Book Image

Extending Power BI with Python and R

By : Luca Zavarella
Book Image

Extending Power BI with Python and R

By: Luca Zavarella

Overview of this book

Python and R allow you to extend Power BI capabilities to simplify ingestion and transformation activities, enhance dashboards, and highlight insights. With this book, you'll be able to make your artifacts far more interesting and rich in insights using analytical languages. You'll start by learning how to configure your Power BI environment to use your Python and R scripts. The book then explores data ingestion and data transformation extensions, and advances to focus on data augmentation and data visualization. You'll understand how to import data from external sources and transform them using complex algorithms. The book helps you implement personal data de-identification methods such as pseudonymization, anonymization, and masking in Power BI. You'll be able to call external APIs to enrich your data much more quickly using Python programming and R programming. Later, you'll learn advanced Python and R techniques to perform in-depth analysis and extract valuable information using statistics and machine learning. You'll also understand the main statistical features of datasets by plotting multiple visual graphs in the process of creating a machine learning model. By the end of this book, you’ll be able to enrich your Power BI data models and visualizations using complex algorithms in Python and R.
Table of Contents (22 chapters)
Section 1: Best Practices for Using R and Python in Power BI
Section 2: Data Ingestion and Transformation with R and Python in Power BI
Section 3: Data Enrichment with R and Python in Power BI
Section 3: Data Visualization with R in Power BI

Configuring Power BI Desktop to work with R

Once you have installed the R engines necessary for the development of your reports and the RStudio IDE, you must configure Power BI Desktop so that it properly references these tools. This is really a very simple task:

  1. In Power BI Desktop, go to the File menu, click on the Options and settings tab, and then click on Options:

    Figure 2.14 – Opening the Power BI Desktop Options and settings window

  2. In the Options window, click on the R scripting tab on the left. The contents of the panel on the right will update, giving you the option to select the R engine to reference and the R IDE to use for R visuals:

    Figure 2.15 – Choosing the engine and the IDE to work with in Power BI Desktop

  3. As you can see, Power BI Desktop automatically identifies the installed R engines and IDEs. For the moment, select the latest version of the engine (in our case, it is 4.0.2), in order to be aligned with the one already selected in RStudio...