https://crates.io/crates/polars
The Rust Polars crate is a data manipulation and analysis library for the Rust programming language. It is designed to provide a fast, efficient, and easy-to-use interface for working with large datasets.
At its core, Rust Polars is built on top of the Apache Arrow memory format, which provides a standard way of representing data in memory. This allows Rust Polars to take advantage of the performance benefits of Arrow, such as zero-copy data access and efficient memory utilization.
Rust Polars provides a DataFrame API, which is similar to the DataFrame API in popular data analysis tools like Pandas for Python and the tidyverse in R. This API allows users to perform a wide variety of operations on their data, such as filtering, aggregation, grouping, and merging.
Some of the key features of Rust Polars include:
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Fast performance: Rust Polars is designed to be as fast as possible, with many operations being implemented using parallel processing to take advantage of multi-core CPUs.
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Easy-to-use API: The DataFrame API is designed to be easy to learn and use, with many common operations being implemented using a fluent, chainable syntax.
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Flexible data types: Rust Polars supports a wide variety of data types, including strings, numbers, dates, times, and more.
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Integration with other Rust libraries: Rust Polars can be easily integrated with other Rust libraries, such as Serde for serialization and deserialization.
Overall, Rust Polars is a powerful data analysis library that provides a fast, efficient, and easy-to-use interface for working with large datasets in Rust.