ENH: add styler option context for sparsification of columns and index separately

asv_bench/benchmarks/io/style.py

@@ -20,19 +20,19 @@ def setup(self, cols, rows):
 
     def time_apply_render(self, cols, rows):
         self._style_apply()
-        self.st._render_html()
+        self.st._render_html(True, True)
 
     def peakmem_apply_render(self, cols, rows):
         self._style_apply()
-        self.st._render_html()
+        self.st._render_html(True, True)
 
     def time_classes_render(self, cols, rows):
         self._style_classes()
-        self.st._render_html()
+        self.st._render_html(True, True)
 
     def peakmem_classes_render(self, cols, rows):
         self._style_classes()
-        self.st._render_html()
+        self.st._render_html(True, True)
 
     def time_format_render(self, cols, rows):
         self._style_format()

doc/source/user_guide/options.rst

@@ -482,6 +482,11 @@ plotting.backend                        matplotlib   Change the plotting backend
                                                      like Bokeh, Altair, etc.
 plotting.matplotlib.register_converters True         Register custom converters with
                                                      matplotlib. Set to False to de-register.
+styler.sparse.index                     True         "Sparsify" MultiIndex display for rows
+                                                     in Styler output (don't display repeated
+                                                     elements in outer levels within groups).
+styler.sparse.columns                   True         "Sparsify" MultiIndex display for columns
+                                                     in Styler output.
 ======================================= ============ ==================================
 
 

doc/source/whatsnew/v1.3.0.rst

@@ -139,6 +139,7 @@ precision, and perform HTML escaping (:issue:`40437` :issue:`40134`). There have
 properly format HTML and eliminate some inconsistencies (:issue:`39942` :issue:`40356` :issue:`39807` :issue:`39889` :issue:`39627`)
 
 :class:`.Styler` has also been compatible with non-unique index or columns, at least for as many features as are fully compatible, others made only partially compatible (:issue:`41269`).
+One also has greater control of the display through separate sparsification of the index or columns, using the new 'styler' options context (:issue:`41142`).
 
 Documentation has also seen major revisions in light of new features (:issue:`39720` :issue:`39317` :issue:`40493`)
 

pandas/core/config_init.py

@@ -726,3 +726,26 @@ def register_converter_cb(key):
         validator=is_one_of_factory(["auto", True, False]),
         cb=register_converter_cb,
     )
+
+# ------
+# Styler
+# ------
+
+styler_sparse_index_doc = """
+: bool
+    Whether to sparsify the display of a hierarchical index. Setting to False will
+    display each explicit level element in a hierarchical key for each row.
+"""
+
+styler_sparse_columns_doc = """
+: bool
+    Whether to sparsify the display of hierarchical columns. Setting to False will
+    display each explicit level element in a hierarchical key for each column.
+"""
+
+with cf.config_prefix("styler"):
+    cf.register_option("sparse.index", True, styler_sparse_index_doc, validator=bool)
+
+    cf.register_option(
+        "sparse.columns", True, styler_sparse_columns_doc, validator=bool
+    )

pandas/io/formats/style.py

@@ -17,6 +17,8 @@
 
 import numpy as np
 
+from pandas._config import get_option
+
 from pandas._typing import (
     Axis,
     FrameOrSeries,
@@ -201,14 +203,27 @@ def _repr_html_(self) -> str:
         """
         Hooks into Jupyter notebook rich display system.
         """
-        return self._render_html()
+        return self.render()
 
-    def render(self, **kwargs) -> str:
+    def render(
+        self,
+        sparse_index: bool | None = None,
+        sparse_columns: bool | None = None,
+        **kwargs,
+    ) -> str:
         """
         Render the ``Styler`` including all applied styles to HTML.
 
