Converting None values with pandas.to_datetime is unpredictable
Why does ``pandas`` convert ``None`` values in the different ways for ``to_datetime`` (unpredictable) and ``to_numeric`` (predictable)?

```python
import pandas as pd
  
VALUE = None
    
print(pd.to_datetime(VALUE))
print(pd.to_numeric(VALUE))

print(pd.__version__)
```

returns

```
None
nan
0.23.4
```

due to https://github.com/pandas-dev/pandas/blob/v0.23.4/pandas/core/tools/datetimes.py#L382

Why not ``pd.to_datetime(None) is pd.NaT`` by design?

See also [original post at stackoverflow](https://stackoverflow.com/questions/52720322/converting-none-values-with-pandas-to-datetime-is-unpredictable).