ENH: Styler builtins: highlight_between (pandas-dev#39821)

Author: attack68

doc/source/_static/style/hbetw_axNone.png

@@ -53,6 +53,7 @@ Builtin styles
    Styler.highlight_null
    Styler.highlight_max
    Styler.highlight_min
+   Styler.highlight_between
    Styler.background_gradient
    Styler.bar
 

doc/source/_static/style/hbetw_basic.png

@@ -209,6 +209,7 @@ Other enhancements
 - :meth:`.Styler.background_gradient` now allows the ability to supply a specific gradient map (:issue:`22727`)
 - :meth:`.Styler.clear` now clears :attr:`Styler.hidden_index` and :attr:`Styler.hidden_columns` as well (:issue:`40484`)
 - Builtin highlighting methods in :class:`Styler` have a more consistent signature and css customisability (:issue:`40242`)
+- :meth:`.Styler.highlight_between` added to list of builtin styling methods (:issue:`39821`)
 - :meth:`Series.loc.__getitem__` and :meth:`Series.loc.__setitem__` with :class:`MultiIndex` now raising helpful error message when indexer has too many dimensions (:issue:`35349`)
 - :meth:`pandas.read_stata` and :class:`StataReader` support reading data from compressed files.
 - Add support for parsing ``ISO 8601``-like timestamps with negative signs to :meth:`pandas.Timedelta` (:issue:`37172`)

doc/source/_static/style/hbetw_props.png

@@ -6,6 +6,7 @@
 from contextlib import contextmanager
 import copy
 from functools import partial
+import operator
 from typing import (
     Any,
     Callable,
@@ -21,6 +22,7 @@
     FrameOrSeries,
     FrameOrSeriesUnion,
     IndexLabel,
+    Scalar,
 )
 from pandas.compat._optional import import_optional_dependency
 from pandas.util._decorators import doc
@@ -1352,6 +1354,7 @@ def highlight_null(
         --------
         Styler.highlight_max: Highlight the maximum with a style.
         Styler.highlight_min: Highlight the minimum with a style.
+        Styler.highlight_between: Highlight a defined range with a style.
         """
 
         def f(data: DataFrame, props: str) -> np.ndarray:
@@ -1399,6 +1402,7 @@ def highlight_max(
         --------
         Styler.highlight_null: Highlight missing values with a style.
         Styler.highlight_min: Highlight the minimum with a style.
+        Styler.highlight_between: Highlight a defined range with a style.
         """
 
         def f(data: FrameOrSeries, props: str) -> np.ndarray:
@@ -1446,6 +1450,7 @@ def highlight_min(
         --------
         Styler.highlight_null: Highlight missing values with a style.
         Styler.highlight_max: Highlight the maximum with a style.
+        Styler.highlight_between: Highlight a defined range with a style.
         """
 
         def f(data: FrameOrSeries, props: str) -> np.ndarray:
@@ -1459,6 +1464,157 @@ def f(data: FrameOrSeries, props: str) -> np.ndarray:
             f, axis=axis, subset=subset, props=props  # type: ignore[arg-type]
         )
 
