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

The available R engines

There is more than one R distribution available on the market that you can use for free for your advanced analytics projects. In this section, we'll explore the main details of each of them.

The CRAN R distribution

When it comes to installing the R engine, we almost always think of the open source software environment par excellence, developed by a collective of contributors over the years, known as CRAN R, also called base R ( To be exact, the Comprehensive R Archive Network (CRAN) is a network of web servers and FTP servers around the world, whose goal is to preserve multiple identical and up-to-date versions of the R source code and the entire ecosystem of R packages developed by the community, along with all the R documentation.

One of the biggest advantages of CRAN R is its very active community of developers. Their contribution to the creation of new packages on CRAN is invaluable. That's why if you think...