> dta = pd.DatetimeIndex(np.array(['1820-01-01', '2020-01-02'], 'datetime64[s]'))

> dta[0].strftime("%y")  # Instance operation raises ValueError
Traceback (most recent call last):
  (...)
  File "timestamps.pyx", line 1518, in pandas._libs.tslibs.timestamps.Timestamp.strftime
ValueError: format %y requires year >= 1900 on Windows

> dta.strftime("%y")  # Array operation catches error and turns into str representation (with default datetime format)
Index(['1820-01-01 00:00:00', '20'], dtype='object')

> dta = pd.DatetimeIndex(np.array(['-0020-01-01', '2020-01-02'], 'datetime64[s]'))

> dta.strftime("%Y_%m_%d")  # Custom so falls back on Timestamp.strftime
NotImplementedError: strftime not yet supported on Timestamps which are outside the range of Python's standard library. For now, please call the components you need (such as `.year` and `.month`) and construct your string from there.

> dta[0].strftime("%Y_%m_%d")
NotImplementedError: strftime not yet supported on Timestamps which are outside the range of Python's standard library. For now, please call the components you need (such as `.year` and `.month`) and construct your string from there.

> dta = pd.DatetimeIndex(np.array(['1820-01-01', '2020-01-02'], **'datetime64[s]'))**
> dta[0].strftime("%y")
ValueError: format %y requires year >= 1900 on Windows
> dta.strftime("%y")
ValueError: format %y requires year >= 1900 on Windows
> dta.strftime("%y", errors='raise')
ValueError: format %y requires year >= 1900 on Windows
> dta.strftime("%y", errors='ignore')
Index([None, '20'], dtype='object')
> dta.strftime("%y", errors='warn')
StrftimeErrorWarning : Not all timestamps could be converted to string: ['1820-01-01']. Set errors=‘raise’ to see the details
Index([None, '20'], dtype='object')