BUG: DataFrame size overflows on Windows
- [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
import numpy as np

a = np.ones(2**30 + 1, dtype=np.int8)
df = pd.DataFrame.from_dict({'a': a, 'b': a})
print(df.size)  # --> -2147483646
print(df.sum(axis=0))  # --> 
# a   NaN
# b   NaN
# dtype: float64
```

#### Problem description

On windows, dataframes with more than 2^31 elements (max 32 bit int) result in negative sizes and nan results from operations performed on them. 

This problem only seems to exist on windows (64-bit Windows-10-10.0.18362-SP0). This seems to be from the assumption that `np.prod(self.shape)` will not overflow, but numpy [makes no such guarantee](https://numpy.org/doc/stable/reference/generated/numpy.prod.html). 

#### Expected Output

positive size, non-nan sum

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.1.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
machine          : AMD64
processor        : Intel64 Family 6 Model 85 Stepping 7, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.None

pandas           : 1.0.1
numpy            : 1.16.4
pytz             : 2018.9
dateutil         : 2.8.0
pip              : 19.2.2
setuptools       : 41.0.1
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          : 7.8.0
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
pytest           : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None
</details>