+    def highlight_between(
+        self,
+        subset: IndexLabel | None = None,
+        color: str = "yellow",
+        axis: Axis | None = 0,
+        left: Scalar | Sequence | None = None,
+        right: Scalar | Sequence | None = None,
+        inclusive: str = "both",
+        props: str | None = None,
+    ) -> Styler:
+        """
+        Highlight a defined range with a style.
+
+        .. versionadded:: 1.3.0
+
+        Parameters
+        ----------
+        subset : IndexSlice, default None
+            A valid slice for ``data`` to limit the style application to.
+        color : str, default 'yellow'
+            Background color to use for highlighting.
+        axis : {0 or 'index', 1 or 'columns', None}, default 0
+            If ``left`` or ``right`` given as sequence, axis along which to apply those
+            boundaries. See examples.
+        left : scalar or datetime-like, or sequence or array-like, default None
+            Left bound for defining the range.
+        right : scalar or datetime-like, or sequence or array-like, default None
+            Right bound for defining the range.
+        inclusive : {'both', 'neither', 'left', 'right'}
+            Identify whether bounds are closed or open.
+        props : str, default None
+            CSS properties to use for highlighting. If ``props`` is given, ``color``
+            is not used.
+
+        Returns
+        -------
+        self : Styler
+
+        See Also
+        --------
+        Styler.highlight_null: Highlight missing values with a style.
+        Styler.highlight_max: Highlight the maximum with a style.
+        Styler.highlight_min: Highlight the minimum with a style.
+
+        Notes
+        -----
+        If ``left`` is ``None`` only the right bound is applied.
+        If ``right`` is ``None`` only the left bound is applied. If both are ``None``
+        all values are highlighted.
+
+        ``axis`` is only needed if ``left`` or ``right`` are provided as a sequence or
+        an array-like object for aligning the shapes. If ``left`` and ``right`` are
+        both scalars then all ``axis`` inputs will give the same result.
+
+        This function only works with compatible ``dtypes``. For example a datetime-like
+        region can only use equivalent datetime-like ``left`` and ``right`` arguments.
+        Use ``subset`` to control regions which have multiple ``dtypes``.
+
+        Examples
+        --------
+        Basic usage
+
+        >>> df = pd.DataFrame({
+        ...     'One': [1.2, 1.6, 1.5],
+        ...     'Two': [2.9, 2.1, 2.5],
+        ...     'Three': [3.1, 3.2, 3.8],
+        ... })
+        >>> df.style.highlight_between(left=2.1, right=2.9)
+
+        .. figure:: ../../_static/style/hbetw_basic.png
+
+        Using a range input sequnce along an ``axis``, in this case setting a ``left``
+        and ``right`` for each column individually
+
+        >>> df.style.highlight_between(left=[1.4, 2.4, 3.4], right=[1.6, 2.6, 3.6],
+        ...     axis=1, color="#fffd75")
+
+        .. figure:: ../../_static/style/hbetw_seq.png
+
+        Using ``axis=None`` and providing the ``left`` argument as an array that
+        matches the input DataFrame, with a constant ``right``
+
+        >>> df.style.highlight_between(left=[[2,2,3],[2,2,3],[3,3,3]], right=3.5,
+        ...     axis=None, color="#fffd75")
+
+        .. figure:: ../../_static/style/hbetw_axNone.png
+
+        Using ``props`` instead of default background coloring
+
+        >>> df.style.highlight_between(left=1.5, right=3.5,
+        ...     props='font-weight:bold;color:#e83e8c')
+
+        .. figure:: ../../_static/style/hbetw_props.png
+        """
+
+        def f(
+            data: FrameOrSeries,
+            props: str,
+            left: Scalar | Sequence | np.ndarray | FrameOrSeries | None = None,
+            right: Scalar | Sequence | np.ndarray | FrameOrSeries | None = None,
+            inclusive: bool | str = True,
+        ) -> np.ndarray:
+            if np.iterable(left) and not isinstance(left, str):
+                left = _validate_apply_axis_arg(
+                    left, "left", None, data  # type: ignore[arg-type]
+                )
+
+            if np.iterable(right) and not isinstance(right, str):
+                right = _validate_apply_axis_arg(
+                    right, "right", None, data  # type: ignore[arg-type]
+                )
+
+            # get ops with correct boundary attribution
+            if inclusive == "both":
+                ops = (operator.ge, operator.le)
+            elif inclusive == "neither":
+                ops = (operator.gt, operator.lt)
+            elif inclusive == "left":
+                ops = (operator.ge, operator.lt)
+            elif inclusive == "right":
+                ops = (operator.gt, operator.le)
+            else:
+                raise ValueError(
+                    f"'inclusive' values can be 'both', 'left', 'right', or 'neither' "
+                    f"got {inclusive}"
+                )
+
+            g_left = (
+                ops[0](data, left)
+                if left is not None
+                else np.full(data.shape, True, dtype=bool)
+            )
+            l_right = (
+                ops[1](data, right)
+                if right is not None
+                else np.full(data.shape, True, dtype=bool)
+            )
+            return np.where(g_left & l_right, props, "")
+
+        if props is None:
+            props = f"background-color: {color};"
+        return self.apply(
+            f,  # type: ignore[arg-type]
+            axis=axis,
+            subset=subset,
+            props=props,
+            left=left,
+            right=right,
+            inclusive=inclusive,
+        )
+
     @classmethod
     def from_custom_template(cls, searchpath, name):
         """

