You're reading from Extending Power BI with Python and R - Second Edition

Product type Book

Published in Mar 2024

Publisher Packt

ISBN-13 9781837639533

Pages 814 pages

Edition 2nd Edition

Languages

Python

Concepts

Business Intelligence

Author (1):

Luca Zavarella

Table of Contents (27) Chapters

Preface

1. Where and How to Use R and Python Scripts in Power BI

2. Configuring R with Power BI

3. Configuring Python with Power BI

4. Solving Common Issues When Using Python and R in Power BI

5. Importing Unhandled Data Objects

6. Using Regular Expressions in Power BI

7. Anonymizing and Pseudonymizing Your Data in Power BI

8. Logging Data from Power BI to External Sources

9. Loading Large Datasets Beyond the Available RAM in Power BI

10. Boosting Data Loading Speed in Power BI with Parquet Format

11. Calling External APIs to Enrich Your Data

12. Calculating Columns Using Complex Algorithms: Distances

13. Calculating Columns Using Complex Algorithms: Fuzzy Matching

14. Calculating Columns Using Complex Algorithms: Optimization Problems

15. Adding Statistical Insights: Associations

16. Adding Statistical Insights: Outliers and Missing Values

17. Using Machine Learning without Premium or Embedded Capacity

18. Using SQL Server External Languages for Advanced Analytics and ML Integration in Power BI

19. Exploratory Data Analysis

20. Using the Grammar of Graphics in Python with plotnine

21. Advanced Visualizations

22. Interactive R Custom Visuals

23. Other Books You May Enjoy

24. Index

Appendix 1: Answers

1. Appendix 2: Glossary

Implementing a circular barplot in Power BI

As you have already seen in the previous chapters, Power BI is able to render graphs developed with ggplot2 using R visuals. So, no matter how complex the graph you created with ggplot2 is, you can be sure that Power BI will handle it well.

To create a circular barplot in Power BI, follow these steps:

Make sure that Power BI Desktop is pointing to the version of CRAN R that is dedicated to R visuals in Options.
Click on Get data, and then click Text/CSV.
Select the Scores.csv file located in the Chapter 21 folder and click Open.
You will see a preview of the CSV file. Be sure to select 65001: Unicode (UTF-8) for File Origin. This will ensure that special characters in speaker names are displayed correctly. Then, click on Load.
Click on the R Visual icon in the Visualizations panel, enable it, and then resize the visual to fit the entire available canvas.
With the R visual selected, expand the...