REGR: 1.3.0rc behavior change with concatenating boolean and numeric columns

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Code Sample, a copy-pastable example

df1 = pd.DataFrame(pd.Series([True, False, True, True], dtype='bool'))
df2 = pd.DataFrame(pd.Series([1,0,1], dtype='int64'))

new_df = pd.concat([df1,df2]) # dtype changed from int64 to object
assert new_df[0].dtype == 'object'

Problem description

Previously, the concat call would produce a series with dtype int64, converting the bools to 1s and 0s. Now, all the values are maintained, so the dtype is object.

Expected Output

I’m not sure if this behavior change is expected or not, but I didn’t see anything in the release notes that made me think it was expected, so I’d expect the result to allow assert new_df[0].dtype == 'int64'

Output of pd.show_versions()

INSTALLED VERSIONS

commit : 2dd9e9ba9009a40191c0c0b96262fa3939d609f0 python : 3.8.2.final.0 python-bits : 64 OS : Darwin OS-release : 19.6.0 Version : Darwin Kernel Version 19.6.0: Sun Jul 5 00:43:10 PDT 2020; root:xnu-6153.141.1~9/RELEASE_X86_64 machine : x86_64 processor : i386 byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : en_US.UTF-8

pandas : 1.3.0rc1 numpy : 1.20.3 pytz : 2021.1 dateutil : 2.8.1 pip : 21.1.2 setuptools : 41.2.0 Cython : None pytest : 6.0.1 hypothesis : None sphinx : 3.2.1 blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : None jinja2 : 2.11.3 IPython : 7.18.1 pandas_datareader: None bs4 : None bottleneck : None fsspec : 2021.06.0 fastparquet : 0.5.0 gcsfs : None matplotlib : 3.2.2 numexpr : None odfpy : None openpyxl : None pandas_gbq : None pyarrow : 4.0.1 pyxlsb : None s3fs : None scipy : 1.6.3 sqlalchemy : None tables : None tabulate : None xarray : None xlrd : None xlwt : None numba : 0.53.1

[jreback]

the result is correct; you should be doing an .astype(int) on the bools

[jbrockmendel]

we also need #42576 to get the analogous ArrayManager behavior fixed