Differences in python array reshape scenarios

Question

What is the difference between the following:

import numpy as np

x = np.array([[1, 2], [3, 4], [5, 6]])

z = x.reshape(6)

print(z)

As opposed to:

import numpy as np

x = np.array([[1, 2], [3, 4], [5, 6]])

z = x.reshape(1,6)

print(z)

You get slightly different outputs. What exactly is the difference?

Answer 1

Reshape means you are shaping element in number of rows and column

in, x.reshape(6)
Will give you a Single Dimension Array

[ 1 2 3 4 5 6 ]

But x.reshape(1,6)
Will give a double dimension array of 6 column and 1 row.

[[1 2 3 4 5 6]]

Answer 2

Thanks for the response. How is the second case considered a 2d dimension?