BUG: select_dtypes(include="int") has different behaviour on windows and linux
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version (1.1.2) of pandas.

---

#### Problem description

Using `DataFrame.select_dtypes(include='int')` on a DataFrame that contains an integer column returns an empty dataframe in windows, yet selects the correct columns in linux (Ubuntu 20.04).

`DataFrame.select_dtypes(include='integer')` works as expected in both environments.

In both cases the dtype of the column is 'int64'.

#### Code Sample, a copy-pastable example

```python
df = pd.DataFrame(columns=["Ints"], data=[1,2,3])
df.select_dtypes(include="int")
```

####  Output
on ubuntu (tested 16.04, 18.04, 20.04, python 3.6, 3.7, 3.8)
```
   Ints
0     1
1     2
2     3
```

on windows 10 (python 3.6, 3.7. 3.8)
```
Empty DataFrame
Columns: []
Index: [0, 1, 2]
```

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

<details>

INSTALLED VERSIONS
------------------
commit           : 2a7d3326dee660824a8433ffd01065f8ac37f7d6
python           : 3.8.6.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.19041
machine          : AMD64
processor        : Intel64 Family 6 Model 126 Stepping 5, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : English_Europe.1252

pandas           : 1.1.2
numpy            : 1.19.2
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.2.1
setuptools       : 49.2.1
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          : 7.18.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>

<details>

INSTALLED VERSIONS
------------------
commit           : 2a7d3326dee660824a8433ffd01065f8ac37f7d6
python           : 3.7.8.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.19.104-microsoft-standard
Version          : #1 SMP Wed Feb 19 06:37:35 UTC 2020
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : C.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.1.2
numpy            : 1.19.1
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.1.1
setuptools       : 47.1.0
Cython           : None
pytest           : 5.4.3
hypothesis       : 5.20.3
sphinx           : 3.1.2
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.16.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.0
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : 1.5.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
