Series: inconsistent behavior of setting value with timestamp dtype for existed index and newly-added

[ianzhy]

sample = pd.Series([1,2],index=['a','b'])
ts = pd.Timestamp('2019-01-01')
sample['a'] = ts
sample['c'] = ts
print(sample)

output:

a    2019-01-01 00:00:00
b                      2
c    1546300800000000000
dtype: object

Problem description

With existed index a, the dtype will be Timestamp, as expected. Howerver, when setting a new index like c, the dtype will be int.
Is this a bug?

Output of pd.show_versions()

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

commit: None
python: 3.6.7.final.0
python-bits: 64
OS: Darwin
OS-release: 18.2.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: zh_CN.UTF-8
LOCALE: zh_CN.UTF-8

pandas: 0.23.4
pytest: 4.0.2
pip: 18.1
setuptools: 40.6.3
Cython: 0.29.2
numpy: 1.15.4
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 7.2.0
sphinx: 1.8.2
patsy: 0.5.1
dateutil: 2.7.5
pytz: 2018.7
blosc: None
bottleneck: 1.2.1
tables: 3.4.4
numexpr: 2.6.8
feather: None
matplotlib: 3.0.2
openpyxl: 2.5.12
xlrd: 1.2.0
xlwt: 1.2.0
xlsxwriter: 1.1.2
lxml: 4.2.5
bs4: 4.6.3
html5lib: 1.0.1
sqlalchemy: 1.2.15
pymysql: 0.9.3
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: 0.7.0

[jreback]

try on 0.24.2 - irrc this is fixed

[WillAyd]

Looks like it's an issue on master. Investigation and PRs would certainly be welcome

[ianzhy]

try on 0.24.2 - irrc this is fixed

@jreback Just tried on 0.24.2, and it's not fixed.
By the way, what does irrc mean?

[jreback]

pls try on master then

[robbuckley]

this is fixed on master, and on releases from 0.25.0.
Output:

a    2019-01-01 00:00:00
b                      2
c    2019-01-01 00:00:00
dtype: object

so this can be closed @jreback @WillAyd

[robbuckley]

i'll take a look at adding a test for this @mroeschke