multi-dimensional-indexing deprecation warning has inconsistent stack level.
#### Code Sample, a copy-pastable example if possible

```python
# Your code here
import warnings
import pandas as pd

warnings.simplefilter("always")


x = pd.Series([], dtype="float64")

df = pd.DataFrame(
    {
        "year": [2018, 2018, 2018],
        "month": [1, 1, 1],
        "day": [1, 2, 3],
        "value": [1, 2, 3],
    }
)
df["date"] = pd.to_datetime(df[["year", "month", "day"]])
monthly = df[["date", "value"]].groupby(["date"]).sum()
dates = monthly.index

dates[:, None]
x.index[:, None]

```
#### Problem description

Running the above script gives:

```
sharon@22:14  ➤  python /tmp/pd_test.py 
/tmp/pd_test.py:21: DeprecationWarning: Support for multi-dimensional indexing (e.g. `index[:, None]`) on an Index is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.
  dates[:, None]
/home/tcaswell/.virtualenvs/sys37/lib/python3.7/site-packages/pandas/core/indexes/range.py:708: DeprecationWarning: Support for multi-dimensional indexing (e.g. `index[:, None]`) on an Index is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.
  return super().__getitem__(key)


```

I think the issue is that https://github.com/pandas-dev/pandas/blob/7d616b951c08bbd90e36bee2c184569556d57093/pandas/core/indexers.py#L263-L270 is pushing the warning up a fixed number of stack layers, but due to implementation details it maybe deeper / less deep than expected.

#### Expected Output

pandas should be the module reported in the warning about slicing in both cases or neither case.  You may want to use something like https://github.com/matplotlib/matplotlib/blob/e4dbf4e7b5241e7d74f79adc854f84a954b45e8f/lib/matplotlib/cbook/__init__.py#L2013-L2032 to find the first stack not in pandas to put the warning at.

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.4.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.0.0-38-generic
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.0rc0
numpy            : 1.16.5
pytz             : 2019.2
dateutil         : 2.8.0
pip              : 19.2.2
setuptools       : 41.0.1
Cython           : 0.29.13
pytest           : 3.10.1
hypothesis       : None
sphinx           : 2.2.0
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.10.3
IPython          : 7.12.0.dev
pandas_datareader: None
bs4              : 4.8.2
bottleneck       : 1.2.1
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.2.0rc2.post1219+g3d8a6cb83
numexpr          : 2.7.0
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 3.10.1
s3fs             : None
scipy            : 1.3.1
sqlalchemy       : None
tables           : 3.6.1
tabulate         : None
xarray           : 0.14.0
xlrd             : 1.2.0
xlwt             : None
xlsxwriter       : None
numba            : None

</details>
