Real Python: Microsoft Power BI and Python: Two Superpowers Combined

Microsoft Power BI is an interactive data analysis and visualization tool that’s used for business intelligence (BI) and that you can now script with Python. By combining these two technologies, you can extend Power BI’s data ingestion, transformation, augmentation, and visualization capabilities. In addition, you’ll be able to bring complex algorithms shipped with Python’s numerous data science and machine learning libraries to Power BI.

In this tutorial, you’ll learn how to:

• Install and configure the Python and Power BI environment
• Use Python to import and transform data
• Make custom visualizations using Python
• Reuse your existing Python source code
• Understand the limitations of using Python in Power BI

Whether you’re new to Power BI, Python, or both, you’ll learn how to use them together. However, it would help if you knew some Python basics and SQL to benefit fully from this tutorial. Additionally, familiarity with the pandas and Matplotlib libraries would be a plus. But don’t worry if you don’t know them, as you’ll learn everything you need on the job.

While Power BI has potential across the world of business, in this tutorial, you’ll focus on sales data. Click the link below to download a sample dataset and the Python scripts that you’ll be using in this tutorial:

Preparing Your Environment

To follow this tutorial, you’ll need Windows 8.1 or later. If you’re currently using macOS or a Linux distribution, then you can get a free virtual machine with an evaluation release of the Windows 11 development environment, which you can run through the open-source VirtualBox or a commercial alternative.

In this section, you’ll install and configure all the necessary tools to run Python and Power BI. By the end of it, you’ll be ready to integrate Python code into your Power BI reports!

Install Microsoft Power BI Desktop

Microsoft Power BI is a collection of various tools and services, some of which require a Microsoft account, a subscription plan, and an Internet connection. Fortunately for you, in this tutorial, you’ll use Microsoft Power BI Desktop, which is completely free of charge, doesn’t require a Microsoft account, and can work offline just like a traditional office suite.

There are a few ways in which you can obtain and install Microsoft Power BI Desktop on your computer. The recommended approach, which is arguably the most convenient one, is to use Microsoft Store, accessible from the Start menu or its web-based storefront:

By installing Power BI Desktop from the Microsoft Store, you’ll ensure automatic and quick updates to the latest Power BI versions without having to be logged in as the system’s administrator. However, if that method doesn’t work for you, then you can always try downloading the installer from the Microsoft Download Center and running it manually. The executable file is roughly four hundred megabytes in size.

Once you have the Power BI Desktop application installed, launch it, and you’ll be greeted with a welcome screen similar to the following one:

Don’t worry if the Power BI Desktop user interface feels intimidating at first. You’ll get to know the basics as you make your way through the tutorial.

Install Microsoft Visual Studio Code

Microsoft Power BI Desktop offers only rudimentary code editing features, which is understandable since it’s mainly a data analysis tool. It doesn’t have intelligent contextual suggestions, auto-completion, or syntax highlighting for Python, all of which are invaluable when working with code. Therefore, you should really use an external code editor for writing anything but the most straightforward Python scripts in Power BI.

Feel free to skip this step if you already use an IDE like PyCharm or if you don’t need any of the fancy code editing features in your workflow. Otherwise, consider installing Visual Studio Code, which is a free, modern, and extremely popular code editor. Because it’s made by Microsoft, you can quickly find it in the Microsoft Store:

Microsoft Visual Studio Code, or VS Code as some like to call it, is a universal code editor that supports many programming languages through extensions. It doesn’t understand Python out of the box. But when you open an existing file with Python source code or create a new file and select Python as the language in VS Code, then it’ll prompt you to install the recommended set of extensions for Python:

After you confirm and proceed, VS Code will ask you to specify the path to your Python interpreter. In most cases, it’ll be able to detect one for you automatically. If you haven’t installed Python on your computer yet, then check out the next section, where you’ll also get your hands on pandas and Matplotlib.