Data manipulation and analysis can be challenging and involve working with large datasets. Thankfully, a widely used Python library known as Pandas has become the go-to tool for processing and manipulating data. Pandas recently got an update, which is version 2.0. This article takes a closer look at what Pandas is, its success, and what the new version brings, including its ecosystem around Arrow, Polars, and DuckDB. (View Highlight)
Note: Pandas is a widely used Python library for data manipulation and analysis, which recently got an update to version 2.0. The new version brings an ecosystem of tools including Arrow, Polars, and DuckDB to make data processing and manipulation easier.
Some say Polars has a less confusing API and better ergonomics, especially from SQL. Polars is more performant out of the box but less stable and mature. It is growing the fastest of all mentioned in this chapter.
Polars has superpowers as it comes with a query optimizer that can make the pipeline run faster by analyzing all operations together before executing them. (View Highlight)
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