PERF: nested dict DataFrame construction

doc/source/whatsnew/v0.17.0.txt

@@ -1032,6 +1032,7 @@ Performance Improvements
 - Improved performance of ``to_datetime`` when specified format string is ISO8601 (:issue:`10178`)
 - 2x improvement of ``Series.value_counts`` for float dtype (:issue:`10821`)
 - Enable ``infer_datetime_format`` in ``to_datetime`` when date components do not have 0 padding (:issue:`11142`)
+- Regression from 0.16.1 in constructing ``DataFrame`` from nested dictionary (:issue:`11084`)
 
 .. _whatsnew_0170.bug_fixes:
 

pandas/core/frame.py

@@ -52,6 +52,8 @@
 
 from pandas.tseries.period import PeriodIndex
 from pandas.tseries.index import DatetimeIndex
+from pandas.tseries.tdi import TimedeltaIndex
+
 
 import pandas.core.algorithms as algos
 import pandas.core.base as base
@@ -5400,8 +5402,13 @@ def _homogenize(data, index, dtype=None):
                 v = v.reindex(index, copy=False)
         else:
             if isinstance(v, dict):
-                v = _dict_compat(v)
-                oindex = index.astype('O')
+                if oindex is None:
+                    oindex = index.astype('O')
+
+                if isinstance(index, (DatetimeIndex, TimedeltaIndex)):
+                    v = _dict_compat(v)
+                else:
+                    v = dict(v)
                 v = lib.fast_multiget(v, oindex.values, default=NA)
             v = _sanitize_array(v, index, dtype=dtype, copy=False,
                                 raise_cast_failure=False)

pandas/tests/test_frame.py

@@ -34,7 +34,7 @@
 from pandas import (DataFrame, Index, Series, Panel, notnull, isnull,
                     MultiIndex, DatetimeIndex, Timestamp, date_range,
                     read_csv, timedelta_range, Timedelta, CategoricalIndex,
-                    option_context)
+                    option_context, period_range)
 from pandas.core.dtypes import DatetimeTZDtype
 import pandas as pd
 from pandas.parser import CParserError
@@ -3061,6 +3061,27 @@ def create_data(constructor):
         assert_frame_equal(result_timedelta, expected)
         assert_frame_equal(result_Timedelta, expected)
 
+    def test_nested_dict_frame_constructor(self):
+        rng = period_range('1/1/2000', periods=5)
+        df = DataFrame(randn(10, 5), columns=rng)
+
+        data = {}
+        for col in df.columns:
+            for row in df.index:
+                data.setdefault(col, {})[row] = df.get_value(row, col)
+
+        result = DataFrame(data, columns=rng)
+        tm.assert_frame_equal(result, df)
+
+        data = {}
+        for col in df.columns:
+            for row in df.index:
+                data.setdefault(row, {})[col] = df.get_value(row, col)
+
+        result = DataFrame(data, index=rng).T
+        tm.assert_frame_equal(result, df)
+
+
     def _check_basic_constructor(self, empty):
         "mat: 2d matrix with shpae (3, 2) to input. empty - makes sized objects"
         mat = empty((2, 3), dtype=float)

pandas/tseries/tests/test_period.py

@@ -2075,26 +2075,6 @@ def test_period_set_index_reindex(self):
         df = df.set_index(idx2)
         self.assertTrue(df.index.equals(idx2))
 
-    def test_nested_dict_frame_constructor(self):
-        rng = period_range('1/1/2000', periods=5)
-        df = DataFrame(randn(10, 5), columns=rng)
-
-        data = {}
-        for col in df.columns:
-            for row in df.index:
-                data.setdefault(col, {})[row] = df.get_value(row, col)
-
-        result = DataFrame(data, columns=rng)
-        tm.assert_frame_equal(result, df)
-
-        data = {}
-        for col in df.columns:
-            for row in df.index:
-                data.setdefault(row, {})[col] = df.get_value(row, col)
-
-        result = DataFrame(data, index=rng).T
-        tm.assert_frame_equal(result, df)
-
     def test_frame_to_time_stamp(self):
         K = 5
         index = PeriodIndex(freq='A', start='1/1/2001', end='12/1/2009')