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Reproducible Example

import pandas as pd 
s = pd.Series(['a','b']) # dtype: object
s.mask([True, True], 1) # dtype: object but expected to be int64

Issue Description

NDFrame._where which is used under the hood of .where and .mask returns sometimes unexpected dtype.

To illustrate, the final Series in the example below is expected to have int64 dtype but it remains a object. 

>>> s = pd.Series(['a','b'])
0    a
1    b
dtype: object

>>> s.mask([True, True], 1)
0    1
1    1
dtype: object

This issue came to our attention during the construction of this PR: https://github.com/pandas-dev/pandas/pull/50343 (comment)

Expected Behavior

It is expected for the resulting object to "refresh" its dtype. In the example above, the dtype shall be int64.

Installed Versions

INSTALLED VERSIONS ------------------ commit : 2e218d10984e9919f0296931d92ea851c6a6faf5 python : 3.10.6.final.0 python-bits : 64 OS : Linux OS-release : 5.19.0-38-generic Version : #39~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Fri Mar 17 21:16:15 UTC 2 machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : en_US.UTF-8 pandas : 1.5.3 numpy : 1.23.5 pytz : 2022.7 dateutil : 2.8.2 setuptools : 65.6.3 pip : 22.3.1 Cython : 0.29.32 pytest : 7.2.0 hypothesis : 6.61.0 ... xlrd : 2.0.1 xlwt : None zstandard : 0.19.0 tzdata : 2022.7

Comment From: rhshadrach

I disagree, I don't think we should be doing inference here. If you instead did s.mask([True, False], 1), then this would need to be object dtype. The dtype of the result should not depend on the values of the mask.

Comment From: phofl

Agreed with @rhshadrach