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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

Test your knowledge

Q01. What are the main purposes of using regexes?Q02. What are the main Python packages that implement regex functionality?Q03. What are the main R packages that implement regex functionality?Q04. Can you briefly summarize the method used to extract useful information from a free-text note?

Answers

A01. The main purposes of using regexes are:

  1. Text validation: Regexes can be used to check if a piece of text matches a certain pattern. This is useful for tasks such as verifying email addresses, dates, or other types of structured data.
  2. Text searching and filtering: Regexes can be used to search for patterns in large amounts of text, such as finding all instances of a particular word or phrase in a document. This can also be used to filter out unwanted data, such as removing all instances of a certain word or phrase from a document.
  3. Text manipulation and formatting: Regexes can be used to manipulate text in various ways, such as finding and replacing certain words or...
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