From 9c24aa68d8ea6390ef2b819f2a2d524e4761cc9c Mon Sep 17 00:00:00 2001
From: Henry Hammond <henryhhammond92@gmail.com>
Date: Tue, 19 Jan 2016 10:50:44 -0500
Subject: [PATCH] Added index column header for styles

---
 doc/source/whatsnew/v0.18.0.txt |  1 +
 pandas/core/style.py            | 18 +++++++++++++++++
 pandas/tests/test_style.py      | 34 +++++++++++++++++++++++++++++++++
 3 files changed, 53 insertions(+)

diff --git a/doc/source/whatsnew/v0.18.0.txt b/doc/source/whatsnew/v0.18.0.txt
index db9cf5ae86d39..3fce0939445d7 100644
--- a/doc/source/whatsnew/v0.18.0.txt
+++ b/doc/source/whatsnew/v0.18.0.txt
@@ -538,3 +538,4 @@ of columns didn't match the number of series provided (:issue:`12039`).
 - Bug in ``Series`` constructor with read-only data (:issue:`11502`)
 
 - Bug in ``.loc`` setitem indexer preventing the use of a TZ-aware DatetimeIndex (:issue:`12050`)
+- Big in ``.style`` indexes and multi-indexes not appearing (:issue:`11655`)
diff --git a/pandas/core/style.py b/pandas/core/style.py
index d8cb53e04ea03..203eda4fdf338 100644
--- a/pandas/core/style.py
+++ b/pandas/core/style.py
@@ -206,6 +206,24 @@ def _translate(self):
                                "class": " ".join(cs)})
             head.append(row_es)
 
+        if self.data.index.names:
+            index_header_row = []
+
+            for c, name in enumerate(self.data.index.names):
+                cs = [COL_HEADING_CLASS,
+                      "level%s" % (n_clvls + 1),
+                      "col%s" % c]
+                index_header_row.append({"type": "th", "value": name,
+                                         "class": " ".join(cs)})
+
+            index_header_row.extend(
+                [{"type": "th",
+                  "value": BLANK_VALUE,
+                  "class": " ".join([BLANK_CLASS])
+                  }] * len(clabels[0]))
+
+            head.append(index_header_row)
+
         body = []
         for r, idx in enumerate(self.data.index):
             cs = [ROW_HEADING_CLASS, "level%s" % c, "row%s" % r]
diff --git a/pandas/tests/test_style.py b/pandas/tests/test_style.py
index fd8540fdf9c0a..b9ca3f331711d 100644
--- a/pandas/tests/test_style.py
+++ b/pandas/tests/test_style.py
@@ -130,6 +130,40 @@ def test_set_properties_subset(self):
         expected = {(0, 0): ['color: white']}
         self.assertEqual(result, expected)
 
+    def test_index_name(self):
+        # https://github.com/pydata/pandas/issues/11655
+        df = pd.DataFrame({'A': [1, 2], 'B': [3, 4], 'C': [5, 6]})
+        result = df.set_index('A').style._translate()
+
+        expected = [[{'class': 'blank', 'type': 'th', 'value': ''},
+                     {'class': 'col_heading level0 col0', 'type': 'th',
+                      'value': 'B'},
+                     {'class': 'col_heading level0 col1', 'type': 'th',
+                      'value': 'C'}],
+                    [{'class': 'col_heading level2 col0', 'type': 'th',
+                      'value': 'A'},
+                     {'class': 'blank', 'type': 'th', 'value': ''},
+                     {'class': 'blank', 'type': 'th', 'value': ''}]]
+
+        self.assertEqual(result['head'], expected)
+
+    def test_multiindex_name(self):
+        # https://github.com/pydata/pandas/issues/11655
+        df = pd.DataFrame({'A': [1, 2], 'B': [3, 4], 'C': [5, 6]})
+        result = df.set_index(['A', 'B']).style._translate()
+
+        expected = [[{'class': 'blank', 'type': 'th', 'value': ''},
+                     {'class': 'blank', 'type': 'th', 'value': ''},
+                     {'class': 'col_heading level0 col0', 'type': 'th',
+                      'value': 'C'}],
+                    [{'class': 'col_heading level2 col0', 'type': 'th',
+                      'value': 'A'},
+                     {'class': 'col_heading level2 col1', 'type': 'th',
+                      'value': 'B'},
+                     {'class': 'blank', 'type': 'th', 'value': ''}]]
+
+        self.assertEqual(result['head'], expected)
+
     def test_apply_axis(self):
         df = pd.DataFrame({'A': [0, 0], 'B': [1, 1]})
         f = lambda x: ['val: %s' % x.max() for v in x]