Series.to_timestamp(freq=None, how='start', copy=True)

Series.ftypes return if the data is sparse|dense

Series.valid(inplace=False, **kwargs)

Series.rank(axis=0, method='average', numeric_only=None, na_option='keep', ascending=True, pct=False)

Series.str.rjust(width, fillchar=' ')

Series.str.translate(table, deletechars=None)

Series.drop(labels, axis=0, level=None, inplace=False, errors='raise')

Series.diff(periods=1)

Series.str.findall(pat, flags=0, **kwargs)

Series.cummin(axis=None, skipna=True, *args, **kwargs)