ENH: Styler.highlight_null can accepts subset argument

doc/source/whatsnew/v1.1.0.rst

@@ -64,6 +64,7 @@ Other enhancements
 ^^^^^^^^^^^^^^^^^^
 
 - :class:`Styler` may now render CSS more efficiently where multiple cells have the same styling (:issue:`30876`)
+- :meth:`Styler.highlight_null` now accepts ``subset`` argument (:issue:`31345`)
 - When writing directly to a sqlite connection :func:`to_sql` now supports the ``multi`` method (:issue:`29921`)
 - `OptionError` is now exposed in `pandas.errors` (:issue:`27553`)
 -

pandas/io/formats/style.py

@@ -1003,19 +1003,27 @@ def hide_columns(self, subset) -> "Styler":
  def _highlight_null(v, null_color: str) -> str:
  return f"background-color: {null_color}" if pd.isna(v) else ""
 
- def highlight_null(self, null_color: str = "red") -> "Styler":
+ def highlight_null(
+ self,
+ null_color: str = "red",
+ subset: Optional[Union[Label, Sequence[Label]]] = None,
+ ) -> "Styler":
  """
  Shade the background ``null_color`` for missing values.
 
  Parameters
  ----------
- null_color : str
+ null_color : str, default 'red'
+ subset : label or list of labels, default None
+ A valid slice for ``data`` to limit the style application to.
+
+ .. versionadded:: 1.1.0
 
  Returns
  -------
  self : Styler
  """
- self.applymap(self._highlight_null, null_color=null_color)
+ self.applymap(self._highlight_null, null_color=null_color, subset=subset)
  return self
 
  def background_gradient(

pandas/tests/io/formats/test_style.py

@@ -1091,6 +1091,23 @@ def test_highlight_null(self, null_color="red"):
  expected = {(0, 0): [""], (1, 0): ["background-color: red"]}
  assert result == expected
 
+ def test_highlight_null_subset(self):
+ # GH 31345
+ df = pd.DataFrame({"A": [0, np.nan], "B": [0, np.nan]})
+ result = (
+ df.style.highlight_null(null_color="red", subset=["A"])
+ .highlight_null(null_color="green", subset=["B"])
+ ._compute()
+ .ctx
+ )
+ expected = {
+ (0, 0): [""],
+ (1, 0): ["background-color: red"],
+ (0, 1): [""],
+ (1, 1): ["background-color: green"],
+ }
+ assert result == expected
+
  def test_nonunique_raises(self):
  df = pd.DataFrame([[1, 2]], columns=["A", "A"])
  with pytest.raises(ValueError):