though NaT means an NA on *time*, while an NaN means an NA on a numerical value. So that’s interesting in that Python gives you a little more information regarding your column data types, which is kind of interesting.
and I do not know that there are libraries in Python that compare with rugarch, PortfolioAnalytics, and Quantstrat, though if anyone wants to share the go-to generally-accepted Python libraries to use beyond the usual numpy/pandas/matplotlib/cvxpy/sklearn (AKA the usual data science stack). ...