Related Issues (20)
- LazyFrame OOM on CSVs with rows that contains large amount of data
- `pl.from_pandas` with columns that mix strings and NAs results in `TypeError` HOT 2
- ComputeError: this expression cannot run in the group_by context HOT 1
- Polars from Pandas - NaN no longer convert to Null when mixed datatypes HOT 1
- Rename after finishing writing file to disk to avoid corrupted parquet files.
- Scan_parquet no longer returns the hive partition column of parquet files in polars==1.0.0 HOT 1
- polars List type columns accessors not returning the right dtype HOT 1
- `scan_parquet` cannot read directory-style hive partitioned parquet files in polars==1.0.0 HOT 5
- `Expr.slice` no longer allows `length = None` HOT 1
- `PanicException` raised on converting result to string HOT 1
- `read_ipc` and `scan_ipc` use more memory than needed. HOT 2
- List.eval giving unexpected results HOT 4
- polars.Expr.all method description is unclear on ignore_nulls parameter logic
- Using `scan_csv` with `with_column_names` argument disables schema validation
- `strict` parameter not applied correctly during row-wise DataFrame construction HOT 5
- Fix doc of GroupBy.__iter__ HOT 1
- SchemaMismatch during `collect`
- Segmentation fault with `to_numpy` with Numpy 2 and datetime column HOT 1
- Entered unreachable code on valid SQL HOT 3
- Using pandas `Timestamp` in DataFrame constructor drops timezone info
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from polars.