doc/source/_static/style/hbetw_seq.png

@@ -1,7 +1,10 @@
 import numpy as np
 import pytest
 
-from pandas import DataFrame
+from pandas import (
+    DataFrame,
+    IndexSlice,
+)
 
 pytest.importorskip("jinja2")
 
@@ -70,3 +73,72 @@ def test_highlight_minmax_ext(df, f, kwargs):
         df = -df
     result = getattr(df.style, f)(**kwargs)._compute().ctx
     assert result == expected
+
+
+@pytest.mark.parametrize(
+    "kwargs",
+    [
+        {"left": 0, "right": 1},  # test basic range
+        {"left": 0, "right": 1, "props": "background-color: yellow"},  # test props
+        {"left": -100, "right": 100, "subset": IndexSlice[[0, 1], :]},  # test subset
+        {"left": 0, "subset": IndexSlice[[0, 1], :]},  # test no right
+        {"right": 1},  # test no left
+        {"left": [0, 0, 11], "axis": 0},  # test left as sequence
+        {"left": DataFrame({"A": [0, 0, 11], "B": [1, 1, 11]}), "axis": None},  # axis
+        {"left": 0, "right": [0, 1], "axis": 1},  # test sequence right
+    ],
+)
+def test_highlight_between(styler, kwargs):
+    expected = {
+        (0, 0): [("background-color", "yellow")],
+        (0, 1): [("background-color", "yellow")],
+    }
+    result = styler.highlight_between(**kwargs)._compute().ctx
+    assert result == expected
+
+
+@pytest.mark.parametrize(
+    "arg, map, axis",
+    [
+        ("left", [1, 2], 0),  # 0 axis has 3 elements not 2
+        ("left", [1, 2, 3], 1),  # 1 axis has 2 elements not 3
+        ("left", np.array([[1, 2], [1, 2]]), None),  # df is (2,3) not (2,2)
+        ("right", [1, 2], 0),  # same tests as above for 'right' not 'left'
+        ("right", [1, 2, 3], 1),  # ..
+        ("right", np.array([[1, 2], [1, 2]]), None),  # ..
+    ],
+)
+def test_highlight_between_raises(arg, styler, map, axis):
+    msg = f"supplied '{arg}' is not correct shape"
+    with pytest.raises(ValueError, match=msg):
+        styler.highlight_between(**{arg: map, "axis": axis})._compute()
+
+
+def test_highlight_between_raises2(styler):
+    msg = "values can be 'both', 'left', 'right', or 'neither'"
+    with pytest.raises(ValueError, match=msg):
+        styler.highlight_between(inclusive="badstring")._compute()
+
+    with pytest.raises(ValueError, match=msg):
+        styler.highlight_between(inclusive=1)._compute()
+
+
+@pytest.mark.parametrize(
+    "inclusive, expected",
+    [
+        (
+            "both",
+            {
+                (0, 0): [("background-color", "yellow")],
+                (0, 1): [("background-color", "yellow")],
+            },
+        ),
+        ("neither", {}),
+        ("left", {(0, 0): [("background-color", "yellow")]}),
+        ("right", {(0, 1): [("background-color", "yellow")]}),
+    ],
+)
+def test_highlight_between_inclusive(styler, inclusive, expected):
+    kwargs = {"left": 0, "right": 1, "subset": IndexSlice[[0, 1], :]}
+    result = styler.highlight_between(**kwargs, inclusive=inclusive)._compute()
+    assert result.ctx == expected