polars
https://github.com/pola-rs/polars
Rust
Dataframes powered by a multithreaded, vectorized query engine, written in Rust
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- Issues
- from_dicts without strict=false can result in silent data loss with ragged data
- Support comparison operations for `list` types
- Implement min-max predicate pushdown optimisation through joins (from DuckDB)
- Move the option to overwrite field names to be responsibility of the `new_columns` parameter
- `df.write_excel` does not work with file objects
- Initializing a struct series with an array type field using Numpy arrays results in nulls
- Ability to `sink` lazy datasets to `STDOUT` or to files
- Consider removing unnecessary projection for single key join followed by `.select(pl.len())`
- Filtering with pl.col is substantially (27x) slower than filtering with pl.Series
- GPU accelerated Polars taking 4 times longer to SUM a column in 100m record CSV than regular CPU. Running in Jupyter Notebook
- Docs
- Rust not yet supported