Related Issues (20)
- `SchemaError` when combining boolean expressions on Decimals using `!=` (fine with `.ne()`) HOT 2
- `pl.concat_list` is slow(?) HOT 5
- ColumnNotFoundError on concat of LazyFrames; works fine if collected first HOT 8
- `pl.read_database()` with `iter_batches=True` no longer loads batches incrementally HOT 3
- Polars read_database does not really respect iter_batches = True when using sqlalchemy/oracledb HOT 5
- SchemaError: nonexistent column when created from sequence HOT 5
- The full streaming engine pipeline scan > join with outer_coalesce > sink does not work HOT 2
- [DRAFT] semi-join on id isn't being pushed down with JIT optimizations HOT 3
- Error when the result of joining two `DataFrame`s is empty, and one of the `DataFrame`s contains an array column HOT 1
- Obfuscate/censor AccessKey in lazy serialize by default (have parameter to leave in the clear).
- Regression 0.20.15->0.20.16: ComputeError: conversion from `null` to `struct[100]` failed in column 'literal' for 0 out of 1 values HOT 4
- Casting a column to pl.Categorical is way slower than pandas (10-20x) HOT 2
- Minimal memory usage tests for read_ipc read_ipc_stream
- Forward_fill() and backward_fill() is about 25% slower in polars compared to pandas' counterparts HOT 6
- Rust code examples missing on page /user-guide/io/cloud-storage/#scanning-from-cloud-storage-with-query-optimisation
- Offset_by is about 4 times slower in polars compared to pandas' counterpart HOT 2
- `filter` + `arg_max` + `over` producing non-deterministic junk values HOT 1
- pyo3_runtime.PanicException: python function failed: PyErr { type: <class 'TypeError'>, value: TypeError("'list' object is not callable"), traceback: None } HOT 1
- support expressions in `Frame.unique()` HOT 2
- Read Options for Calamine HOT 1
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