BUG: pd.date_range with DST-crossing has incorrect freq attribute
- [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.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

#### Code Sample, a copy-pastable example

```python
import pandas as pd
i = pd.date_range('2020-03-28', periods=4, freq='D', tz='Europe/Berlin')
i # DatetimeIndex(['2020-03-28 00:00:00+01:00',  '2020-03-29 00:00:00+01:00', '2020-03-30 00:00:00+02:00', '2020-03-31 00:00:00+02:00'], dtype='datetime64[ns, Europe/Berlin]', freq='D')
i[0] + i.freq == i[1] #True
i[2] + i.freq == i[3] #True
i[1] + i.freq == i[2] #False (!)
```

#### Problem description

Variably-spaced timestamps are not handled well, if the variation is caused by DST. The result of `i[1] + i.freq` is 
`Timestamp('2020-03-30 01:00:00+0200', tz='Europe/Berlin', freq='D')`, whereas 
`Timestamp('2020-03-30 00:00:00+0200', tz='Europe/Berlin', freq='D')` was expected.

This is in contrast to timestamps where the variation is caused by e.g. months being different lengths, which *are* handled correctly.

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.8.3.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
machine          : AMD64
processor        : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : en
LOCALE           : de_DE.cp1252

pandas           : 1.0.5
numpy            : 1.18.5
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.1.1
setuptools       : 49.2.0.post20200714
Cython           : None
pytest           : 5.4.3
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : 1.0.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.16.1
pandas_datareader: None
bs4              : 4.9.1
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.2.2
numexpr          : None
odfpy            : None
openpyxl         : 3.0.4
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 5.4.3
pyxlsb           : None
s3fs             : None
scipy            : 1.5.0
sqlalchemy       : 1.3.18
tables           : None
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : None
xlsxwriter       : None
numba            : None

</details>
