ENH: Added more options for formats.style.bar

You can now have the bar be centered on zero or midpoint value (in addition to the already existing way of having the min value at the left side of the cell)

Author: jmarrec

pandas/formats/style.py

@@ -17,7 +17,7 @@
  "or `pip install Jinja2`"
  raise ImportError(msg)
 
-from pandas.types.common import is_float, is_string_like
+from pandas.types.common import is_float, is_string_like, is_list_like
 
 import numpy as np
 import pandas as pd
@@ -857,38 +857,151 @@ def set_properties(self, subset=None, **kwargs):
  return self.applymap(f, subset=subset)
 
  @staticmethod
- def _bar(s, color, width):
- normed = width * (s - s.min()) / (s.max() - s.min())
+ def _bar_left(s, color, width):
+ """
+ The minimum value is aligned at the left of the cell
+ .. versionadded:: 0.17.1
 
+ Parameters
+ ----------
+ color: 2-tuple/list, of [``color_negative``, ``color_positive``]
+
+ Returns
+ -------
+ self : Styler
+ """
+ normed = width * (s - s.min()) / (s.max() - s.min())
+ zero_normed = width * (0 - s.min()) / (s.max() - s.min())
  base = 'width: 10em; height: 80%;'
  attrs = (base + 'background: linear-gradient(90deg,{c} {w}%, '
  'transparent 0%)')
- return [attrs.format(c=color, w=x) if x != 0 else base for x in normed]
 
- def bar(self, subset=None, axis=0, color='#d65f5f', width=100):
+ return [base if x == 0 else attrs.format(c=color[0], w=x)
+ if x < zero_normed
+ else attrs.format(c=color[1], w=x) if x >= zero_normed
+ else base for x in normed]
+
+ @staticmethod
+ def _bar_center_zero(s, color, width):
+ """
+ Creates a bar chart where the zero is centered in the cell
+ .. versionadded:: 0.19.2
+
+ Parameters
+ ----------
+ color: 2-tuple/list, of [``color_negative``, ``color_positive``]
+
+ Returns
+ -------
+ self : Styler
+ """
+
+ # Either the min or the max should reach the edge
+ # (50%, centered on zero)
+ m = max(abs(s.min()), abs(s.max()))
+
+ normed = s * 50 * width / (100 * m)
+
+ base = 'width: 10em; height: 80%;'
+
+ attrs_neg = (base + 'background: linear-gradient(90deg, transparent 0%, transparent {w}%, {c} {w}%, '
+ '{c} 50%, transparent 50%)')
+
+ attrs_pos = (base + 'background: linear-gradient(90deg, transparent 0%, transparent 50%, {c} 50%, {c} {w}%, '
+ 'transparent {w}%)')
+
+ return [attrs_pos.format(c=color[1], w=(50 + x)) if x >= 0
+ else attrs_neg.format(c=color[0], w=(50 + x))
+ for x in normed]
+
+ @staticmethod
+ def _bar_center_mid(s, color, width):
+ """
+ Creates a bar chart where the midpoint is centered in the cell
+ .. versionadded:: 0.19.2
+
+ Parameters
+ ----------
+ color: 2-tuple/list, of [``color_negative``, ``color_positive``]
+
+ Returns
+ -------
+ self : Styler
+ """
+
+ if s.min() >= 0:
+ # In this case, we place the zero at the left, and the max() should
+ # be at width
+ zero = 0
+ slope = width / s.max()
+ elif s.max() <= 0:
+ # In this case, we place the zero at the right, and the min()
+ # should be at 100-width
+ zero = 100
+ slope = width / -s.min()
+ else:
+ slope = width / (s.max() - s.min())
+ zero = (100 + width) / 2 - slope * s.max()
+
+ normed = zero + slope * s
+
+ base = 'width: 10em; height: 80%;'
+
+ attrs_neg = (base + 'background: linear-gradient(90deg, transparent 0%, transparent {w}%, {c} {w}%, '
+ '{c} {zero}%, transparent {zero}%)')
+
+ attrs_pos = (base + 'background: linear-gradient(90deg, transparent 0%, transparent {zero}%, {c} {zero}%, {c} {w}%, '
+ 'transparent {w}%)')
+
+ return [attrs_pos.format(c=color[1], zero=zero, w=x) if x > zero
+ else attrs_neg.format(c=color[0], zero=zero, w=x)
+ for x in normed]
+
+ def bar(self, subset=None, align='left', axis=0, color='#d65f5f', width=100):
  """
  Color the background ``color`` proptional to the values in each column.
  Excludes non-numeric data by default.
-
  .. versionadded:: 0.17.1
 
