Data Analysis with Polars

The widely used Pandas package is powerful but its API is enormous, inconsistent, and clunky and it is known to be quite slow. The tide has turned and we at Python Charmers believe Polars is now superior to Pandas for most tasks involving dataframes because of its better API, better performance, and better options for cross-language interoperability.

Prerequisites

Proficiency in Python. Proficiency with Pandas is helpful but not required.

Expected Outcomes

This course will teach you about efficiently handling and analyzing large tabular and time-series datasets with Polars.

Course Syllabus

Session 1: Using Polars

Session 1 will give you a crash course on handling and analyzing tabular data
with Polars:

Introduction to Polars as an alternative to Pandas
- Concepts and philosophy of Polars versus Pandas
- DataFrame structure (vs Pandas DataFrame, dict and array)
- Data types and casting; handling missing data
- Eager vs lazy evaluation
Useful features of Polars
- Expressions: selecting and filtering data; windows functions; ...
- Handling dates, times, and time-series; resampling
- Data fusion: joining & concatenating datasets
- Summarization with “group by” operations; pivot tables

Session 2: Polars in more depth

This session teaches you more about data analysis with Polars:

Polars in depth
- The Polars lazy API
- Polars internals: Arrow memory format
- Strings in depth
- Expressions in depth: Structs, user-defined functions, ...
- Speed and memory characteristics of Polars; immutability
Limitations and differences versus Pandas
- Patterns for working without an index
- Reshaping data: equivalents to Pandas’ stack/unstack/melt; hierarchical indices

Personal help

We are happy to offer on-the-spot problem-solving after each day of the training for you to ask one-on-one questions — whether about the course content and exercises or about specific problems you face in your work and how to solve them. If you would like us to prepare for this in advance, you are welcome to send us background info before the course.

Other information

Format:
Courses are conducted online via video meeting using Python Charmers' cloud notebook server for sharing code with the trainer(s).
Computer:

Hardware: we recommend ≥ 8 GB of RAM and a webcam. Preferably also multiple screens and a quiet room (or headset mic).

Software: a modern browser: Chrome, Firefox, or Safari (not IE or Edge); and Zoom.

Coding: we have a cloud-based coding server that supports running code and sharing code with the trainer(s).
Timing:

Most courses will run from 9:00 to roughly 17:00 (AEST/AEDT) each day, with breaks of 50 minutes for lunch and 20 minutes each for morning and afternoon tea.

Certificate of completion:

We will provide you a certificate if you complete the course and successfully answer the majority of the exercise questions.

Materials:

You will have access to all the course materials via the cloud server. We will also send you a bound copy of the course notes, cheat sheets, and a USB stick containing the materials, exercise solutions, and further resources.

Python Training