 # Create a Numpy array filled with all

We can use the Numpy.ones () method to accomplish this task. This method takes three parameters, which are discussed below —

`  shape:  integer or sequence of integers  order:  C_contiguous or F_contiguous C-contiguous order in memory (last index varies the fastest) C order means that operating row-rise on the array will be slightly quicker FORTRAN-contiguous order in memory (first index varies the fastest). F order means that column-wise operations will be faster.  dtype:  [optional, float (byDeafult)] Data type of returned array. `

Code # 1:

 ` # Python program to create an array with all ` ` import ` ` numpy as geek `   ` a ` ` = ` ` geek.ones (` ` 3 ` `, dtype ` ` = ` ` int ` `) ` ` print ` ` ( "Matrix a:" , a) ````   b = geek.ones ([ 3 , 3 ], dtype = int )  print ( "Matrix b:" , b)  ```

Exit:

` Matrix a: [1 1 1] Matrix b: [[1 1 1] [1 1 1] [1 1 1]] `

Code # 2:

 ` # Python program to create an array with all ` ` import ` ` numpy as geek `   ` c ` ` = ` ` geek.ones ([` ` 5 ` `, ` ` 3 ` `])  ```` prin t ( "Matrix c:" , c)    d = geek.ones ([ 5 , 2 ], dtype = float )  print ( "Matrix d:" , d)  ```

Exit:

` Matrix c: [[1. 1. 1.] [1. 1. 1.] [1 . 1. 1.] [1. 1. 1.] [1. 1. 1.]] Matrix d: [[1. 1.] [1. 1.] [1. 1.] [1. 1. ] [1. 1.]] `