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Add polars to ecosystem (#101)
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protocol/purpose_and_scope.md

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@@ -126,6 +126,9 @@ It uses SQLAlchemy and a custom SQL compiler to translate its pandas-like API to
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SQL statements, executed by the backends. It supports conventional DBMS, as well
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as big data systems such as Apache Impala or BigQuery.
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[Polars](https://www.pola.rs/) is a DataFrame library written in Rust, with
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Python bindings available. Their API is intentionally different to the pandas one.
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#### History of this dataframe protocol
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While there is no dataframe protocol like the one described in this document in

spec/purpose_and_scope.md

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SQL statements, executed by the backends. It supports conventional DBMS, as well
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as big data systems such as Apache Impala or BigQuery.
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[Polars](https://www.pola.rs/) is a DataFrame library written in Rust, with
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Python bindings available. Their API is intentionally different to the pandas one.
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Given the growing Python dataframe ecosystem, and its complexity, this document provides
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a standard Python dataframe API. Until recently, pandas has been a de-facto standard for
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Python dataframes. But currently there are a growing number of not only dataframe libraries,
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- [Mars](https://docs.pymars.org/en/latest/)
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- [Modin](https://github.com/modin-project/modin)
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- [pandas](https://pandas.pydata.org/)
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- [polars](https://www.pola.rs/)
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- [PySpark](https://spark.apache.org/docs/latest/api/python/index.html)
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- [StaticFrame](https://static-frame.readthedocs.io/en/latest/)
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- [Turi Create](https://github.com/apple/turicreate)

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