Comments (2)
What were your feature flags?
from polars.
What were your feature flags?
default-features = false, features = ["dtype-struct", "fmt", "ipc", "json", "lazy", "temporal"]
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Related Issues (20)
- Support `Enum` inputs in `lit` HOT 8
- Provide per-version documentation on the website
- Cannot create polars dataframes on AWS Lambda HOT 2
- Panic when using shift and over on empty data
- Handle parquet files with incorrect statistics in `scan_parquet` HOT 4
- [Python] `min_periods` should be a named argument or not? HOT 2
- chore: use `polars-compute` in `polars-parquet` statistics
- pl.Enum equivalence is category order dependent HOT 3
- `Decimal[*, scale>0] * Int` has differing result type than `Decimal[*, scale>0] * Decimal[*,scale=0]` HOT 1
- The `pivot` feature does not compile in Rust polars v38-40. HOT 2
- Struct with decimals not read properly in parquet HOT 7
- Regression from 0.20.21 -> 0.20.22-rc.1 `pl.Expr.list.to_array(n)` is throwing `polars.exceptions.ComputeError: not all elements have the specified width n` HOT 1
- performance issue with tpch q7 after dropping columns and using sink_parquet HOT 4
- `map_elements` doesn't respect `return_dtype` within an `over` statement on an empty DataFrame HOT 1
- `pl.lit(None, dtype=pl.Struct({"a": pl.Int64()}))` gives `{'a': None}`, not `None` HOT 1
- Support equality operation on nested Array types
- Unordered enum data type HOT 4
- Support interval expressions in Python SQL Context
- minimal `dyn int` when reading from python HOT 1
- Panic when casting Array of Categoricals to Array of String HOT 2
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