ENH: change default min_count value for pandas.core.resample.Resampler.sum()
#### Is your feature request related to a problem?

When using, pandas.core.resample.Resampler.sum(), the behavior I would expect based on using other resampler aggregation methods (e.g. mean, median,) is that if there is a gap in the time series values should be filled with NaNs, instead they are filled with 0's because the min_count parameter default is 0, I think it should be 1. 

Furthermore,this could also be applied to the min() and max() Resampler aggregation methods. On a related note there seems to be an error in the documentation for the min() and max() methods. The source code shows the default value for the min_count parameter on min() and max() is 0, but the documentation says default is -1 (see: https://pandas.pydata.org/docs/reference/api/pandas.core.resample.Resampler.min.html )

#### Describe the solution you'd like

Change the default value for the min_count parameter to 1 for pandas.core.resample.Resampler.sum(), pandas.core.resample.Resampler.min() and pandas.core.resample.Resampler.max()

#### API breaking implications

Not sure if this would break things :/

#### Describe alternatives you've considered

An alternative would be to add a min_count parameter to other Resampler methods for consistency (e.g. mean, median, etc.)
