fix perf

Author: jreback

pandas/_libs/src/inference.pyx

@@ -442,7 +442,7 @@ def infer_dtype(object value):
 cpdef object infer_datetimelike_array(object arr):
     """
     infer if we have a datetime or timedelta array
-    - date: we have *only* date and myabe strings, nulls
+    - date: we have *only* date and maybe strings, nulls
     - datetime: we have *only* datetimes and maybe strings, nulls
     - timedelta: we have *only* timedeltas and maybe strings, nulls
     - nat: we do not have *any* date, datetimes or timedeltas, but do have
@@ -476,7 +476,7 @@ cpdef object infer_datetimelike_array(object arr):
 
         elif util._checknull(v):
             # nan or None
-            seen_null = 1
+            pass
         elif v is NaT:
             seen_nat = 1
         elif is_datetime(v) or util.is_datetime64_object(v):
@@ -516,7 +516,6 @@ cpdef object infer_datetimelike_array(object arr):
     return 'mixed'
 
 
-
 cdef inline bint is_null_datetimelike(v):
     # determine if we have a null for a timedelta/datetime (or integer
     # versions)

pandas/tests/frame/test_misc_api.py

@@ -330,12 +330,12 @@ def test_empty_nonzero(self):
 
     def test_with_datetimelikes(self):
 
-        df = DataFrame({'A': date_range('20130101', periods=2),
-                        'B': timedelta_range('1 day', periods=2)})
+        df = DataFrame({'A': date_range('20130101', periods=10),
+                        'B': timedelta_range('1 day', periods=10)})
         t = df.T
 
         result = t.get_dtype_counts()
-        expected = Series({'object': 2})
+        expected = Series({'object': 10})
         tm.assert_series_equal(result, expected)
 
     def test_inplace_return_self(self):

pandas/types/cast.py

@@ -774,6 +774,10 @@ def maybe_infer_to_datetimelike(value, convert_dates=False):
     if not v.ndim == 1:
         v = v.ravel()
 
+    # we only care about object dtypes
+    if not is_object_dtype(v):
+        return value
+
     if len(v):
 
         def _try_datetime(v):