BUG: TimedeltaIndex raising ValueError when slice indexing (#16637) (#16638)

Author: jdeschenes

doc/source/whatsnew/v0.20.3.txt

@@ -41,6 +41,8 @@ Bug Fixes
 - Fixed a pytest marker failing downstream packages' tests suites (:issue:`16680`)
 - Fixed compat with loading a ``DataFrame`` with a ``PeriodIndex``, from a ``format='fixed'`` HDFStore, in Python 3, that was written in Python 2 (:issue:`16781`)
 - Fixed a bug in failing to compute rolling computations of a column-MultiIndexed ``DataFrame`` (:issue:`16789`, :issue:`16825`)
+- Bug in a DataFrame/Series with a ``TimedeltaIndex`` when slice indexing (:issue:`16637`)
+
 
 Conversion
 ^^^^^^^^^^

pandas/core/dtypes/common.py

@@ -396,7 +396,10 @@ def is_timedelta64_dtype(arr_or_dtype):
 
     if arr_or_dtype is None:
         return False
-    tipo = _get_dtype_type(arr_or_dtype)
+    try:
+        tipo = _get_dtype_type(arr_or_dtype)
+    except ValueError:
+        return False
     return issubclass(tipo, np.timedelta64)
 
 

pandas/core/indexes/timedeltas.py

@@ -680,8 +680,7 @@ def get_loc(self, key, method=None, tolerance=None):
         -------
         loc : int
         """
-
-        if is_bool_indexer(key):
+        if is_bool_indexer(key) or is_timedelta64_dtype(key):
             raise TypeError
 
         if isnull(key):

pandas/tests/dtypes/test_common.py

@@ -200,10 +200,12 @@ def test_is_datetime64tz_dtype():
 def test_is_timedelta64_dtype():
     assert not com.is_timedelta64_dtype(object)
     assert not com.is_timedelta64_dtype([1, 2, 3])
-
+    assert not com.is_timedelta64_dtype(np.array([], dtype=np.datetime64))
     assert com.is_timedelta64_dtype(np.timedelta64)
     assert com.is_timedelta64_dtype(pd.Series([], dtype="timedelta64[ns]"))
 
+    assert not com.is_timedelta64_dtype("0 days 00:00:00")
+
 
 def test_is_period_dtype():
     assert not com.is_period_dtype(object)

pandas/tests/indexing/test_timedelta.py

@@ -1,3 +1,5 @@
+import pytest
+
 import pandas as pd
 from pandas.util import testing as tm
 
@@ -16,5 +18,25 @@ def test_boolean_indexing(self):
             result = df.assign(x=df.mask(cond, 10).astype('int64'))
             expected = pd.DataFrame(data,
                                     index=pd.to_timedelta(range(10), unit='s'),
-                                    columns=['x'])
+                                    columns=['x'],
+                                    dtype='int64')
             tm.assert_frame_equal(expected, result)
+
+    @pytest.mark.parametrize(
+        "indexer, expected",
+        [(0, [20, 1, 2, 3, 4, 5, 6, 7, 8, 9]),
+         (slice(4, 8), [0, 1, 2, 3, 20, 20, 20, 20, 8, 9]),
+         ([3, 5], [0, 1, 2, 20, 4, 20, 6, 7, 8, 9])])
+    def test_list_like_indexing(self, indexer, expected):
+        # GH 16637
+        df = pd.DataFrame({'x': range(10)}, dtype="int64")
+        df.index = pd.to_timedelta(range(10), unit='s')
+
+        df.loc[df.index[indexer], 'x'] = 20
+
+        expected = pd.DataFrame(expected,
+                                index=pd.to_timedelta(range(10), unit='s'),
+                                columns=['x'],
+                                dtype="int64")
+
+        tm.assert_frame_equal(expected, df)