refactor(python): Add Series.cut, deprecate pl.cut

py-polars/docs/source/reference/series/modify_select.rst

@@ -17,6 +17,7 @@ Manipulation/selection
     Series.clip_max
     Series.clip_min
     Series.clone
+    Series.cut
     Series.drop_nans
     Series.drop_nulls
     Series.explode

py-polars/polars/internals/functions.py

@@ -1,11 +1,12 @@
 from __future__ import annotations
 
 import contextlib
+import warnings
 from datetime import date, datetime, timedelta
 from typing import TYPE_CHECKING, Iterable, Sequence, overload
 
 from polars import internals as pli
-from polars.datatypes import Categorical, Date, Float64, PolarsDataType
+from polars.datatypes import Date, PolarsDataType
 from polars.utils import (
     _datetime_to_pl_timestamp,
     _timedelta_to_pl_duration,
@@ -505,6 +506,9 @@ def cut(
     """
     Bin values into discrete values.
 
+    .. deprecated:: 0.16.8
+        `pl.cut(series, ...)` has been deprecated; use `series.cut(...)`
+
     Parameters
     ----------
     s
@@ -550,43 +554,12 @@ def cut(
     └──────┴─────────────┴──────────────┘
 
     """
-    var_nm = s.name
-
-    cuts_df = pli.DataFrame(
-        [
-            pli.Series(
-                name=break_point_label, values=bins, dtype=Float64
-            ).extend_constant(float("inf"), 1)
-        ]
-    )
-
-    if labels:
-        if len(labels) != len(bins) + 1:
-            raise ValueError("expected more labels")
-        cuts_df = cuts_df.with_columns(pli.Series(name=category_label, values=labels))
-    else:
-        cuts_df = cuts_df.with_columns(
-            pli.format(
-                "({}, {}]",
-                pli.col(break_point_label).shift_and_fill(1, float("-inf")),
-                pli.col(break_point_label),
-            ).alias(category_label)
-        )
-
-    cuts_df = cuts_df.with_columns(pli.col(category_label).cast(Categorical))
-
-    result = (
-        s.cast(Float64)
-        .sort()
-        .to_frame()
-        .join_asof(
-            cuts_df,
-            left_on=var_nm,
-            right_on=break_point_label,
-            strategy="forward",
-        )
+    warnings.warn(
+        "`pl.cut(series)` has been deprecated; use `series.cut()`",
+        category=DeprecationWarning,
+        stacklevel=2,
     )
-    return result
+    return s.cut(bins, labels, break_point_label, category_label)
 
 
 @overload

py-polars/polars/internals/series/series.py

@@ -1415,6 +1415,99 @@ def to_dummies(self, separator: str = "_") -> pli.DataFrame:
         """
         return pli.wrap_df(self._s.to_dummies(separator))
 
+    def cut(
+        self,
+        bins: list[float],
+        labels: list[str] | None = None,
+        break_point_label: str = "break_point",
+        category_label: str = "category",
+    ) -> pli.DataFrame:
+        """
+        Bin values into discrete values.
+
+        Parameters
+        ----------
+        bins
+            Bins to create.
+        labels
+            Labels to assign to the bins. If given the length of labels must be
+            len(bins) + 1.
+        break_point_label
+            Name given to the breakpoint column.
+        category_label
+            Name given to the category column.
+
+        Returns
+        -------
+        DataFrame
+
+        Warnings
+        --------
+        This functionality is experimental and may change without it being considered a
+        breaking change.
+
+        Examples
+        --------
+        >>> a = pl.Series("a", [v / 10 for v in range(-30, 30, 5)])
+        >>> a.cut(bins=[-1, 1])
+        shape: (12, 3)
+        ┌──────┬─────────────┬──────────────┐
+        │ a    ┆ break_point ┆ category     │
+        │ ---  ┆ ---         ┆ ---          │
+        │ f64  ┆ f64         ┆ cat          │
+        ╞══════╪═════════════╪══════════════╡
+        │ -3.0 ┆ -1.0        ┆ (-inf, -1.0] │
+        │ -2.5 ┆ -1.0        ┆ (-inf, -1.0] │
+        │ -2.0 ┆ -1.0        ┆ (-inf, -1.0] │
+        │ -1.5 ┆ -1.0        ┆ (-inf, -1.0] │
+        │ ...  ┆ ...         ┆ ...          │
+        │ 1.0  ┆ 1.0         ┆ (-1.0, 1.0]  │
+        │ 1.5  ┆ inf         ┆ (1.0, inf]   │
+        │ 2.0  ┆ inf         ┆ (1.0, inf]   │
+        │ 2.5  ┆ inf         ┆ (1.0, inf]   │
+        └──────┴─────────────┴──────────────┘
+
+        """
+        var_nm = self.name
+
+        cuts_df = pli.DataFrame(
+            [
+                pli.Series(
+                    name=break_point_label, values=bins, dtype=Float64
+                ).extend_constant(float("inf"), 1)
+            ]
+        )
+
+        if labels:
+            if len(labels) != len(bins) + 1:
+                raise ValueError("expected more labels")
+            cuts_df = cuts_df.with_columns(
+                pli.Series(name=category_label, values=labels)
+            )
+        else:
+            cuts_df = cuts_df.with_columns(
+                pli.format(
+                    "({}, {}]",
+                    pli.col(break_point_label).shift_and_fill(1, float("-inf")),
+                    pli.col(break_point_label),
+                ).alias(category_label)
+            )
+
+        cuts_df = cuts_df.with_columns(pli.col(category_label).cast(Categorical))
+
+        result = (
+            self.cast(Float64)
+            .sort()
+            .to_frame()
+            .join_asof(
+                cuts_df,
+                left_on=var_nm,
+                right_on=break_point_label,
+                strategy="forward",
+            )
+        )
+        return result
+
     def value_counts(self, sort: bool = False) -> pli.DataFrame:
         """
         Count the unique values in a Series.