         Parameters
         ----------
+        sparse_index : bool, optional
+            Whether to sparsify the display of a hierarchical index. Setting to False
+            will display each explicit level element in a hierarchical key for each row.
+            Defaults to ``pandas.options.styler.sparse.index`` value.
+        sparse_columns : bool, optional
+            Whether to sparsify the display of a hierarchical index. Setting to False
+            will display each explicit level element in a hierarchical key for each row.
+            Defaults to ``pandas.options.styler.sparse.columns`` value.
         **kwargs
             Any additional keyword arguments are passed
             through to ``self.template.render``.
@@ -240,7 +255,11 @@ def render(self, **kwargs) -> str:
         * caption
         * table_attributes
         """
-        return self._render_html(**kwargs)
+        if sparse_index is None:
+            sparse_index = get_option("styler.sparse.index")
+        if sparse_columns is None:
+            sparse_columns = get_option("styler.sparse.columns")
+        return self._render_html(sparse_index, sparse_columns, **kwargs)
 
     def set_tooltips(
         self,

pandas/io/formats/style_render.py

@@ -107,14 +107,14 @@ def __init__(
             tuple[int, int], Callable[[Any], str]
         ] = defaultdict(lambda: partial(_default_formatter, precision=def_precision))
 
-    def _render_html(self, **kwargs) -> str:
+    def _render_html(self, sparse_index: bool, sparse_columns: bool, **kwargs) -> str:
         """
         Renders the ``Styler`` including all applied styles to HTML.
         Generates a dict with necessary kwargs passed to jinja2 template.
         """
         self._compute()
         # TODO: namespace all the pandas keys
-        d = self._translate()
+        d = self._translate(sparse_index, sparse_columns)
         d.update(kwargs)
         return self.template_html.render(**d)
 
@@ -133,9 +133,7 @@ def _compute(self):
             r = func(self)(*args, **kwargs)
         return r
 
-    def _translate(
-        self, sparsify_index: bool | None = None, sparsify_cols: bool | None = None
-    ):
+    def _translate(self, sparse_index: bool, sparse_cols: bool):
         """
         Process Styler data and settings into a dict for template rendering.
 
@@ -144,22 +142,19 @@ def _translate(
 
         Parameters
         ----------
-        sparsify_index : bool, optional
-            Whether to sparsify the index or print all hierarchical index elements
-        sparsify_cols : bool, optional
-            Whether to sparsify the columns or print all hierarchical column elements
+        sparse_index : bool
+            Whether to sparsify the index or print all hierarchical index elements.
+            Upstream defaults are typically to `pandas.options.styler.sparse.index`.
+        sparse_cols : bool
+            Whether to sparsify the columns or print all hierarchical column elements.
+            Upstream defaults are typically to `pandas.options.styler.sparse.columns`.
 
         Returns
         -------
         d : dict
             The following structure: {uuid, table_styles, caption, head, body,
             cellstyle, table_attributes}
         """
-        if sparsify_index is None:
-            sparsify_index = get_option("display.multi_sparse")
-        if sparsify_cols is None:
-            sparsify_cols = get_option("display.multi_sparse")
-
         ROW_HEADING_CLASS = "row_heading"
         COL_HEADING_CLASS = "col_heading"
         INDEX_NAME_CLASS = "index_name"
@@ -176,14 +171,14 @@ def _translate(
         }
 
         head = self._translate_header(
-            BLANK_CLASS, BLANK_VALUE, INDEX_NAME_CLASS, COL_HEADING_CLASS, sparsify_cols
+            BLANK_CLASS, BLANK_VALUE, INDEX_NAME_CLASS, COL_HEADING_CLASS, sparse_cols
         )
         d.update({"head": head})
 
         self.cellstyle_map: DefaultDict[tuple[CSSPair, ...], list[str]] = defaultdict(
             list
         )
-        body = self._translate_body(DATA_CLASS, ROW_HEADING_CLASS, sparsify_index)
+        body = self._translate_body(DATA_CLASS, ROW_HEADING_CLASS, sparse_index)
         d.update({"body": body})
 
         cellstyle: list[dict[str, CSSList | list[str]]] = [

pandas/tests/io/formats/style/test_format.py

@@ -28,28 +28,28 @@ def styler(df):
 
 
 def test_display_format(styler):
-    ctx = styler.format("{:0.1f}")._translate()
+    ctx = styler.format("{:0.1f}")._translate(True, True)
     assert all(["display_value" in c for c in row] for row in ctx["body"])
     assert all([len(c["display_value"]) <= 3 for c in row[1:]] for row in ctx["body"])
     assert len(ctx["body"][0][1]["display_value"].lstrip("-")) <= 3
 
 
 def test_format_dict(styler):
-    ctx = styler.format({"A": "{:0.1f}", "B": "{0:.2%}"})._translate()
+    ctx = styler.format({"A": "{:0.1f}", "B": "{0:.2%}"})._translate(True, True)
     assert ctx["body"][0][1]["display_value"] == "0.0"
     assert ctx["body"][0][2]["display_value"] == "-60.90%"
 
