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DEPR: __array__ for tz-aware Series/Index
This deprecates the current behvior when converting tz-aware Series or Index to an ndarray. Previously, we converted to M8[ns], throwing away the timezone information. In the future, we will return an object-dtype array filled with Timestamps, each of which has the correct tz. ```python In [1]: import pandas as pd; import numpy as np In [2]: ser = pd.Series(pd.date_range('2000', periods=2, tz="CET")) In [3]: np.asarray(ser) /bin/ipython:1: FutureWarning: Converting timezone-aware DatetimeArray to timezone-naive ndarray with 'datetime64[ns]' dtype. In the future, this will return an ndarray with 'object' dtype where each element is a 'pandas.Timestamp' with the correct 'tz'. To accept the future behavior, pass 'dtype=object'. To keep the old behavior, pass 'dtype="datetime64[ns]"'. #!/Users/taugspurger/Envs/pandas-dev/bin/python3 Out[3]: array(['1999-12-31T23:00:00.000000000', '2000-01-01T23:00:00.000000000'], dtype='datetime64[ns]') ``` xref pandas-dev#23569
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