BUG:ValueError: Invalid frequency with date
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

---

#### Code Sample
```python
import pandas as pd

df = pd.read_hdf('metr-la.h5')
print(df)
```
metr-la.h5
https://drive.google.com/open?id=10FOTa6HXPqX8Pf5WRoRwcFnW9BrNZEIX
It's index is DataTime type, data is float64 type.

#### Output

```python
Traceback (most recent call last):
  File "C:\Test.py", line 5, in <module>
    print(pandas_df)
  File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\frame.py", line 751, in __repr__
    show_dimensions=show_dimensions,
  File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\frame.py", line 881, in to_string
    line_width=line_width,
  File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\io\formats\format.py", line 630, in __init__
    self._chk_truncate()
  File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\io\formats\format.py", line 716, in _chk_truncate
    frame = concat((frame.iloc[:row_num, :], frame.iloc[-row_num:, :]))
  File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\reshape\concat.py", line 284, in concat
    sort=sort,
  File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\reshape\concat.py", line 454, in __init__
    self.new_axes = self._get_new_axes()
  File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\reshape\concat.py", line 521, in _get_new_axes
    for i in range(ndim)
  File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\reshape\concat.py", line 521, in <listcomp>
    for i in range(ndim)
  File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\reshape\concat.py", line 574, in _get_concat_axis
    concat_axis = _concat_indexes(indexes)
  File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\reshape\concat.py", line 592, in _concat_indexes
    return indexes[0].append(indexes[1:])
  File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\indexes\base.py", line 4153, in append
    return self._concat(to_concat, name)
  File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\indexes\base.py", line 4161, in _concat
    result = _concat.concat_compat(to_concat)
  File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\dtypes\concat.py", line 162, in concat_compat
    return concat_datetime(to_concat, axis=axis, typs=typs)
  File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\dtypes\concat.py", line 392, in concat_datetime
    result = type(to_concat[0])._concat_same_type(to_concat, axis=axis)
  File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\arrays\datetimelike.py", line 695, in _concat_same_type
    if all(pair[0][-1] + obj.freq == pair[1][0] for pair in pairs):
  File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\arrays\datetimelike.py", line 695, in <genexpr>
    if all(pair[0][-1] + obj.freq == pair[1][0] for pair in pairs):
  File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\arrays\datetimelike.py", line 540, in __getitem__
    return self._box_func(result)
  File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\arrays\datetimes.py", line 476, in <lambda>
    return lambda x: Timestamp(x, freq=self.freq, tz=self.tz)
  File "pandas\_libs\tslibs\timestamps.pyx", line 1083, in pandas._libs.tslibs.timestamps.Timestamp.__new__
  File "pandas\_libs\tslibs\offsets.pyx", line 3580, in pandas._libs.tslibs.offsets.to_offset
ValueError: Invalid frequency: b"ccopy_reg\n_reconstructor\np1\n(cpandas.tseries.offsets\nMinute\np2\nc__builtin__\nobject\np3\nNtRp4\n(dp5\nS'normalize'\np6\nI00\nsS'_offset'\np7\ncdatetime\ntimedelta\np8\n(I1\nI0\nI0\ntRp9\nsS'_use_relativedelta'\np10\nI00\nsS'kwds'\np11\n(dp12\nsS'n'\nI5\nsb."
```

#### Problem description

Pandas seems to work incorrect with hdf5 file created by old version pandas.
The file work well with pandas 0.19.2. Now, many method will raise ValueError: Invalid frequency.
 
I am not sure what causes this error, but I found that the DataFrame's index is DatetimeArray  type instead of DatetimeIndex type which may be the reason.


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

<details>

INSTALLED VERSIONS
------------------
commit           : f2ca0a2665b2d169c97de87b8e778dbed86aea07
python           : 3.7.8.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.18362
machine          : AMD64
processor        : Intel64 Family 6 Model 42 Stepping 7, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.None

pandas           : 1.1.1
numpy            : 1.19.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.2.2
setuptools       : 47.1.0
Cython           : None
pytest           : 5.4.1
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.5.0
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.13.0
pandas_datareader: None
bs4              : 4.9.0
bottleneck       : None
fsspec           : 0.7.2
fastparquet      : None
gcsfs            : None
matplotlib       : 3.2.1
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.3
pandas_gbq       : None
pyarrow          : 0.17.0
pytables         : None
pyxlsb           : None
s3fs             : 0.2.2
scipy            : 1.4.1
sqlalchemy       : None
tables           : 3.6.1
tabulate         : 0.8.7
xarray           : 0.15.1
xlrd             : 1.2.0
xlwt             : None
numba            : 0.48.0

</details>
