Issue 1:
xref #6942

xref #12499

xref #14179

Simple repro, casting to object, but a datetimelike is cast to its underlying repr

In [1]: s = pd.Series([1])

In [2]: s
Out[2]:
0 1
dtype: int64

In [3]: s[1] = pd.Timestamp('20130101')

In [4]: s
Out[4]:
0 1
1 1356998400000000000
dtype: object

Code Sample, a copy-pastable example if possible

>>> import pandas as pd
>>> s = pd.Series()
>>> s.loc['date'] = pd.Timestamp.now()
>>> s
date 2017-02-27 15:04:32.357
dtype: datetime64[ns]
>>> s.loc['date2'] = pd.Timestamp.now()
>>> s
date 2017-02-27 15:04:32.357
date2 2017-02-27 15:04:41.724
dtype: datetime64[ns]
>>> s.loc['date3'] = 3
>>> s
date 2017-02-27 15:04:32.357000
date2 2017-02-27 15:04:41.724000
date3 3
dtype: object
>>> s.loc['date4'] = pd.Timestamp.now()
>>> s
date 2017-02-27 15:04:32.357000
date2 2017-02-27 15:04:41.724000
date3 3
date4 1488207907032000000
dtype: object

Problem description

When a series' dtype is object, .loc assignment of pd.Timestamp values results in being cast to a long, rather than remaining a datetime. Since the dtype is object, I would expect objects to be uncasted.

Expected Output

The expected behavior is to not be casted, i.e. to remain a datetime.

>>> s = s.append(pd.Series(data = [pd.Timestamp.now()], index = ['date_x']))
>>> s
date 2017-02-27 15:04:32.357000
date2 2017-02-27 15:04:41.724000
date3 3
date4 1488207907032000000
date_x 2017-02-27 15:11:03.995000
dtype: object

Output of pd.show_versions()

# Paste the output here pd.show_versions() here
27-Feb-17 15:08:27 DEBUG lzma module is not available
27-Feb-17 15:08:27 DEBUG Registered VCS backend: git
27-Feb-17 15:08:28 DEBUG Registered VCS backend: hg
27-Feb-17 15:08:28 DEBUG Config variable 'Py_DEBUG' is unset, Python ABI tag may be incorrect
27-Feb-17 15:08:28 DEBUG Config variable 'WITH_PYMALLOC' is unset, Python ABI tag may be incorrect
27-Feb-17 15:08:28 DEBUG Config variable 'Py_UNICODE_SIZE' is unset, Python ABI tag may be incorrect
27-Feb-17 15:08:28 DEBUG Config variable 'Py_DEBUG' is unset, Python ABI tag may be incorrect
27-Feb-17 15:08:28 DEBUG Config variable 'WITH_PYMALLOC' is unset, Python ABI tag may be incorrect
27-Feb-17 15:08:28 DEBUG Config variable 'Py_UNICODE_SIZE' is unset, Python ABI tag may be incorrect
27-Feb-17 15:08:28 DEBUG Registered VCS backend: svn
27-Feb-17 15:08:28 DEBUG Registered VCS backend: bzr

INSTALLED VERSIONS

commit: None

python: 2.7.12.final.0

python-bits: 64

OS: Windows

OS-release: 10

machine: AMD64

processor: Intel64 Family 6 Model 60 Stepping 3, GenuineIntel

byteorder: little

LC_ALL: None

LANG: None

LOCALE: None.None

pandas: 0.19.2

nose: 1.3.7

pip: 9.0.1

setuptools: 33.1.0.post20170122

Cython: 0.25.2

numpy: 1.10.4

scipy: 0.17.1

statsmodels: 0.8.0

xarray: 0.9.1

IPython: 5.2.2

sphinx: 1.5.2

patsy: 0.4.1

dateutil: 2.6.0

pytz: 2016.10

blosc: None

bottleneck: 1.2.0

tables: 3.3.0

numexpr: 2.6.1

matplotlib: 2.0.0

openpyxl: 2.4.1

xlrd: 1.0.0

xlwt: 1.2.0

xlsxwriter: 0.9.6

lxml: 3.7.2

bs4: 4.5.3

html5lib: 0.999

httplib2: None

apiclient: None

sqlalchemy: 1.1.5

pymysql: None

psycopg2: None

jinja2: 2.8

boto: 2.45.0

pandas_datareader: 0.2.1

Issue 2:
xref #14179

xref #12499

xref #18027

http://stackoverflow.com/questions/23250333/in-pandas-dataframe-after-i-set-an-entire-column-i-cant-update-another-column

but .loc works

In [50]: df = pd.DataFrame(index=pd.date_range(start,periods=1), columns=['timenow','Live'])

In [51]: df.at[start,'timenow'] = datetime.today() # initial value

In [52]: df
Out[52]:
timenow Live
2014-04-01 2014-04-23 12:42:38.883082 NaN

[1 rows x 2 columns]

In [53]: df._data
Out[53]:
BlockManager
Items: Index([u'timenow', u'Live'], dtype='object')
Axis 1: <class 'pandas.tseries.index.DatetimeIndex'>
[2014-04-01]
Length: 1, Freq: D, Timezone: None
ObjectBlock: [timenow, Live], 2 x 1, dtype: object

In [54]: df = pd.DataFrame(index=pd.date_range(start,periods=1), columns=['timenow','Live'])

In [55]: df.loc[start,'timenow'] = datetime.today() # initial value

In [56]: df
Out[56]:
timenow Live
2014-04-01 2014-04-23 12:43:00.554915 NaT

[1 rows x 2 columns]

In [57]: df._data
Out[57]:
BlockManager
Items: Index([u'timenow', u'Live'], dtype='object')
Axis 1: <class 'pandas.tseries.index.DatetimeIndex'>
[2014-04-01]
Length: 1, Freq: D, Timezone: None
DatetimeBlock: [timenow, Live], 2 x 1, dtype: datetime64[ns]