Summary
In this chapter, you got to learn about the Tidyverse approach to R development and how to serialize R objects to files. After that, you learned how to use these serialized files, both in Power Query Editor and in R visuals.
You then approached the same issues using Python. Specifically, you learned which packages are most used by the PyData community, learned how to serialize Python objects to files, and how to use them in Power BI, both in Power Query Editor and in Python visuals.
In the next chapter, you'll have a chance to learn how powerful regular expressions and fuzzy string matching are and what benefits they can bring to your Power BI reports.
