BUG: Compare type `int64` with `Int64` fails

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• 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.

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Code Sample, a copy-pastable example

pd.api.types.pandas_dtype("int64") == "Int64"

Problem description

The code above fails (TypeError: data type 'Int64' not understood) while the following cases pass:

pd.api.types.pandas_dtype("int64") == "int64"
pd.api.types.pandas_dtype("Int64") == "Int64"
pd.api.types.pandas_dtype("Int64") == "int64"

Expected Output

False

Output of pd.show_versions()

INSTALLED VERSIONS

commit : c7f7443c1bad8262358114d5e88cd9c8a308e8aa python : 3.7.11.final.0 python-bits : 64 OS : Windows OS-release : 10 Version : 10.0.19041 machine : AMD64 processor : Intel64 Family 6 Model 142 Stepping 10, GenuineIntel byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : None.None

pandas : 1.3.1 numpy : 1.20.3 pytz : 2021.1 dateutil : 2.8.2 pip : 21.2.2 setuptools : 52.0.0.post20210125 Cython : 0.29.24 pytest : 6.1.2 hypothesis : 6.14.1 sphinx : 4.0.2 blosc : None feather : None xlsxwriter : 1.4.4 lxml.etree : 4.6.3 html5lib : 1.1 pymysql : 1.0.2 psycopg2 : None jinja2 : 3.0.1 IPython : 7.22.0 pandas_datareader: None bs4 : 4.9.3 bottleneck : 1.3.2 fsspec : 2021.07.0 fastparquet : None gcsfs : None matplotlib : 3.4.2 numexpr : 2.7.3 odfpy : None openpyxl : 3.0.7 pandas_gbq : None pyarrow : 3.0.0 pyxlsb : None s3fs : 0.4.2 scipy : 1.6.2 sqlalchemy : 1.4.22 tables : 3.6.1 tabulate : 0.8.9 xarray : 0.19.0 xlrd : 2.0.1 xlwt : 1.3.0 numba : 0.53.0

[mzeitlin11]

Can you give me an example for how to add a regression test for this issue? Thank you 😃

I’d recommend looking at closed good first issues about testing (for example from https://github.com/pandas-dev/pandas/issues?q=is%3Aissue+label%3A"good+first+issue"+is%3Aclosed+label%3A"Needs+Tests"). If you look at some pull requests which close the issue, those should be good examples

[simonjayhawkins]

closing as tests added in #44840