pd.to_datetime() fails for KeyError when raising monotonic increasing index ValueError
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
import numpy as np
from datetime import datetime

times = pd.date_range(datetime.now(), periods=1000, freq='h')
times = times.to_frame(index=False, name='DT').sample(1000)
times.index = times.index.to_series().astype(float)/1000

pd.to_datetime(times.iloc[:, 0]) # <-- Fails

pd.to_datetime(times.reset_index(drop=True).iloc[:, 0]) # <-- Reset index to sorted int works

```
#### Problem description
Sometimes during data processing after pivoting or sampling data you may end up with a float index that is not sorted. When you try to convert a series which happens to have an unsorted float index to a DateTime, a ValueError followed by KeyError occurs. Also, this only happens for a series with 60 elements or more. There may be differences in code path for larger frames.

```python
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
D:\Python37\lib\site-packages\pandas\core\indexes\base.py in get_slice_bound(self, label, side, kind)
   5159             try:
-> 5160                 return self._searchsorted_monotonic(label, side)
   5161             except ValueError:

D:\Python37\lib\site-packages\pandas\core\indexes\base.py in _searchsorted_monotonic(self, label, side)
   5120 
-> 5121         raise ValueError("index must be monotonic increasing or decreasing")
   5122 

ValueError: index must be monotonic increasing or decreasing

During handling of the above exception, another exception occurred:

KeyError                                  Traceback (most recent call last)
<ipython-input-67-ffc7a0542f03> in <module>
----> 1 pd.to_datetime(times.iloc[:, 0])

D:\Python37\lib\site-packages\pandas\util\_decorators.py in wrapper(*args, **kwargs)
    206                 else:
    207                     kwargs[new_arg_name] = new_arg_value
--> 208             return func(*args, **kwargs)
    209 
    210         return wrapper

D:\Python37\lib\site-packages\pandas\core\tools\datetimes.py in to_datetime(arg, errors, dayfirst, yearfirst, utc, box, format, exact, unit, infer_datetime_format, origin, cache)
    769                 result = result.tz_localize(tz)
    770     elif isinstance(arg, ABCSeries):
--> 771         cache_array = _maybe_cache(arg, format, cache, convert_listlike)
    772         if not cache_array.empty:
    773             result = arg.map(cache_array)

D:\Python37\lib\site-packages\pandas\core\tools\datetimes.py in _maybe_cache(arg, format, cache, convert_listlike)
    149     if cache:
    150         # Perform a quicker unique check
--> 151         if not should_cache(arg):
    152             return cache_array
    153 

D:\Python37\lib\site-packages\pandas\core\tools\datetimes.py in should_cache(arg, unique_share, check_count)
    119     assert 0 < unique_share < 1, "unique_share must be in next bounds: (0; 1)"
    120 
--> 121     unique_elements = unique(arg[:check_count])
    122     if len(unique_elements) > check_count * unique_share:
    123         do_caching = False

D:\Python37\lib\site-packages\pandas\core\series.py in __getitem__(self, key)
   1104             key = check_bool_indexer(self.index, key)
   1105 
-> 1106         return self._get_with(key)
   1107 
   1108     def _get_with(self, key):

D:\Python37\lib\site-packages\pandas\core\series.py in _get_with(self, key)
   1109         # other: fancy integer or otherwise
   1110         if isinstance(key, slice):
-> 1111             indexer = self.index._convert_slice_indexer(key, kind="getitem")
   1112             return self._get_values(indexer)
   1113         elif isinstance(key, ABCDataFrame):

D:\Python37\lib\site-packages\pandas\core\indexes\numeric.py in _convert_slice_indexer(self, key, kind)
    395 
    396         # translate to locations
--> 397         return self.slice_indexer(key.start, key.stop, key.step, kind=kind)
    398 
    399     def _format_native_types(

D:\Python37\lib\site-packages\pandas\core\indexes\base.py in slice_indexer(self, start, end, step, kind)
   5025         slice(1, 3)
   5026         """
-> 5027         start_slice, end_slice = self.slice_locs(start, end, step=step, kind=kind)
   5028 
   5029         # return a slice

D:\Python37\lib\site-packages\pandas\core\indexes\base.py in slice_locs(self, start, end, step, kind)
   5245         end_slice = None
   5246         if end is not None:
-> 5247             end_slice = self.get_slice_bound(end, "right", kind)
   5248         if end_slice is None:
   5249             end_slice = len(self)

D:\Python37\lib\site-packages\pandas\core\indexes\base.py in get_slice_bound(self, label, side, kind)
   5161             except ValueError:
   5162                 # raise the original KeyError
-> 5163                 raise err
   5164 
   5165         if isinstance(slc, np.ndarray):

D:\Python37\lib\site-packages\pandas\core\indexes\base.py in get_slice_bound(self, label, side, kind)
   5155         # we need to look up the label
   5156         try:
-> 5157             slc = self.get_loc(label)
   5158         except KeyError as err:
   5159             try:

D:\Python37\lib\site-packages\pandas\core\indexes\numeric.py in get_loc(self, key, method, tolerance)
    477         except (TypeError, NotImplementedError):
    478             pass
--> 479         return super().get_loc(key, method=method, tolerance=tolerance)
    480 
    481     @cache_readonly

D:\Python37\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
   2890                 return self._engine.get_loc(key)
   2891             except KeyError:
-> 2892                 return self._engine.get_loc(self._maybe_cast_indexer(key))
   2893         indexer = self.get_indexer([key], method=method, tolerance=tolerance)
   2894         if indexer.ndim > 1 or indexer.size > 1:

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.Float64HashTable.get_item()

pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.Float64HashTable.get_item()

KeyError: 100.0
```

#### Expected Output
Ideally it could create the DateTime series regardless of the state of the index. Perhaps users want to keep an unsorted float index and just want to cast to DateTime.


#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.1.final.0
python-bits      : 64
OS               : Windows
OS-release       : 2008ServerR2
machine          : AMD64
processor        : Intel64 Family 6 Model 45 Stepping 7, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.None

pandas           : 0.25.0
numpy            : 1.17.0
pytz             : 2019.2
dateutil         : 2.8.0
pip              : 19.2.2
setuptools       : 41.1.0
Cython           : 0.29.13
pytest           : 5.0.1
hypothesis       : None
sphinx           : 2.1.2
blosc            : 1.8.1
feather          : None
xlsxwriter       : None
lxml.etree       : 4.4.1
html5lib         : 1.0.1
pymysql          : None
psycopg2         : None
jinja2           : 2.10.1
IPython          : 7.7.0
pandas_datareader: None
bs4              : 4.8.0
bottleneck       : 1.2.1
fastparquet      : 0.3.2
gcsfs            : None
lxml.etree       : 4.4.1
matplotlib       : 3.1.1
numexpr          : 2.7.0
odfpy            : None
openpyxl         : 2.6.2
pandas_gbq       : None
pyarrow          : 0.14.0
pytables         : None
s3fs             : None
scipy            : 1.3.1
sqlalchemy       : 1.3.6
tables           : 3.5.2
xarray           : 0.12.3
xlrd             : 1.2.0
xlwt             : 1.3.0
xlsxwriter       : None

</details>
