coerce_extension

pandas/core/frame.py

@@ -30,6 +30,7 @@
                                _possibly_downcast_to_dtype,
                                _invalidate_string_dtypes,
                                _coerce_to_dtypes,
+                               _coerce_extension_to_embed,
                                _maybe_upcast_putmask,
                                _find_common_type)
 from pandas.types.common import (is_categorical_dtype,
@@ -2647,7 +2648,7 @@ def reindexer(value):
 
         # return internal types directly
         if is_extension_type(value):
-            return value
+            return _coerce_extension_to_embed(value)
 
         # broadcast across multiple columns if necessary
         if broadcast and key in self.columns and value.ndim == 1:

pandas/tests/frame/test_alter_axes.py

@@ -8,7 +8,7 @@
 
 from pandas.compat import lrange
 from pandas import (DataFrame, Series, Index, MultiIndex,
-                    RangeIndex, date_range)
+                    RangeIndex, date_range, IntervalIndex)
 import pandas as pd
 
 from pandas.util.testing import (assert_series_equal,
@@ -718,11 +718,33 @@ def test_set_index_preserve_categorical_dtype(self):
 
 class TestIntervalIndex(tm.TestCase):
 
-    def test_set_reset(self):
+    def test_setitem(self):
+
+        df = DataFrame({'A': range(10)})
+        s = pd.cut(df.A, 5)
+        self.assertIsInstance(s.cat.categories, IntervalIndex)
+
+        # these should end up the same, namely
+        # an object array of Intervals
+        df['B'] = s
+        df['C'] = np.array(s)
+        df['D'] = s.values
+        df['E'] = np.array(s.values)
+
+        self.assertTrue(df['B'].dtype == 'object')
+        self.assertTrue(df['C'].dtype == 'object')
+        self.assertTrue(df['D'].dtype == 'object')
+        self.assertTrue(df['E'].dtype == 'object')
+
+        tm.assert_series_equal(df['B'], df['C'], check_names=False)
+        tm.assert_series_equal(df['B'], df['D'], check_names=False)
+        tm.assert_series_equal(df['B'], df['E'], check_names=False)
+
+    def test_set_reset_index(self):
+
         df = DataFrame({'A': range(10)})
-        df['B'] = pd.cut(df.A, 5)
+        s = pd.cut(df.A, 5)
+        df['B'] = s
         df = df.set_index('B')
 
-        # TODO: this should actually be converted prior
-        self.assertTrue(isinstance(df.index, pd.CategoricalIndex))
         df = df.reset_index()

pandas/tests/indexing/test_interval.py

@@ -33,10 +33,10 @@ def test_loc_getitem_series(self):
     def test_loc_getitem_frame(self):
 
         df = DataFrame({'A': range(10)})
-        df['B'] = pd.cut(df.A, 5)
+        s = pd.cut(df.A, 5)
+        df['B'] = s
         df = df.set_index('B')
 
-        # TODO: fixme
-        # result = df.loc[4]
-        # expected = df.iloc[3]
-        # tm.assert_series_equal(result, expected)
+        result = df.loc[4]
+        expected = df.iloc[4:6]
+        tm.assert_frame_equal(result, expected)

pandas/types/cast.py

@@ -7,7 +7,7 @@
 from pandas.compat import string_types, text_type, PY3
 from .common import (_ensure_object, is_bool, is_integer, is_float,
                      is_complex, is_datetimetz, is_categorical_dtype,
-                     is_datetimelike,
+                     is_datetimelike, is_interval_dtype,
                      is_extension_type, is_object_dtype,
                      is_datetime64tz_dtype, is_datetime64_dtype,
                      is_timedelta64_dtype, is_dtype_equal,
@@ -484,6 +484,20 @@ def conv(r, dtype):
     return [conv(r, dtype) for r, dtype in zip(result, dtypes)]
 
 
+def _coerce_extension_to_embed(value):
+    """
+    we have an extension type, coerce it to a type
+    suitable for embedding (in a Series/DataFrame)
+    """
+
+    # TODO: maybe we should have a method on Categorical
+    # to actually do this instead
+    if is_categorical_dtype(value):
+        if is_interval_dtype(value.categories):
+            return np.array(value)
+
+    return value
+
 def _astype_nansafe(arr, dtype, copy=True):
     """ return a view if copy is False, but
         need to be very careful as the result shape could change! """