  Parameters
  ----------
  subset: IndexSlice, default None
  a valid slice for ``data`` to limit the style application to
  axis: int
- color: str
+ color: str (for align='left') or 2-tuple/list (for align='zero', 'mid')
+ If a str is passed, the color is the same for both 
+ negative and positive numbers. If 2-tuple/list is used, the
+ first element is the color_negative and the second is the 
+ color_positive (eg: ['d65f5f', '5fba7d'])
  width: float
  A number between 0 or 100. The largest value will cover ``width``
  percent of the cell's width
+ align : str, default 'left'
+ .. versionadded:: 0.19.2
+ - 'left' : the min value starts at the left of the cell
+ - 'zero' : a value of zero is located at the center of the cell
+ - 'mid' : the center of the cell is at (max-min)/2, or
+ if values are all negative (positive) the zero is aligned
+ at the right (left) of the cell
 
  Returns
  -------
  self : Styler
  """
  subset = _maybe_numeric_slice(self.data, subset)
  subset = _non_reducing_slice(subset)
- self.apply(self._bar, subset=subset, axis=axis, color=color,
+
+ if not(is_list_like(color)):
+ color = [color, color]
+
+ if align == 'left':
+ self.apply(self._bar_left, subset=subset, axis=axis, color=color,
+ width=width)
+ elif align == 'zero':
+ self.apply(self._bar_center_zero, subset=subset, axis=axis, color=color,
+ width=width)
+ elif align == 'mid':
+ self.apply(self._bar_center_mid, subset=subset, axis=axis, color=color,
  width=width)
  return self
 

pandas/tests/formats/test_style.py

@@ -265,7 +265,7 @@ def test_empty(self):
  {'props': [['', '']], 'selector': 'row1_col0'}]
  self.assertEqual(result, expected)
 
- def test_bar(self):
+ def test_bar_align_left(self):
  df = pd.DataFrame({'A': [0, 1, 2]})
  result = df.style.bar()._compute().ctx
  expected = {
@@ -298,7 +298,7 @@ def test_bar(self):
  result = df.style.bar(color='red', width=50)._compute().ctx
  self.assertEqual(result, expected)
 
- def test_bar_0points(self):
+ def test_bar_align_left_0points(self):
  df = pd.DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
  result = df.style.bar()._compute().ctx
  expected = {(0, 0): ['width: 10em', ' height: 80%'],
@@ -348,6 +348,89 @@ def test_bar_0points(self):
  ', transparent 0%)']}
  self.assertEqual(result, expected)
 
