BUG: need better inference for path in Series construction

[jreback]

This hits a path in Series.__init__ which I think needs some better inference

https://github.com/pydata/pandas/blob/master/pandas/core/series.py#L178

In [1]: d = {numpy.datetime64('2015-01-07T02:00:00.000000000+0200'): 42544017.198965244,
   ...:      numpy.datetime64('2015-01-08T02:00:00.000000000+0200'): 40512335.181958228,
   ...:      numpy.datetime64('2015-01-09T02:00:00.000000000+0200'): 39712952.781494237,
   ...:      numpy.datetime64('2015-01-12T02:00:00.000000000+0200'): 39002721.453793451}

In [2]: Series(d)
Out[2]: 
2015-01-07   NaN
2015-01-08   NaN
2015-01-09   NaN
2015-01-12   NaN
dtype: float64

In [3]: Series(d.values(),d.keys())
Out[3]: 
2015-01-07    42544017.198965
2015-01-08    40512335.181958
2015-01-09    39712952.781494
2015-01-12    39002721.453793
dtype: float64

The problem is the index is already converted at this point and its not easy to get the keys/values out (except to do so explicity which is better IMHO).

Need a review of what currently hits this path (can simply put a halt in here and see what tests hit this). Then figure out a better method.

[patrickfournier]

I am working on this issue (not at the sprint, unfortunately).

[patrickfournier]

I put some traces in the elif isinstance(data, dict): block and ran the tests in pandas.tests.test_series.

• The if isinstance(index, DatetimeIndex) block catches those tests:

  • test_from_csv
  • test_name_printing
  • test_to_dict

  However, all three throw a TypeError exception because index.astype('O') is an Index, not an nparray.

• The elif isinstance(index, PeriodIndex) block catches the second Series() of the test_constructor_dict

• The else block catches everything else. Three tests throw a TypeError exception because data is not a dict but a dict subclass:

  • test_constructor_subclass_dict
  • test_orderedDict_ctor
  • test_orderedDict_subclass_ctor

I suggest to rewrite the try block like this:

    if isinstance(index, DatetimeIndex) and lib.infer_dtype(data) != 'datetime64':
        data = lib.fast_multiget(data, index.astype('O').values, default=np.nan)
    elif isinstance(index, PeriodIndex):
        data = [data.get(i, nan) for i in index]
    else:
        data = lib.fast_multiget(data, index.values, default=np.nan)

If this is not complete nonsense, I can add a test and create a pull request.