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

Summary

In this chapter, you learned about the most popular free R engines in the community. In particular, you learned about the performance advantages introduced by Microsoft in its distribution of R, even if this distribution will be retired in the near future. You also learned how to enhance the standard CRAN R with the oneMKL libraries for multi-threaded calculations.

Taking note of the unique features of Power BI Desktop and the Power BI service, you have learned how to properly choose the engines and how to install them.

You have also learned about the most popular IDE in the R community and how to install it.

In addition, you were introduced to all of the best practices for properly configuring both Power BI Desktop and the Power BI service with R, whether in a development or enterprise environment.

Finally, you learned about some of the limitations of using R with Power BI, knowledge of which is critical to avoid making mistakes in developing and deploying...