+ def test_bar_align_zero_pos_and_neg(self):
+ df = pd.DataFrame({'A': [-10, 0, 20, 90]})
+
+ result = df.style.bar(align='zero', color=[
+ '#d65f5f', '#5fba7d'], width=90)._compute().ctx
+
+ expected = {(0, 0): ['width: 10em',
+ ' height: 80%',
+ 'background: linear-gradient(90deg, transparent 0%, transparent 45.0%, #d65f5f 45.0%, #d65f5f 50%, transparent 50%)'],
+ (1, 0): ['width: 10em',
+ ' height: 80%',
+ 'background: linear-gradient(90deg, transparent 0%, transparent 50%, #5fba7d 50%, #5fba7d 50.0%, transparent 50.0%)'],
+ (2, 0): ['width: 10em',
+ ' height: 80%',
+ 'background: linear-gradient(90deg, transparent 0%, transparent 50%, #5fba7d 50%, #5fba7d 60.0%, transparent 60.0%)'],
+ (3, 0): ['width: 10em',
+ ' height: 80%',
+ 'background: linear-gradient(90deg, transparent 0%, transparent 50%, #5fba7d 50%, #5fba7d 95.0%, transparent 95.0%)']}
+ self.assertEqual(result, expected)
+
+ def test_bar_align_mid_pos_and_neg(self):
+ df = pd.DataFrame({'A': [-10, 0, 20, 90]})
+
+ result = df.style.bar(align='mid', color=[
+ '#d65f5f', '#5fba7d'])._compute().ctx
+
+ expected = {(0, 0): ['width: 10em',
+ ' height: 80%',
+ 'background: linear-gradient(90deg, transparent 0%, transparent 0.0%, #d65f5f 0.0%, #d65f5f 10.0%, transparent 10.0%)'],
+ (1, 0): ['width: 10em',
+ ' height: 80%',
+ 'background: linear-gradient(90deg, transparent 0%, transparent 10.0%, #d65f5f 10.0%, #d65f5f 10.0%, transparent 10.0%)'],
+ (2, 0): ['width: 10em',
+ ' height: 80%',
+ 'background: linear-gradient(90deg, transparent 0%, transparent 10.0%, #5fba7d 10.0%, #5fba7d 30.0%, transparent 30.0%)'],
+ (3, 0): ['width: 10em',
+ ' height: 80%',
+ 'background: linear-gradient(90deg, transparent 0%, transparent 10.0%, #5fba7d 10.0%, #5fba7d 100.0%, transparent 100.0%)']}
+
+ self.assertEqual(result, expected)
+
+ def test_bar_align_mid_all_pos(self):
+ df = pd.DataFrame({'A': [10, 20, 50, 100]})
+
+ result = df.style.bar(align='mid', color=[
+ '#d65f5f', '#5fba7d'])._compute().ctx
+
+ expected = {(0, 0): ['width: 10em',
+ ' height: 80%',
+ 'background: linear-gradient(90deg, transparent 0%, transparent 0%, #5fba7d 0%, #5fba7d 10.0%, transparent 10.0%)'],
+ (1, 0): ['width: 10em',
+ ' height: 80%',
+ 'background: linear-gradient(90deg, transparent 0%, transparent 0%, #5fba7d 0%, #5fba7d 20.0%, transparent 20.0%)'],
+ (2, 0): ['width: 10em',
+ ' height: 80%',
+ 'background: linear-gradient(90deg, transparent 0%, transparent 0%, #5fba7d 0%, #5fba7d 50.0%, transparent 50.0%)'],
+ (3, 0): ['width: 10em',
+ ' height: 80%',
+ 'background: linear-gradient(90deg, transparent 0%, transparent 0%, #5fba7d 0%, #5fba7d 100.0%, transparent 100.0%)']}
+
+ self.assertEqual(result, expected)
+
+ def test_bar_align_mid_all_neg(self):
+ df = pd.DataFrame({'A': [-100, -60, -30, -20]})
+
+ result = df.style.bar(align='mid', color=[
+ '#d65f5f', '#5fba7d'])._compute().ctx
+
+ expected = {(0, 0): ['width: 10em',
+ ' height: 80%',
+ 'background: linear-gradient(90deg, transparent 0%, transparent 0.0%, #d65f5f 0.0%, #d65f5f 100%, transparent 100%)'],
+ (1, 0): ['width: 10em',
+ ' height: 80%',
+ 'background: linear-gradient(90deg, transparent 0%, transparent 40.0%, #d65f5f 40.0%, #d65f5f 100%, transparent 100%)'],
+ (2, 0): ['width: 10em',
+ ' height: 80%',
+ 'background: linear-gradient(90deg, transparent 0%, transparent 70.0%, #d65f5f 70.0%, #d65f5f 100%, transparent 100%)'],
+ (3, 0): ['width: 10em',
+ ' height: 80%',
+ 'background: linear-gradient(90deg, transparent 0%, transparent 80.0%, #d65f5f 80.0%, #d65f5f 100%, transparent 100%)']}
+
+ self.assertEqual(result, expected)
+
  def test_highlight_null(self, null_color='red'):
  df = pd.DataFrame({'A': [0, np.nan]})
  result = df.style.highlight_null()._compute().ctx