10 апр. 2024 г. · For what I understand scan could be thought of as a stream, while read_csv_batched is, well, in batches.

22 мая 2024 г. · Had a weird Polars issue using postgres when reading/writing from a database. Switched back to pandas and it solved the issue.

17 мар. 2023 г. · It's consistently much faster than pandas for reading in data, often more memory efficient (especially on groupbys, merges etc) and I personally ...

6 янв. 2023 г. · The Polars api overview docs are so concise compared to pandas. Its a total breath of fresh air.

22 окт. 2024 г. · My typical workflow with a dataframe library in any language is to 1) read a csv or other data file 2) wrangle the data with select, filter, ...

9 сент. 2023 г. · Yes, since Polars is more explicit and idiomatic, its more clear to what some one exactly does, so code reads more naturally.

9 нояб. 2023 г. · A very simple test/comparison for C++ DataFrame vs. Polars. I wrote the following identical programs for both Polars and C++ DataFrame.

1 мар. 2024 г. · Both polars and arrow offer methods to efficiently process large data without loading it into memory. However, I've faced issues with unnesting operations.

13 мар. 2021 г. · tl;dr: Polars offers a great API and performance. No clear edge between Polars or native Rust. Performance overall Performance without Reading

31 мая 2023 г. · You can read it in in chunks with pandas and polars and do a similar thing. Parquet shouldn't change the space of a fully loaded dataset and ...