Search icon
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Extending Power BI with Python and R - Second Edition

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
Author (1):
Luca Zavarella Luca Zavarella
Profile icon 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

Using multiple datasets in Python and R script steps

You may have noticed how each query in Power Query has its own queue of transformation steps, leading from the initial data to the final dataset in the desired form. You may need to add a Python or R script step that uses a function to which you need to pass two dataframes as parameters to a query.

Assuming I have the two queries, query_A and query_B, which return the two datasets to be used as parameters for the above function, how do I reference the result of query_B in my script if I’m adding the script step to query_A?

There are several ways to do this. Let’s see them.

Applying a full join with Merge

The first trick that comes to mind for any analyst who is used to dealing with data is to apply a full join between the two datasets and thus generate a third dataset on which to apply the script step. Within the script step, the reverse merge transformation is applied, that is, separating the columns...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €14.99/month. Cancel anytime}