From the course: Advanced Python: Top Tools for Data Science and Engineering
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Overview of Polars
From the course: Advanced Python: Top Tools for Data Science and Engineering
Overview of Polars
- [Instructor] In this chapter, we're going to examine the Polars Library. And the Polars Library, which was first introduced in 2020, is a high performance data frame library designed to efficiently handle large scale data processing. It's written using the Rust programming language, enabling it to process data at speeds comparable to low level languages, while maintaining a user-friendly Python API. Polars provides an API that's similar to Pandas, but with some important differences that we'll get to later in the chapter. It's optimized for speed and memory efficiency, making it particularly well suited for so-called big data applications. This combination of performance and ease of use makes Polars a powerful tool for data scientists and engineers working with large data sets, even those that don't entirely fit within the available system memory. Like Pandas, Polars also integrates with other common data science tools. You can read and write various other data formats and work with…
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