DataFrame.nunique and Series.nunique not consistent when Empty
#### Code Sample, a copy-pastable example if possible

Example A:
```python
>>> import pandas as pd
>>> df = pd.DataFrame({"a": [1, 2], "b": [3, 4], "c": [5, 6]})
>>> assert df.nunique().tolist() == [df[col].nunique() for col in df.columns]
# Both equal [2, 2, 2]
```

Example B:
```python
>>> df = pd.DataFrame(columns=['a', 'b', 'c'])
>>> df.nunique()
# Empty DataFrame
# Columns: [a, b, c]
# Index: []

>>> [df[col].nunique() for col in df.columns]
# [0, 0, 0]
```

#### Problem description

In Example A, when a DataFrame isn't empty, getting nunique is consistent between the DataFrame and Series approaches; however, when a DataFrame is empty (Example B), DataFrame.nunique returns itself, while the Series approach returns 0. 

#### Expected Output

I would expect df.nunique to return 0 for each column, consistent with how a Series behaves. An empty object, by definition, has 0 unique elements in my mind.

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

<details>

[paste the output of ``pd.show_versions()`` here below this line]
INSTALLED VERSIONS
------------------
commit           : None
python           : 3.6.5.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 18.7.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 0.25.0
numpy            : 1.17.0
pytz             : 2019.2
dateutil         : 2.8.0
pip              : 18.1
setuptools       : 41.1.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : 7.7.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None

</details>

Thank you!