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Polars Crash Course

training

Duration

1/2 day

Location

Virtual or on-site

Skill level

Beginner

Certificate

Yes

Enroll your company

What you will learn

Learn the basics of Polars. By the end of this half day course, you will have a solid grasp of Polars concepts and essentials to get you started with data manipulation. This is a denser, more fast-paced version of the Polars Essential training course. It contains fewer hands-on exercises.

Audience

Prior experience in Python is required. This course is well-suited to anyone learning the basics of Polars.

Learning outcomes

  • Learn about key concepts in Polars

  • Get comfortable with the Polars API to manipulate large datasets

  • Process time series data with Polars

Module 1

Polars basics
  1. Data structures
    • Learn about the core data structures in Polars: DataFrames and Series.
  2. Input / Output
    • Master various ways of reading & writing data in Polars, such as constructing DataFrames from scratch and importing data from various sources.
  3. Data manipulation
    • Explore Polars' powerful and expressive API, including filtering, joining and transforming DataFrames to efficiently handle large-scale datasets.

Module 2

High performance data analysis
  1. Performance
    • Learn about the concepts that make Polars so performant and how to use them correctly: lazy evaluation, multithreading, and streaming and out-of-core algorithms.
  2. Ecosystem
    • Discover how Polars integrates with other data science tools and libraries in the ecosystem using Apache Arrow.

Module 3

Analyzing time series data
  1. Datetime operations
    • Use robust datetime functionalities to efficiently handle time series data for temporal analyses.
  2. Time series analysis
    • Apply specialized time series features to conduct advanced analyses, including resampling, rolling operations and more.

"Polars revolutionizes data analysis, completely replacing pandas in my setup. It offers massive performance boosts, effortlessly handling data frames with millions of rows. Allowing us to focus on crafting simpler, cleaner code. This efficiency drastically cuts down iteration time, driving improved trading decisions. And speed? Polars isn't just fast—it's lightning-fast."

Matt Whitehead

Quantitative Researcher @ Optiver

" Migrating from pandas to Polars was surprisingly easy. For us, the results speak for themselves. Polars not only solved our initial problem but opened the door to new possibilities. We are excited to use Polars on future data engineering projects. "

Paul Duvenage

Senior Data Engineer @ Check

"The speedup of Polars compared to Pandas is massively noticeable. I generally enjoy writing code that I know is fast."

Casey H.

Machine Learning Engineer @ G-Research

Polars courses

Enroll your company today and master Polars Crash Course

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