polars.Expr.shrink_dtype#
- Expr.shrink_dtype() Expr [source]#
Shrink numeric columns to the minimal required datatype.
Shrink to the dtype needed to fit the extrema of this [
Series
]. This can be used to reduce memory pressure.Examples
>>> pl.DataFrame( ... { ... "a": [1, 2, 3], ... "b": [1, 2, 2 << 32], ... "c": [-1, 2, 1 << 30], ... "d": [-112, 2, 112], ... "e": [-112, 2, 129], ... "f": ["a", "b", "c"], ... "g": [0.1, 1.32, 0.12], ... "h": [True, None, False], ... } ... ).select(pl.all().shrink_dtype()) shape: (3, 8) ┌─────┬────────────┬────────────┬──────┬──────┬─────┬──────┬───────┐ │ a ┆ b ┆ c ┆ d ┆ e ┆ f ┆ g ┆ h │ │ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- │ │ i8 ┆ i64 ┆ i32 ┆ i8 ┆ i16 ┆ str ┆ f32 ┆ bool │ ╞═════╪════════════╪════════════╪══════╪══════╪═════╪══════╪═══════╡ │ 1 ┆ 1 ┆ -1 ┆ -112 ┆ -112 ┆ a ┆ 0.1 ┆ true │ │ 2 ┆ 2 ┆ 2 ┆ 2 ┆ 2 ┆ b ┆ 1.32 ┆ null │ │ 3 ┆ 8589934592 ┆ 1073741824 ┆ 112 ┆ 129 ┆ c ┆ 0.12 ┆ false │ └─────┴────────────┴────────────┴──────┴──────┴─────┴──────┴───────┘