re a Windows or Mac user, we’ve got you covered.

By the end, you’ll have a ready-to-go Python environment. It’s the first step in your exciting data analysis journey! If you need more help, don’t forget to check out the official Python documentation, VSCode manual, PyCharm manual, and Jupiter notebook user guide.

Python Installation

Python comes in many versions, but don’t worry, you won’t have to figure out which one is best for you because we’re here to help! For our journey into the realm of data analysis, we suggest Python 3.X, specifically Python 3.9, due to its stability and the range of features it offers.

Let’s get it installed, shall we?

For Windows users

First, visit the official Python website’s downloads page. Look for Python 3.9 and click on the download link.

Once downloaded, run the installer. A word of advice: Check the box that says “Add Python 3.9 to PATH” before you click on ‘Install Now‘. This ensures Python is easily accessible from any command line run in Windows. Sit back and relax while the installer works its magic.

For Mac users

Lucky you! Most Macs come with Python pre-installed. But to ensure you’re using the right version, open your Terminal (You can find it in Applications > Utilities > Terminal) and type python --version. Press Enter.

If Python 3.9 is installed, you’ll see it as your version. If not, don’t worry! You can install it just like our Windows friends. Visit the Python website’s downloads page, download Python 3.9, and run the installer. Wait while your Mac upgrades its Python game.

And voila! You’ve installed Python on your machine, which is the first big step on your data analysis path. Well done!

Selecting a Code Editor

A code editor is where you’ll write your Python scripts. It’s like a canvas for a painter but instead of colors, you’ll be using code to paint data analysis masterpieces.

Now, there are several code editors out there. You might have heard about Visual Studio Code (VSCode), PyCharm, Sublime Text, or Atom. But how do you know which one is right for you?

Let’s simplify things. For beginners, we usually recommend VSCode or PyCharm. They are user-friendly, highly customizable, and offer many features that make coding a breeze. Plus, they have fantastic Python support!

For VSCode fans

Are you a fan of a sleek interface, extensibility, and speed? VSCode might be your match. Here’s how to get it:

Head over to the VSCode download page and choose the version suitable for your OS. Run the installer and follow the prompts.

Once installed, open VSCode, and visit the extensions tab (the square icon on the left). Search for ‘Python’ and install the official Python extension by Microsoft.

Congratulations, your VSCode is ready for some Python action!

For PyCharm fans

If you prefer an IDE specifically designed for Python that comes with a ton of Python-specific features out of the box, then PyCharm is your guy.

Visit the PyCharm download page, select your OS, and download the community edition (it’s free!). Run the installer and follow the prompts. Upon successful installation, PyCharm is set to interpret Python code right away!

There you have it – your code editor is set up and ready to accompany you on your data analysis adventure.

Installing and Using the Jupiter Notebook

Now that Python is up and running and you’ve chosen your code editor, it’s time to add another fantastic tool: the Jupyter Notebook. It’s like a science lab where you experiment, observe the results, and keep improving!

Jupyter Notebook is an open-source application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text. What’s great about it, especially for data analysis, is that it allows you to see the output of your code right there, step by step, as you’re creating it. Sounds exciting? Let’s get it installed:

Step 1: Install Jupyter Notebook:

The easiest way to install Jupyter is with Anaconda, a Python distribution that comes with everything you need for data analysis.

  • Download the Anaconda installer for your OS.
  • Run the installer and follow the prompts.
  • After successful installation, you have not just Jupyter, but also Python and some other super useful data analysis libraries pre-installed!

Step 2: Launch Jupyter Notebook:

  • Open your terminal (or Anaconda Prompt for Windows users).
  • Type jupyter notebook and hit Enter.
  • A new browser window or tab will open with the Jupyter Notebook interface.

Step 3: Create your first notebook:

  • Click on ‘New’ > ‘Python 3’. A new tab will open with your fresh notebook.
  • You’ll see a cell where you can start typing Python code. Write a simple print('Hello, Data Analysis!') and click ‘Run‘ or press Shift+Enter.

Congratulations! You’ve just run your first piece of Python code in Jupyter Notebook!

This interactive environment will be your best friend in the data analysis journey, allowing you to write code, run it, see the results, and write notes (in Markdown) – all in the same place!

Further Reading


Congratulations! You’ve successfully navigated through the essential steps of setting up your Python environment, from the installation of Python, and choosing your trustworthy code editor, to preparing your interactive Jupyter Notebook. Every grand journey begins with a single step, and you’ve made several today toward becoming a competent data analyst. Happy Coding!

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