Manipulating array shapes

We have already learned about the reshape() function. Another repeating chore is the flattening of arrays. Flattening in this setting entails transforming a multidimensional array into a one-dimensional array. Let us create an array b that we shall use for practicing the further examples:

In: b = np.arange(24).reshape(2,3,4) 
 
In: print(b) 
 
Out: [[[ 0,  1,  2,  3], 
        [ 4,  5,  6,  7], 
        [ 8,  9, 10, 11]], 
 
       [[12, 13, 14, 15], 
        [16, 17, 18, 19], 
        [20, 21, 22, 23]]]) 

We can manipulate array shapes using the following functions:

• Ravel: We can accomplish this with the ravel() function as follows:

          In: b 
          Out: 
          array([[[ 0,  1,  2,  3], 
                  [ 4,  5,  6,  7], 
                  [ 8,  9, 10, 11]], 
                 [[12, 13, 14, 15], 
                  [16, 17, 18, 19], 
                  [20, 21, 22, 23]]]) 
  ...