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 the Power BI service to work with R

As you learned in the The R engines used by Power BI section of this chapter, the Power BI service uses different R engines depending on whether the scripts are used in R visuals or in Power Query for data transformation. In the first case, the engine is pre-installed on the cloud; in the second case, you need to install the on-premises data gateway in personal mode on any machine of your choice in order to make the Power BI service communicate with the R engine you installed on that machine.

Installing the on-premises data gateway in personal mode

We have emphasized the fact that you will need to install the data gateway in personal mode for an important reason: R scripts are not supported for the on-premises data gateway in Enterprise mode.

In your case, you will install the data gateway on the same laptop on which you have installed the R engines and Power BI Desktop. The steps to do this are as follows:

  1. Make sure...