ENH: Styler.bar: properly support NaNs

Author: soxofaan

doc/source/whatsnew/v0.24.0.txt

@@ -686,7 +686,7 @@ Other
 - :meth:`~pandas.io.formats.style.Styler.background_gradient` now takes a ``text_color_threshold`` parameter to automatically lighten the text color based on the luminance of the background color. This improves readability with dark background colors without the need to limit the background colormap range. (:issue:`21258`)
 - Require at least 0.28.2 version of ``cython`` to support read-only memoryviews (:issue:`21688`)
 - :meth:`~pandas.io.formats.style.Styler.background_gradient` now also supports tablewise application (in addition to rowwise and columnwise) with ``axis=None`` (:issue:`15204`)
-- :meth:`~pandas.io.formats.style.Styler.bar` now also supports tablewise application (in addition to rowwise and columnwise) with ``axis=None`` and setting clipping range with ``vmin`` and ``vmax`` (:issue:`21548` and :issue:`21526`)
+- :meth:`~pandas.io.formats.style.Styler.bar` now also supports tablewise application (in addition to rowwise and columnwise) with ``axis=None`` and setting clipping range with ``vmin`` and ``vmax`` (:issue:`21548` and :issue:`21526`). ``NaN`` values are also handled properly.
 -
 -
 -

pandas/io/formats/style.py

@@ -997,8 +997,8 @@ def _bar(s, align, colors, width=100, vmin=None, vmax=None):
         """Draw bar chart in dataframe cells"""
 
         # Get input value range.
-        smin = s.values.min() if vmin is None else vmin
-        smax = s.values.max() if vmax is None else vmax
+        smin = s.min().min() if vmin is None else vmin
+        smax = s.max().max() if vmax is None else vmax
         if align == 'mid':
             smin = min(0, smin)
             smax = max(0, smax)
@@ -1025,6 +1025,8 @@ def css_bar(start, end, color):
             return css
 
         def css(x):
+            if pd.isna(x):
+                return ''
             if align == 'left':
                 return css_bar(0, x, colors[x > zero])
             else:

pandas/tests/io/formats/test_style.py

@@ -651,6 +651,45 @@ def test_bar_align_mid_vmin_vmax_clipping(self):
         }
         assert result == expected
 
+    def test_bar_align_mid_nans(self):
+        df = pd.DataFrame({'A': [1, None], 'B': [-1, 3]})
+        result = df.style.bar(align='mid', axis=None)._compute().ctx
+        expected = {
+            (0, 0): ['width: 10em', ' height: 80%',
+                     'background: linear-gradient(90deg, '
+                     'transparent 25.0%, #d65f5f 25.0%, '
+                     '#d65f5f 50.0%, transparent 50.0%)'],
+            (1, 0): [''],
+            (0, 1): ['width: 10em', ' height: 80%',
+                     'background: linear-gradient(90deg,'
+                     '#d65f5f 25.0%, transparent 25.0%)'],
+            (1, 1): ['width: 10em', ' height: 80%',
+                     'background: linear-gradient(90deg, '
+                     'transparent 25.0%, #d65f5f 25.0%, '
+                     '#d65f5f 100.0%, transparent 100.0%)']
+        }
+        assert result == expected
+
+    def test_bar_align_zero_nans(self):
+        df = pd.DataFrame({'A': [1, None], 'B': [-1, 2]})
+        result = df.style.bar(align='zero', axis=None)._compute().ctx
+        expected = {
+            (0, 0): ['width: 10em', ' height: 80%',
+                     'background: linear-gradient(90deg, '
+                     'transparent 50.0%, #d65f5f 50.0%, '
+                     '#d65f5f 75.0%, transparent 75.0%)'],
+            (1, 0): [''],
+            (0, 1): ['width: 10em', ' height: 80%',
+                     'background: linear-gradient(90deg, '
+                     'transparent 25.0%, #d65f5f 25.0%, '
+                     '#d65f5f 50.0%, transparent 50.0%)'],
+            (1, 1): ['width: 10em', ' height: 80%',
+                     'background: linear-gradient(90deg, '
+                     'transparent 50.0%, #d65f5f 50.0%, '
+                     '#d65f5f 100.0%, transparent 100.0%)']
+        }
+        assert result == expected
+
     def test_bar_bad_align_raises(self):
         df = pd.DataFrame({'A': [-100, -60, -30, -20]})
         with pytest.raises(ValueError):