Modify index of Series derived from Dataframe affects index of it's column.
```python
import pandas as pd
from datetime import datetime
import pytz

dt_from = datetime(2019, 3, 30, 0, tzinfo=pytz.utc)
dt_to = datetime(2019, 3, 30, 4, tzinfo=pytz.utc)
idx = pd.date_range(dt_from, dt_to, freq='H')

df = pd.DataFrame(data={
    'a': {i: v for i, v in zip(idx, range(idx.size))}, 
    'b': {i: v+10 for i, v in zip(idx, range(idx.size))}}
)

>>> df
                           a   b
2019-03-30 00:00:00+00:00  0  10
2019-03-30 01:00:00+00:00  1  11
2019-03-30 02:00:00+00:00  2  12
2019-03-30 03:00:00+00:00  3  13
2019-03-30 04:00:00+00:00  4  14

s = df['a']  # df.loc[:, 'a'] instead of df['a'] works the same
s.index = s.index.tz_convert('Europe/Prague')

>>> s

2019-03-30 01:00:00+01:00     0
2019-03-30 02:00:00+01:00     1
2019-03-30 03:00:00+01:00     2
2019-03-30 04:00:00+01:00     3
2019-03-30 05:00:00+01:00     4
Name: a, dtype: int64

# good

>>> df

                           a   b
2019-03-30 00:00:00+00:00  0  10
2019-03-30 01:00:00+00:00  1  11
2019-03-30 02:00:00+00:00  2  12
2019-03-30 03:00:00+00:00  3  13
2019-03-30 04:00:00+00:00  4  14

# good

>>> df['a']

2019-03-30 01:00:00+01:00    0
2019-03-30 02:00:00+01:00    1
2019-03-30 03:00:00+01:00    2
2019-03-30 04:00:00+01:00    3
2019-03-30 05:00:00+01:00    4
Name: a, dtype: int64

# BAD INDEX

>>> df['b']

2019-03-30 00:00:00+00:00    10
2019-03-30 01:00:00+00:00    11
2019-03-30 02:00:00+00:00    12
2019-03-30 03:00:00+00:00    13
2019-03-30 04:00:00+00:00    14
Name: b, dtype: int64

# good
```

#### Workaround

```python
s = df['a'].copy()
```

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.15.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: 0.24.2
pytest: None
pip: 19.0.3
setuptools: 40.8.0
Cython: 0.29.5
numpy: 1.14.6
scipy: 1.2.1
pyarrow: None
xarray: None
IPython: 5.8.0
sphinx: None
patsy: None
dateutil: 2.8.0
pytz: 2018.9
blosc: None
bottleneck: 1.2.1
tables: 3.4.4
numexpr: 2.6.8
feather: None
matplotlib: 2.2.3
openpyxl: 2.6.0
xlrd: 1.2.0
xlwt: None
xlsxwriter: 1.1.5
lxml.etree: 4.3.1
bs4: 4.7.1
html5lib: None
sqlalchemy: 1.2.17
pymysql: None
psycopg2: 2.7.7 (dt dec pq3 ext lo64)
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: 0.7.0
gcsfs: None
</details>