3. Data Manipulation

Lay the essential groundwork for pricing analytics by mastering Python’s core data concepts and tools. This chapter introduces fundamental syntax, interactive notebooks, key libraries, powerful dataframes, and abstraction techniques to streamline your coding workflow.

Build a solid understanding of Python’s core data-handling capabilities - the essential foundation for any pricing analytics project.

Get familiar with the key Python libraries for pricing analytics - from data wrangling to statistical modeling - and how to integrate them into your workflow.

Master Polars DataFrames to efficiently store, manipulate, and query large tabular datasets.