Numpy python R eqivalent indexing

Numpy python R eqivalent indexing

It first flattens the row of each matrix

import numpy as np

o = np.array([

              [
              [1,2,3,4],
              [5,6,7,8]
              ],

              [
              [9,10,11,12],
              [13,14,15,16]
              ]

             ])
print(o.flatten())

# array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16])

It first flattens the row of each matrix

But I want that it flattens the coluumn of each matrix first so that it prints [1,5,2,6,3,7,4,8,9,13,10,14,11,15,12,16]

I tried searching and what I found was passing "F" as an argument but that gives [1,5,9,13,2,6,10,14,3,7,11,15,4,8,12,16] that is it switches to another matrix without completing first.

In short, I would like to find python equivalent of R's indexing with double brackets

someData <- rep(0, 2*3*4);

ar <- array(someData, c(2, 3, 4));
ar[1,1,1] = 1 ar[1,2,1] = 2 ar[1,3,1] = 3

ar[2,1,1] = 4 ar[2,2,1] = 5 ar[2,3,1] = 6

ar[1,1,2] = 7 ar[1,2,2] = 8 ar[1,3,2] = 9 print(ar[[1]]) # 1 print(ar[[2]]) # 4 print(ar[[3]]) # 2 print(ar[[4]]) # 5 print(ar[[5]]) # 3 print(ar[[6]]) # 6


python numpy data-science r

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