Adopt microsecond as default datetime precision

[genedan]

Pandas 3.0 has changed the default datetime precision to microsecond, when I believe it was nanosecond previously:

https://pandas.pydata.org/docs/dev/whatsnew/v3.0.0.html#datetime-timedelta-resolution-inference

There are some places in the package where we specify nanosecond, which I assume was to conform to the previous pandas default precision:

chainladder-python/chainladder/core/base.py

Lines 535 to 543 in 6ea3577

	def valuation(self):
	ddims = self.ddims
	if self.is_val_tri:
	out = pd.DataFrame(np.repeat(self.ddims.values[None], len(self.odims), 0))
	return pd.DatetimeIndex(out.unstack().values)
	ddim_arr = ddims - ddims[0]
	origin = np.minimum(self.odims, np.datetime64(self.valuation_date))
	val_array = origin.astype("datetime64[M]") + np.timedelta64(ddims[0], "M")
	val_array = val_array.astype("datetime64[ns]") - np.timedelta64(1, "ns")

However this leads to a breaking change whenever we compare these datetimes to those generated from the default pandas conversions, which happens in the valuation == valuation_date comparison discovered by Henry, due to a nanosecond-to-microsecond comparison.

I propose that we adopt microsecond as the default datetime, to stay consistent with pandas.