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BugCompatpandas objects compatability with Numpy or Python functionspandas objects compatability with Numpy or Python functionsNumeric OperationsArithmetic, Comparison, and Logical operationsArithmetic, Comparison, and Logical operations
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#29057 xfails some tests that are broken with numpy 1.18, which changes the behavior of np.minimum.accumulate on dt64/td64 arrays:
s = pd.Series(
pd.to_datetime(["NaT", "2000-1-2", "NaT", "2000-1-1", "NaT", "2000-1-3"])
)
>>> np.minimum.accumulate(s.values) # numpy 1.17
array([ 'NaT', '2000-01-02T00:00:00.000000000',
'2000-01-02T00:00:00.000000000', '2000-01-01T00:00:00.000000000',
'2000-01-01T00:00:00.000000000', '2000-01-01T00:00:00.000000000'],
dtype='datetime64[ns]')
>>> np.accumulate.minimum(s.values) # numpy 1.18
array(['NaT', 'NaT', 'NaT', 'NaT', 'NaT', 'NaT'], dtype='datetime64[ns]')
This will need to be addressed in core.generic._make_cum_function (maybe other places too, not sure)
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BugCompatpandas objects compatability with Numpy or Python functionspandas objects compatability with Numpy or Python functionsNumeric OperationsArithmetic, Comparison, and Logical operationsArithmetic, Comparison, and Logical operations