Interpolating of datetime64 values ignored (at best)

[jbrockmendel]

tz naive case:

index = pd.Index([23, 26, 30])
dti = pd.DatetimeIndex(['2015-09-23', '2015-09-26', '2015-09-30'])
ser = pd.Series(dti, index=index).reindex(range(23, 31))
df = pd.DataFrame(ser)

>>> ser    # for reference
23   2015-09-23
24          NaT
25          NaT
26   2015-09-26
27          NaT
28          NaT
29          NaT
30   2015-09-30
dtype: datetime64[ns]

>>> ser.interpolate()
23   2015-09-23
24          NaT
25          NaT
26   2015-09-26
27          NaT
28          NaT
29          NaT
30   2015-09-30
dtype: datetime64[ns]

>>> df.interpolate()
            0
23 2015-09-23
24        NaT
25        NaT
26 2015-09-26
27        NaT
28        NaT
29        NaT
30 2015-09-30

tz-aware case

index = pd.Index([23, 26, 30])
dti = pd.DatetimeIndex(['2015-09-23', '2015-09-26', '2015-09-30'], tz='US/Central')
ser = pd.Series(dti, index=index).reindex(range(23, 31))
df = pd.DataFrame(ser)

>>> ser
23   2015-09-23 00:00:00-05:00
24                         NaT
25                         NaT
26   2015-09-26 00:00:00-05:00
27                         NaT
28                         NaT
29                         NaT
30   2015-09-30 00:00:00-05:00
dtype: datetime64[ns, US/Central]

>>> ser.interpolate()
23   2015-09-23 00:00:00-05:00
24                         NaT
25                         NaT
26   2015-09-26 00:00:00-05:00
27                         NaT
28                         NaT
29                         NaT
30   2015-09-30 00:00:00-05:00
dtype: datetime64[ns, US/Central]

>>> df.interpolate()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib/python2.7/site-packages/pandas/core/generic.py", line 4738, in interpolate
    'object') == len(_maybe_transposed_self.T):
  File "/usr/local/lib/python2.7/site-packages/pandas/core/frame.py", line 1909, in transpose
    return super(DataFrame, self).transpose(1, 0, **kwargs)
  File "/usr/local/lib/python2.7/site-packages/pandas/core/generic.py", line 599, in transpose
    new_values = self.values.transpose(axes_numbers)
  File "/usr/local/lib/python2.7/site-packages/pandas/core/base.py", line 696, in transpose
    nv.validate_transpose(args, kwargs)
  File "/usr/local/lib/python2.7/site-packages/pandas/compat/numpy/function.py", line 54, in __call__
    self.defaults)
  File "/usr/local/lib/python2.7/site-packages/pandas/util/_validators.py", line 218, in validate_args_and_kwargs
    validate_kwargs(fname, kwargs, compat_args)
  File "/usr/local/lib/python2.7/site-packages/pandas/util/_validators.py", line 157, in validate_kwargs
    _check_for_default_values(fname, kwds, compat_args)
  File "/usr/local/lib/python2.7/site-packages/pandas/util/_validators.py", line 69, in _check_for_default_values
    format(fname=fname, arg=key)))
ValueError: the 'axes' parameter is not supported in the pandas implementation of transpose()

The ValueError for the DataFrame case is in issue #19198.

[jreback]

we have tons of interpolation issues, pls find the duplicate and close this one

[jbrockmendel]

Dup of #11701