New submission from m.meliani: The few following lines, i believe, show how the numpy.ndarray.T or numpy.ndarray.transpose() don't change the structure of the data only the way they're displayed. Which is sometimes a problem when handling big quantities of data which you need to look at a certain way for sorting problems among others.
>>> import numpy as np >>> x=np.array([[0,1,2],[1,2,3]]) >>> x=x.T >>> print x [[0 1] [1 2] [2 3]] >>> y=np.array([[0,1],[1,2],[2,3]]) >>> print y [[0 1] [1 2] [2 3]] >>> y.view('i8,i8') array([[(0, 1)], [(1, 2)], [(2, 3)]], dtype=[('f0', '<i8'), ('f1', '<i8')]) >>> x.view('i8,i8') Traceback (most recent call last): File "<stdin>", line 1, in <module> ValueError: new type not compatible with array. ---------- messages: 291967 nosy: m.meliani priority: normal severity: normal status: open title: numpy.ndarray.T doesn't change the structure type: behavior versions: Python 2.7 _______________________________________ Python tracker <rep...@bugs.python.org> <http://bugs.python.org/issue30116> _______________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com