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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

Validating data using regex in Power BI

To date, Power BI has no native feature in Power Query to perform operations via regexes. There are cases when you can't avoid using regexes to extract useful information from data in text form. The only way to be able to use regexes is through R scripts or Python scripts. The only cons you have in this case is that, if you need to publish the report on the Power BI service, to allow Power Query to use external R or Python engines, you must also install the on-premises data gateway in personal mode.

However, let's get right into it with real-world examples.

Let's suppose you work at a retail company where there is a team dedicated to identifying fraudulent customers. As soon as a team member identifies a fraudster, they fill out an Excel spreadsheet, in which the Email and BannedDate columns are included along with others. Your task is to load the data from this Excel file into Power BI and, from other data sources, select...

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