On 6/20/19 5:39 PM, Markos wrote: > Hi, > > I'm studying Numpy and I don't understand the difference between > >>>> vector_1 = np.array( [ 1,0,1 ] ) > > with 1 bracket and > >>>> vector_2 = np.array( [ [ 1,0,1 ] ] ) > > with 2 brackets
the first is one-dimensional, the second two-dimensional. If we expand how we write the second a bit does it make it more clear? np.array([ [1, 0, 1], # no other elements ]) the double brackets look magical, but as soon as you have more than one row it makes sense. > > The shape of vector_1 is: > >>>> vector_1.shape > (3,) > > But the shape of vector_2 is: > >>>> vector_2.shape > (1, 3) > > The transpose on vector_1 don't work: > >>>> vector_1.T > array([1, 0, 1]) > > But the transpose method in vector_2 works fine: > >>>> vector_2.T > array([[1], > [0], > [1]]) > > > I thought that both vectors would be treated as an matrix of 1 row and 3 > columns. > > Why this difference? > > Any tip? > > Thank you, > Markos > _______________________________________________ > Tutor maillist - Tutor@python.org > To unsubscribe or change subscription options: > https://mail.python.org/mailman/listinfo/tutor _______________________________________________ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor