ENH: show percentiles in timestamp describe (#30164)
closes https://github.com/pandas-dev/pandas/issues/30164

When creating a pandas Series of timestamps and calling `describe` on it, it will not show the percentiles of the data, even if these are specified as arguments (`s.describe(percentiles = [0.25, 0.5, 0.75])`).

This PR solves the issue by introducing a new describe logic for timestamps that would:
* Add the percentiles in the same way as for numeric.
* Rename `first` and `last` to `min` and `max` in order to match numeric types.
* Add the mean of the series.
* ~~Show datetime columns alongside numerics by default in the describe method for DataFrames.~~ (just realized there were other issues in which this was deemed to be the desirable behavior)

After this, it more or less matches the functionality of R's `summary` on `POSIXct` and `Date` types.

Why I think this is a good idea: I oftentimes find myself trying to inspect tables of mixed types, and want to get a quick overview of which kind of ranges and variations are there in each column, including timestamps. Currently this is very inconvenient in pandas, and they are not displayed alongside numeric columns by default and don't match the names if passing `include = "all"`, which is what I want to see when I call `DataFrame.describe`.

Examples:
```python
import numpy as np, pandas as pd
dt_list = [
    "2019-01-01 00:01:00",
    "2019-01-01 00:02:00",
    "2019-01-01 00:02:10",
    "2019-01-01 00:10:01",
    "2019-01-01 00:11:00"
]
s = pd.to_datetime(pd.Series(dt_list))
s.describe()
```
```python
pd.DataFrame({
    "col1" : s,
    "col2" : np.arange(s.shape[0])
}).describe(include = "all")
```

Update: corrected the coding style to comply with `black` and pass the automatic test.