Sum of all NA and empty should be 0

And the prod of those should be 1.

xref: https://github.com/pandas-dev/pandas/issues/9422, https://github.com/pandas-dev/pandas/pull/17630, https://mail.python.org/pipermail/pandas-dev/2017-November/000657.html

We need to implement that and design and implement the alternative (either a new method, or a keyword-argument to sum and prod).

[TomAugspurger]

Another (large) place this affects is upsampling:

In [1]: import pandas as pd

In [2]: pd.__version__
Out[2]: '0.20.3'

In [3]: pd.Series(range(4), index=pd.date_range(start='2017', periods=4, freq='1H')).resample('30T').sum()
Out[3]:
2017-01-01 00:00:00    0.0
2017-01-01 00:30:00    NaN
2017-01-01 01:00:00    1.0
2017-01-01 01:30:00    NaN
2017-01-01 02:00:00    2.0
2017-01-01 02:30:00    NaN
2017-01-01 03:00:00    3.0
Freq: 30T, dtype: float64

On my branch:

In [1]: import pandas as pd

In [2]: pd.__version__
Out[2]: '0.22.0.dev0+364.g70e9bf903.dirty'

In [3]: pd.Series(range(4), index=pd.date_range(start='2017', periods=4, freq='1H')).resample('30T').sum()
Out[3]:
2017-01-01 00:00:00    0
2017-01-01 00:30:00    0
2017-01-01 01:00:00    1
2017-01-01 01:30:00    0
2017-01-01 02:00:00    2
2017-01-01 02:30:00    0
2017-01-01 03:00:00    3
Freq: 30T, dtype: int64

which is I suspect what we want, but another thing I’ll make sure to document.

[jorisvandenbossche]

I would keep the more general discussion on the mailing list, and here more the details of the changes we then want to make