py-polars/tests/unit/test_functions.py

@@ -93,38 +93,10 @@ def test_all_any_horizontally() -> None:
     assert_frame_equal(result, expected)
 
 
-def test_cut() -> None:
-    a = pl.Series("a", [v / 10 for v in range(-30, 30, 5)])
-    out = pl.cut(a, bins=[-1, 1])
-
-    assert out.shape == (12, 3)
-    assert out.filter(pl.col("break_point") < 1e9).to_dict(False) == {
-        "a": [-3.0, -2.5, -2.0, -1.5, -1.0, -0.5, 0.0, 0.5, 1.0],
-        "break_point": [-1.0, -1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0],
-        "category": [
-            "(-inf, -1.0]",
-            "(-inf, -1.0]",
-            "(-inf, -1.0]",
-            "(-inf, -1.0]",
-            "(-inf, -1.0]",
-            "(-1.0, 1.0]",
-            "(-1.0, 1.0]",
-            "(-1.0, 1.0]",
-            "(-1.0, 1.0]",
-        ],
-    }
-
-    # test cut on integers #4939
-    inf = float("inf")
-    df = pl.DataFrame({"a": list(range(5))})
-    ser = df.select("a").to_series()
-    assert pl.cut(ser, bins=[-1, 1]).rows() == [
-        (0.0, 1.0, "(-1.0, 1.0]"),
-        (1.0, 1.0, "(-1.0, 1.0]"),
-        (2.0, inf, "(1.0, inf]"),
-        (3.0, inf, "(1.0, inf]"),
-        (4.0, inf, "(1.0, inf]"),
-    ]
+def test_cut_deprecated() -> None:
+    with pytest.deprecated_call():
+        a = pl.Series("a", [v / 10 for v in range(-30, 30, 5)])
+        pl.cut(a, bins=[-1, 1])
 
 
 def test_null_handling_correlation() -> None:

py-polars/tests/unit/test_series.py

@@ -2523,3 +2523,37 @@ def test_from_epoch_seq_input() -> None:
     expected = pl.Series([datetime(2006, 5, 17, 15, 34, 4)])
     result = pl.from_epoch(seq_input)
     assert_series_equal(result, expected)
+
+
+def test_cut() -> None:
+    a = pl.Series("a", [v / 10 for v in range(-30, 30, 5)])
+    out = a.cut(bins=[-1, 1])
+
+    assert out.shape == (12, 3)
+    assert out.filter(pl.col("break_point") < 1e9).to_dict(False) == {
+        "a": [-3.0, -2.5, -2.0, -1.5, -1.0, -0.5, 0.0, 0.5, 1.0],
+        "break_point": [-1.0, -1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0],
+        "category": [
+            "(-inf, -1.0]",
+            "(-inf, -1.0]",
+            "(-inf, -1.0]",
+            "(-inf, -1.0]",
+            "(-inf, -1.0]",
+            "(-1.0, 1.0]",
+            "(-1.0, 1.0]",
+            "(-1.0, 1.0]",
+            "(-1.0, 1.0]",
+        ],
+    }
+
+    # test cut on integers #4939
+    inf = float("inf")
+    df = pl.DataFrame({"a": list(range(5))})
+    ser = df.select("a").to_series()
+    assert ser.cut(bins=[-1, 1]).rows() == [
+        (0.0, 1.0, "(-1.0, 1.0]"),
+        (1.0, 1.0, "(-1.0, 1.0]"),
+        (2.0, inf, "(1.0, inf]"),
+        (3.0, inf, "(1.0, inf]"),
+        (4.0, inf, "(1.0, inf]"),
+    ]