polars.DataFrame.bottom_k#

DataFrame.bottom_k( k: int, *, by: IntoExpr | Iterable[IntoExpr], reverse: bool | Sequence[bool] = False, ) → DataFrame[source]#

Return the k smallest rows.

Non-null elements are always preferred over null elements, regardless of the value of reverse. The output is not guaranteed to be in any particular order, call sort() after this function if you wish the output to be sorted.

Parameters:

k: Number of rows to return.
by: Column(s) used to determine the bottom rows. Accepts expression input. Strings are parsed as column names.
reverse: Consider the k largest elements of the by column(s) (instead of the k smallest). This can be specified per column by passing a sequence of booleans.

See also

top_k

Examples

>>> df = pl.DataFrame(
...     {
...         "a": ["a", "b", "a", "b", "b", "c"],
...         "b": [2, 1, 1, 3, 2, 1],
...     }
... )

Get the rows which contain the 4 smallest values in column b.

>>> df.bottom_k(4, by="b")
shape: (4, 2)
┌─────┬─────┐
│ a   ┆ b   │
│ --- ┆ --- │
│ str ┆ i64 │
╞═════╪═════╡
│ b   ┆ 1   │
│ a   ┆ 1   │
│ c   ┆ 1   │
│ a   ┆ 2   │
└─────┴─────┘

Get the rows which contain the 4 smallest values when sorting on column a and b.

>>> df.bottom_k(4, by=["a", "b"])
shape: (4, 2)
┌─────┬─────┐
│ a   ┆ b   │
│ --- ┆ --- │
│ str ┆ i64 │
╞═════╪═════╡
│ a   ┆ 1   │
│ a   ┆ 2   │
│ b   ┆ 1   │
│ b   ┆ 2   │
└─────┴─────┘