infer_dtype not reporting mixed with decimal/floating

[jmkuhn]

Code Sample, a copy-pastable example if possible

import pandas as pd
from decimal import Decimal
print(pd.api.types.infer_dtype([1.0, Decimal(1)]))
print(pd.api.types.infer_dtype([Decimal(1), 2.0]))

Problem description

I expect both infer_dtypes to return 'mixed'. The second returns 'decimal'.

Output of pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 3.6.4.final.0
python-bits: 64
OS: Darwin
OS-release: 17.4.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.22.0
pytest: 3.3.2
pip: 9.0.1
setuptools: 38.4.0
Cython: None
numpy: 1.14.0
scipy: None
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: None
patsy: None
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.1.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: None
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

[TomAugspurger]

This is in cython, at

pandas/pandas/_libs/src/inference.pyx

Line 242 in 238499a

def infer_dtype(object value, bint skipna=False):

so it'll be a bit tricky but hopefully not too bad with some print statements if anyone wants to dig into it.

[jmkuhn]

I think the problem is with

pandas/pandas/_libs/src/inference.pyx

Lines 443 to 448 in 238499a

	elif is_decimal(val):
	return 'decimal'
	elif util.is_float_object(val):
	if is_float_array(values):
	return 'floating'

I think there should be a call to is_decimal_array(...). There isn't an is_decimal_array function and I don't know how to write one.

[ademhilmibozkurt]

I tried it.

print(pd.api.types.infer_dtype([1.0, Decimal(1)]))
print(pd.api.types.infer_dtype([Decimal(1), 2.0]))

>>>OpenSource/Issues/infer_dtype#19449.py
mixed
mixed

There is no issue in python 3.11.0

[jmkuhn]

Fixed in pandas 1.2.0 with #37176