 
 def test_format_string(styler):
-    ctx = styler.format("{:.2f}")._translate()
+    ctx = styler.format("{:.2f}")._translate(True, True)
     assert ctx["body"][0][1]["display_value"] == "0.00"
     assert ctx["body"][0][2]["display_value"] == "-0.61"
     assert ctx["body"][1][1]["display_value"] == "1.00"
     assert ctx["body"][1][2]["display_value"] == "-1.23"
 
 
 def test_format_callable(styler):
-    ctx = styler.format(lambda v: "neg" if v < 0 else "pos")._translate()
+    ctx = styler.format(lambda v: "neg" if v < 0 else "pos")._translate(True, True)
     assert ctx["body"][0][1]["display_value"] == "pos"
     assert ctx["body"][0][2]["display_value"] == "neg"
     assert ctx["body"][1][1]["display_value"] == "pos"
@@ -60,17 +60,17 @@ def test_format_with_na_rep():
     # GH 21527 28358
     df = DataFrame([[None, None], [1.1, 1.2]], columns=["A", "B"])
 
-    ctx = df.style.format(None, na_rep="-")._translate()
+    ctx = df.style.format(None, na_rep="-")._translate(True, True)
     assert ctx["body"][0][1]["display_value"] == "-"
     assert ctx["body"][0][2]["display_value"] == "-"
 
-    ctx = df.style.format("{:.2%}", na_rep="-")._translate()
+    ctx = df.style.format("{:.2%}", na_rep="-")._translate(True, True)
     assert ctx["body"][0][1]["display_value"] == "-"
     assert ctx["body"][0][2]["display_value"] == "-"
     assert ctx["body"][1][1]["display_value"] == "110.00%"
     assert ctx["body"][1][2]["display_value"] == "120.00%"
 
-    ctx = df.style.format("{:.2%}", na_rep="-", subset=["B"])._translate()
+    ctx = df.style.format("{:.2%}", na_rep="-", subset=["B"])._translate(True, True)
     assert ctx["body"][0][2]["display_value"] == "-"
     assert ctx["body"][1][2]["display_value"] == "120.00%"
 
@@ -85,13 +85,13 @@ def test_format_non_numeric_na():
     )
 
     with tm.assert_produces_warning(FutureWarning):
-        ctx = df.style.set_na_rep("NA")._translate()
+        ctx = df.style.set_na_rep("NA")._translate(True, True)
     assert ctx["body"][0][1]["display_value"] == "NA"
     assert ctx["body"][0][2]["display_value"] == "NA"
     assert ctx["body"][1][1]["display_value"] == "NA"
     assert ctx["body"][1][2]["display_value"] == "NA"
 
-    ctx = df.style.format(None, na_rep="-")._translate()
+    ctx = df.style.format(None, na_rep="-")._translate(True, True)
     assert ctx["body"][0][1]["display_value"] == "-"
     assert ctx["body"][0][2]["display_value"] == "-"
     assert ctx["body"][1][1]["display_value"] == "-"
@@ -150,19 +150,19 @@ def test_format_with_precision():
     df = DataFrame(data=[[1.0, 2.0090], [3.2121, 4.566]], columns=["a", "b"])
     s = Styler(df)
 
-    ctx = s.format(precision=1)._translate()
+    ctx = s.format(precision=1)._translate(True, True)
     assert ctx["body"][0][1]["display_value"] == "1.0"
     assert ctx["body"][0][2]["display_value"] == "2.0"
     assert ctx["body"][1][1]["display_value"] == "3.2"
     assert ctx["body"][1][2]["display_value"] == "4.6"
 
-    ctx = s.format(precision=2)._translate()
+    ctx = s.format(precision=2)._translate(True, True)
     assert ctx["body"][0][1]["display_value"] == "1.00"
     assert ctx["body"][0][2]["display_value"] == "2.01"
     assert ctx["body"][1][1]["display_value"] == "3.21"
     assert ctx["body"][1][2]["display_value"] == "4.57"
 
