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Extending Power BI with Python and R

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

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Product type Paperback
Published in Nov 2021
Publisher Packt
ISBN-13 9781801078207
Length 558 pages
Edition 1st Edition
Languages
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Author (1):
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Luca Zavarella Luca Zavarella
Author Profile Icon Luca Zavarella
Luca Zavarella
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Table of Contents (22) Chapters Close

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

R and Python limitations on Power BI products

The first question once you are clear on where to inject R and Python scripts in Power BI could be: "Is the use of R and Python code allowed in all Power BI products?" In order to have a brief recap of the various Power BI products and their usage in general, here is a concise list:

  • Power BI Service: This is sometimes called Power BI Online, and it's the Software as a Service (SaaS) declination of Power BI. It was created to facilitate the sharing of visual analysis between users through Dashboards and Reports.
  • Power BI Report Server: This is the on-premises version of Power BI and it extends the capabilities of SQL Server Reporting Services, enabling the sharing of reports created in Power BI Desktop (for Report Server).
  • Power BI Embedded: A Microsoft Azure service that allows dashboards and reports to be embedded in an application for users who do not have a Power BI account.
  • Power BI Desktop: A free desktop application for Windows that allows you to use almost all of the features that Power BI exposes. It is not the right tool for sharing results between users, but it allows you to share them on Power BI Service and Power BI Report Server. The desktop versions that allow publishing on the two mentioned services are distinct.
  • Power BI Mobile: A mobile application, available on Windows, Android, and iOS, that allows secure access to Power BI Service and Power BI Report Server, and that allows you to browse and share dashboards and reports, but not edit them.

Apart from the licenses, which we will not go into here, a summary figure of the relationships between the previously mentioned products follows:

Figure 1.15 – Interactions between Power BI products

Figure 1.15 – Interactions between Power BI products

Unfortunately, of all these products, only Power BI Service, Power BI Embedded, and Power BI Desktop allow you to enrich data via code in R and Python:

Figure 1.16 – Power BI products compatibility with R and Python

Figure 1.16 – Power BI products compatibility with R and Python

Important note

From here on out, when we talk about Power BI Service in terms of compatibility with analytical languages, what we say will also apply to Power BI Embedded.

So, if you need to develop reports using advanced analytics through R and Python, make sure the target platform supports them.

You have been reading a chapter from
Extending Power BI with Python and R
Published in: Nov 2021
Publisher: Packt
ISBN-13: 9781801078207
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