pd.to_datetime does not work.
#### Code Sample, a copy-pastable example if possible

```python
data = pd.read_csv("Data_export.csv")
data.drop_duplicates(keep='first',inplace=True) # dropping duplicate rows
df_out = data.pivot(index='timeutc', columns='attributename', values='value') # produce correct columns with values
df_out = df_out.dropna()

print("BEFORE")
print(df_out.index)

df_out.index = pd.to_datetime(df_out.index)

print("AFTER")
print(df_out.index)

```
#### Problem description

I am importing a .csv file taken from the local meteorological data service.
The file contains data such as "humidity", "temperature", etc. together with a "dateutc" containing the timestamp of the data sample.

Pandas does not recognise the format immediately, so I explicitly call ```to_datetime```, but it does not seem to work.

Output of my file:
```
BEFORE
Index(['2018-06-06 15:10:00+02', '2018-06-06 15:20:00+02',
       '2018-06-06 15:30:00+02', '2018-06-06 16:20:00+02',
       '2018-06-06 16:30:00+02', '2018-06-06 17:10:00+02',
       '2018-06-06 17:20:00+02', '2018-06-06 17:30:00+02',
       '2018-06-06 17:40:00+02', '2018-06-06 17:50:00+02',
       ...
       '2019-07-21 05:50:00+02', '2019-07-21 06:00:00+02',
       '2019-07-21 06:10:00+02', '2019-07-21 06:20:00+02',
       '2019-07-21 06:30:00+02', '2019-07-21 06:40:00+02',
       '2019-07-21 06:50:00+02', '2019-07-21 07:00:00+02',
       '2019-07-21 07:10:00+02', '2019-07-21 07:20:00+02'],
      dtype='object', name='timeutc', length=52029)
```

This is type Object, as expected. But even after calling ```to_datetime``` it still remains Object:

```
AFTER
Index([2018-06-06 15:10:00+02:00, 2018-06-06 15:20:00+02:00,
       2018-06-06 15:30:00+02:00, 2018-06-06 16:20:00+02:00,
       2018-06-06 16:30:00+02:00, 2018-06-06 17:10:00+02:00,
       2018-06-06 17:20:00+02:00, 2018-06-06 17:30:00+02:00,
       2018-06-06 17:40:00+02:00, 2018-06-06 17:50:00+02:00,
       ...
       2019-07-21 05:50:00+02:00, 2019-07-21 06:00:00+02:00,
       2019-07-21 06:10:00+02:00, 2019-07-21 06:20:00+02:00,
       2019-07-21 06:30:00+02:00, 2019-07-21 06:40:00+02:00,
       2019-07-21 06:50:00+02:00, 2019-07-21 07:00:00+02:00,
       2019-07-21 07:10:00+02:00, 2019-07-21 07:20:00+02:00],
      dtype='object', name='timeutc', length=52029)
```

Calling ```print(type(data.index))``` gives
```
<class 'pandas.core.indexes.base.Index'>
```

#### Expected Output

I expected to have a DateTime index.
My code was working as intended before upgrading the Anaconda Interface. Somehow, without me realising it, upgrading the Anaconda Interface also upgraded Pandas to 1.0.1, and my code broke down in several places. I tried downgrading but I do not remember exactly which version of Pandas I was using before, when the code was working, but the above behaviour happens both with 1.0.1 and with 0.25.3.

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.6.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
machine          : AMD64
processor        : Intel64 Family 6 Model 142 Stepping 10, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.None

pandas           : 0.25.3
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 46.0.0.post20200309
Cython           : 0.29.15
pytest           : 5.3.5
hypothesis       : 5.5.4
sphinx           : 2.4.0
blosc            : None
feather          : None
xlsxwriter       : 1.2.7
lxml.etree       : 4.5.0
html5lib         : 1.0.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.1
IPython          : 7.13.0
pandas_datareader: None
bs4              : 4.8.2
bottleneck       : 1.3.2
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.5.0
matplotlib       : 3.1.3
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.3
pandas_gbq       : None
pyarrow          : None
pytables         : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.3.13
tables           : 3.6.1
xarray           : None
xlrd             : 1.2.0
xlwt             : 1.3.0
xlsxwriter       : 1.2.7

</details>
