Chapter 2: Data Wrangling with Polars

This chapter introduces the Polars library for data wrangling in Python, covering select, filter, with_columns, group_by, agg, and method chaining.

1Introduction to Polars

2Exercise: A look at the gapminder DataFrame

3The select() function

4Exercise: Practice with select()

5The filter() function

6Exercise: Practice with filter()

7The with_columns() function

8Exercise: Practice with with_columns()

9The group_by() and agg() functions

10Exercise: Practice with group_by() and agg()

11Method chaining

12Exercise: Practice method chaining

13Joining DataFrames

14Exercise: Practice joining DataFrames

15Conclusion

About this course

These tutorials introduce Python for data wrangling with Polars and data visualisation with plotnine, using the grammar of graphics approach.

About me

Ph.D in Social and Experimental Psychology from the University Grenoble-Alpes, France. Now Assistant Professor of Business Research Methods at Dublin City University, my domain of expertise relies on multivariate time series analysis and trend extraction for supervised or unsupervised machine learning classification.