convert_dtypes fails with int and str

[pjadzinsky]

Code Sample, a copy-pastable example if possible

Thanks for an amazing package and maintaining it

# Your code here
s = pd.Series(["h", "i", 1])
s.convert_dtypes()

Problem description

Example raises an error, when it shouldn't. I think the case is missing from the tests

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Expected Output

series with object dtype ?

Output of pd.show_versions()

[paste the output of pd.show_versions() here below this line]
In [6]: pd.show_versions()

INSTALLED VERSIONS

commit : None
python : 3.7.6.final.0
python-bits : 64
OS : Darwin
OS-release : 19.2.0
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.0.1
numpy : 1.18.1
pytz : 2019.3
dateutil : 2.8.1
pip : 20.0.2
setuptools : 45.2.0
Cython : None
pytest : 5.3.5
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.1
IPython : 7.12.0
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 : 0.16.0
pytables : None
pytest : 5.3.5
pyxlsb : None
s3fs : 0.4.0
scipy : 1.4.1
sqlalchemy : 1.3.13
tables : None
tabulate : 0.8.6
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None
numba : None

[pjadzinsky]

As far as I can tell

pandas/pandas/core/dtypes/cast.py

Line 1054 in ac3056f

inferred_dtype = lib.infer_dtype(input_array)

returns 'mixed-integer' which according to the definition in

pandas/pandas/_libs/lib.pyx

Line 1250 in ac3056f

>>> infer_dtype(['a', 1])

is correct. However this

pandas/pandas/core/dtypes/cast.py

Line 1065 in ac3056f

if isinstance(inferred_dtype, str) and (

executes to True and
(

pandas/pandas/core/dtypes/cast.py

Line 1069 in ac3056f

inferred_dtype = target_int_dtype

)

sets the 'inferred_dtype' to "Int64" which I think is wrong

Hope this helps

[jorisvandenbossche]

Yes, for this case taking "mixed-integer" as integer is indeed wrong:

pandas/pandas/core/dtypes/cast.py

Lines 1065 to 1068 in ac3056f

	if isinstance(inferred_dtype, str) and (
	inferred_dtype == "mixed-integer"
	or inferred_dtype == "mixed-integer-float"
	):

@Dr-Irv do you remember for which use case mixed-integer is needed?
As for mix of integers and floats (which could still be all integer-like) it gives "mixed-integer-float"

[jorisvandenbossche]

And thanks for the report, @pjadzinsky !

[Dr-Irv]

@Dr-Irv do you remember for which use case mixed-integer is needed?
As for mix of integers and floats (which could still be all integer-like) it gives "mixed-integer-float"

I think this is just my mistake in understanding the meaning of "mixed-integer" when I wrote convert_dtypes(). I will take a look at this