# Python | Numpy method np.multivariate_normal ()

Using the `np.multivariate_normal() ` method, we can get an array of multivariate normal values ​​using ` np.multivariate_normal () `.

Syntax: ` np.multivariate_normal (mean, matrix, size) `
Return: Return the array of multivariate normal values.

Example # 1:
In this example we can see that using ` np.multivariate_normal () ` we can get an array of multivariate normal values ​​using this method.

 ` # NumPy import ` ` import ` ` numpy as np ` ` `  ` mean ` ` = ` ` [` ` 1 ` `, ` ` 2 ` `] ` ` matrix ` ` = ` ` [[[` ` 5 ` `, ` ` 0 ` `], [` ` 0 ` `, ` ` 5 ` `]] ` ` # using the np.multinomial () method ` ` gfg ` ` = ` ` np.random.multivariate_normal (mean, matrix, ` ` 10 ` `) `   ` print ` ` (gfg) `

Output:

[[6.24847794 6.57894103]
[1.24114594 3.22013831]
[3.0660329 2.1442572]
[0.3239289 2.79949784]
[-1.42964186 1.11846394]
[-0.08521476 0.74518872]
[1.42307847 3.27995017]
[3.08412374 0.45869097]
[2.2158498 2.97014443]
[1.77583875 0.57446964]]

Example # 2:

 ` # NumPy import ` ` import ` ` numpy as np ` ` `  ` mean ` ` = ` ` [` ` 0 ` `, ` ` 0 ` `, ` ` 0 ` `] ` ` matrix ` ` = ` ` [[` ` 1 ` `, ` ` 0 ` `, ` ` 0 ` `], [` ` 0 ` `, ` ` 1 ` `, ` ` 0 ` `], [` ` 0 ` `, ` ` 0 ` `, ` ` 1 ` `]] ` ` # using the np.multinomial () method ` ` gfg ` ` = ` ` np.random.multivariate_normal (mean, matrix, ` ` 5 ` `) `   ` print ` ` (gfg) `

Output:

[[-2.21792571 -1.04526811 -0.4586839]
[0.15760965 0.83934119 -0.52943583]
[-0.9978205 0.79594411 -0.00937]
[-0.16882821 0.1727549 0.14002367]
[-1.34406079 1.03498375 0.17620708]]