You're reading from Extending Power BI with Python and R Ingest, transform, enrich, and visualize data using the power of analytical languages

Product type Paperback

Published in Nov 2021

Publisher Packt

ISBN-13 9781801078207

Length 558 pages

Edition 1st Edition

Languages

Python

Tools

Power BI

Concepts

Business Intelligence

Author (1):

Luca Zavarella

View More author details

Table of Contents (22) Chapters

Preface

1. Section 1: Best Practices for Using R and Python in Power BI

2. Chapter 1: Where and How to Use R and Python Scripts in Power BI FREE CHAPTER

3. Chapter 2: Configuring R with Power BI

4. Chapter 3: Configuring Python with Power BI

5. Section 2: Data Ingestion and Transformation with R and Python in Power BI

6. Chapter 4: Importing Unhandled Data Objects

7. Chapter 5: Using Regular Expressions in Power BI

8. Chapter 6: Anonymizing and Pseudonymizing Your Data in Power BI

9. Chapter 7: Logging Data from Power BI to External Sources

10. Chapter 8: Loading Large Datasets beyond the Available RAM in Power BI

11. Section 3: Data Enrichment with R and Python in Power BI

12. Chapter 9: Calling External APIs to Enrich Your Data

13. Chapter 10: Calculating Columns Using Complex Algorithms

14. Chapter 11: Adding Statistics Insights: Associations

15. Chapter 12: Adding Statistics Insights: Outliers and Missing Values

16. Chapter 13: Using Machine Learning without Premium or Embedded Capacity

17. Section 3: Data Visualization with R in Power BI

18. Chapter 14: Exploratory Data Analysis

19. Chapter 15: Advanced Visualizations

20. Chapter 16: Interactive R Custom Visuals

21. Other Books You May Enjoy

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 (https://cran.r-project.org). 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...