-    ctx = s.format(precision=3)._translate()
+    ctx = s.format(precision=3)._translate(True, True)
     assert ctx["body"][0][1]["display_value"] == "1.000"
     assert ctx["body"][0][2]["display_value"] == "2.009"
     assert ctx["body"][1][1]["display_value"] == "3.212"
@@ -173,26 +173,28 @@ def test_format_subset():
     df = DataFrame([[0.1234, 0.1234], [1.1234, 1.1234]], columns=["a", "b"])
     ctx = df.style.format(
         {"a": "{:0.1f}", "b": "{0:.2%}"}, subset=IndexSlice[0, :]
-    )._translate()
+    )._translate(True, True)
     expected = "0.1"
     raw_11 = "1.123400"
     assert ctx["body"][0][1]["display_value"] == expected
     assert ctx["body"][1][1]["display_value"] == raw_11
     assert ctx["body"][0][2]["display_value"] == "12.34%"
 
-    ctx = df.style.format("{:0.1f}", subset=IndexSlice[0, :])._translate()
+    ctx = df.style.format("{:0.1f}", subset=IndexSlice[0, :])._translate(True, True)
     assert ctx["body"][0][1]["display_value"] == expected
     assert ctx["body"][1][1]["display_value"] == raw_11
 
-    ctx = df.style.format("{:0.1f}", subset=IndexSlice["a"])._translate()
+    ctx = df.style.format("{:0.1f}", subset=IndexSlice["a"])._translate(True, True)
     assert ctx["body"][0][1]["display_value"] == expected
     assert ctx["body"][0][2]["display_value"] == "0.123400"
 
-    ctx = df.style.format("{:0.1f}", subset=IndexSlice[0, "a"])._translate()
+    ctx = df.style.format("{:0.1f}", subset=IndexSlice[0, "a"])._translate(True, True)
     assert ctx["body"][0][1]["display_value"] == expected
     assert ctx["body"][1][1]["display_value"] == raw_11
 
-    ctx = df.style.format("{:0.1f}", subset=IndexSlice[[0, 1], ["a"]])._translate()
+    ctx = df.style.format("{:0.1f}", subset=IndexSlice[[0, 1], ["a"]])._translate(
+        True, True
+    )
     assert ctx["body"][0][1]["display_value"] == expected
     assert ctx["body"][1][1]["display_value"] == "1.1"
     assert ctx["body"][0][2]["display_value"] == "0.123400"
@@ -206,19 +208,19 @@ def test_format_thousands(formatter, decimal, precision):
     s = DataFrame([[1000000.123456789]]).style  # test float
     result = s.format(
         thousands="_", formatter=formatter, decimal=decimal, precision=precision
-    )._translate()
+    )._translate(True, True)
     assert "1_000_000" in result["body"][0][1]["display_value"]
 
     s = DataFrame([[1000000]]).style  # test int
     result = s.format(
         thousands="_", formatter=formatter, decimal=decimal, precision=precision
-    )._translate()
+    )._translate(True, True)
     assert "1_000_000" in result["body"][0][1]["display_value"]
 
     s = DataFrame([[1 + 1000000.123456789j]]).style  # test complex
     result = s.format(
         thousands="_", formatter=formatter, decimal=decimal, precision=precision
-    )._translate()
+    )._translate(True, True)
     assert "1_000_000" in result["body"][0][1]["display_value"]
 
 
@@ -229,11 +231,11 @@ def test_format_decimal(formatter, thousands, precision):
     s = DataFrame([[1000000.123456789]]).style  # test float
     result = s.format(
         decimal="_", formatter=formatter, thousands=thousands, precision=precision
-    )._translate()
+    )._translate(True, True)
     assert "000_123" in result["body"][0][1]["display_value"]
 
     s = DataFrame([[1 + 1000000.123456789j]]).style  # test complex
     result = s.format(
         decimal="_", formatter=formatter, thousands=thousands, precision=precision
-    )._translate()
+    )._translate(True, True)
     assert "000_123" in result["body"][0][1]["display_value"]

pandas/tests/io/formats/style/test_non_unique.py

@@ -108,7 +108,7 @@ def test_set_td_classes_non_unique_raises(styler):
 
 
 def test_hide_columns_non_unique(styler):
-    ctx = styler.hide_columns(["d"])._translate()
+    ctx = styler.hide_columns(["d"])._translate(True, True)
 
     assert ctx["head"][0][1]["display_value"] == "c"
     assert ctx["head"][0][1]["is_visible"] is True