read_json with typ="series" of json list of bools results in timestamps/Exception

[stewit]

Code Sample, a copy-pastable example if possible

import pandas as pd
pd.read_json('[true, true, false]', typ="series")

results in the following Pandas Series object in older Pandas versions:

0   1970-01-01 00:00:01
1   1970-01-01 00:00:01
2   1970-01-01 00:00:00
dtype: datetime64[ns]

Since 1.0.0 it raises TypeError: <class 'bool'> is not convertible to datetime

Problem description

The expected output would be a Pandas Series of bools. Note that

• with typ="frame" it works and the result is a dataframe with one column with bool values
• with convert_dates set to False correctly outputs a Series of boolean values

This is a problem because

• users would expect a Series of bools (and neither an exception nor a series of timestamps)
• it is inconsistent with the "frame" case

Expected Output

Output of pd.show_versions()

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

INSTALLED VERSIONS

commit : None
python : 3.8.1.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.13-arch1-1
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : de_DE.UTF-8
LOCALE : de_DE.UTF-8

pandas : 1.0.0
numpy : 1.18.1
pytz : 2019.3
dateutil : 2.8.1
pip : 20.0.2
setuptools : 44.0.0
Cython : 0.29.14
pytest : 5.2.4
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.4.2
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.10.3
IPython : 7.11.1
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : 4.4.2
matplotlib : 3.1.2
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pytest : 5.2.4
pyxlsb : None
s3fs : None
scipy : 1.3.2
sqlalchemy : 1.3.11
tables : None
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : None
xlsxwriter : None
numba : None

[jessefarnham]

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