Hi there -- Is there a fast way to make a numpy ndarray from column data?
For example, suppose I want to make an ndarray with 2 rows and 3 columns of different data types based on the following column data: C0 = [1,2] C1 = ['a','b'] C2 = [3.3,4.4] I could create an empty ndarray and fill the columns one by one: X = numpy.core.ndarray((2,), dtype='<i4,|S1,<f8') X['f0'] = C0 X['f1'] = C1 X['f2'] = C2 The result is the same as: X = numpy.array([(1,'a',3.3), (2,'b',4.4)], dtype='<i4,|S1,<f8') but I would like to make X directly from the column data. [ I know that numpy.core.records.fromarrays will produce a numpy recarray from column data, but this of course is a recarray and not a ndarray! For ex: X = numpy.numpy.core.records.fromarrays([C0,C1,C2]) ] Thanks for any help, Elaine
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