polars.Expr.hist

Expr.hist(

bins: IntoExpr | None = None,

*,

bin_count: int | None = None,

include_category: bool = False,

include_breakpoint: bool = False,

) → Self

Bin values into buckets and count their occurrences.

Warning

This functionality is considered unstable. It may be changed at any point without it being considered a breaking change.

Parameters:

bins

Discretizations to make. If None given, we determine the boundaries based on the data.

bin_count

If no bins provided, this will be used to determine the distance of the bins

include_breakpoint

Include a column that indicates the upper breakpoint.

include_category

Include a column that shows the intervals as categories.

Returns:

DataFrame

Examples

>>> df = pl.DataFrame({"a": [1, 3, 8, 8, 2, 1, 3]})
>>> df.select(pl.col("a").hist(bins=[1, 2, 3]))
shape: (4, 1)
┌─────┐
│ a   │
│ --- │
│ u32 │
╞═════╡
│ 2   │
│ 1   │
│ 2   │
│ 2   │
└─────┘
>>> df.select(
...     pl.col("a").hist(
...         bins=[1, 2, 3], include_breakpoint=True, include_category=True
...     )
... )
shape: (4, 1)
┌───────────────────────┐
│ a                     │
│ ---                   │
│ struct[3]             │
╞═══════════════════════╡
│ {1.0,"(-inf, 1.0]",2} │
│ {2.0,"(1.0, 2.0]",1}  │
│ {3.0,"(2.0, 3.0]",2}  │
│ {inf,"(3.0, inf]",2}  │
└───────────────────────┘