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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

Implementing a circular barplot in Power BI

As you have already seen in the previous chapters, Power BI is capable of rendering graphs developed with ggplot2 using R visuals. Therefore, whatever the complexity of the graph created using ggplot2, you can be sure that Power BI handles it well.

To create a circular barplot in Power BI, proceed as follows:

  1. Make sure that Power BI Desktop is referencing the version of CRAN R dedicated to R visuals in Options.
  2. Click on Get Data, Text/CSV, and then Connect.
  3. Select the Scores.csv file found in the Chapter15 folder and click Open.
  4. You will see a preview of the CSV file. Make sure to select 65001: Unicode (UTF-8) as File Origin. This way, special characters in speaker names will be displayed correctly. Then, click on Load.
  5. Click on the R Visual icon in the Visualizations panel, enable it, and then resize the visual as all the available canvas.
  6. Keeping the R visual selected, expand the Scores table under the Fields...
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