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)
1
Section 1: Best Practices for Using R and Python in Power BI
5
Section 2: Data Ingestion and Transformation with R and Python in Power BI
11
Section 3: Data Enrichment with R and Python in Power BI
17
Section 3: Data Visualization with R in Power BI

Installing an IDE for R development

The need to install a state-of-the-art IDE for the development of code in Power BI comes from the need to have all the tools necessary to identify any bugs and to quickly test the results of code chunks on the fly.

Tip

It is strongly suggested to test your R code in the IDE and verify the results before using it in Power BI.

There are many IDEs for R development on the market. Some examples are R-Brain IDE (RIDE), IntelliJ IDEA, and Jupyter Lab, but it is estimated that over 90% of R programmers use RStudio as their primary IDE because of the countless features that simplify their daily work. That's why we suggest you also use this IDE to test the code you'll encounter throughout this book.

Installing RStudio

Installing RStudio on your machine is very simple:

  1. Go to https://rstudio.com/products/rstudio/download/ and click on DOWNLOAD under the RStudio Desktop column:

    Figure 2.9 – Go to the Download page of RStudio...