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):