Creation in NumPy

For using numpy, import the numpy library.

import numpy

Create an Array of Zeros

To create a numpy array containing zeros, write: np.zeros(size)

To create an array of size 9 write: np.zeros(9)

Here is how this array is stored in memory:

   ┌───┬───┬───┬───┬───┬───┬───┬───┬───┐
 Z │ 0 │ 0 │ 0 │ 0 │ 0 │ 0 │ 0 │ 0 │ 0 │
   └───┴───┴───┴───┴───┴───┴───┴───┴───┘

Create an Array of Ones

To create a numpy array containing ones, write: np.ones(size).

To create an array of size 9 write: np.ones(9)

Here is how this array is stored in memory:

    ┌───┬───┬───┬───┬───┬───┬───┬───┬───┐
  Z │ 1 │ 1 │ 1 │ 1 │ 1 │ 1 │ 1 │ 1 │ 1 │
    └───┴───┴───┴───┴───┴───┴───┴───┴───┘

Create an Array of 0’s and 1’s

To create an array of zeros and ones, use np.array([1,0,0,0,0,0,1,0]):

Here is how the array is stored in memory:

   ┌───┬───┬───┬───┬───┬───┬───┬───┬───┐
Z  │ 1 │ 0 │ 0 │ 0 │ 0 │ 0 │ 0 │ 1 │ 0 │
   └───┴───┴───┴───┴───┴───┴───┴───┴───┘

Create an Array of 2’s

To create an array of 2’s write: 2*np.ones(size).

To create an array of 2’s of size 9 write: 2*np.ones(9).

Here is how the array is stored in memory:

   ┌───┬───┬───┬───┬───┬───┬───┬───┬───┐
Z  │ 2 │ 2 │ 2 │ 2 │ 2 │ 2 │ 2 │ 2 │ 2 │
   └───┴───┴───┴───┴───┴───┴───┴───┴───┘

Create a NumPy Array of any Length

To create an array of any length write: np.arange(size).

To create an array of size 9 write : np.arange(9).

Here is how the array is stored in memory:

   ┌───┬───┬───┬───┬───┬───┬───┬───┬───┐
 Z │ 0 │ 1 │ 2 │ 3 │ 4 │ 5 │ 6 │ 7 │ 8 │
   └───┴───┴───┴───┴───┴───┴───┴───┴───┘

Reshape a NumPy Array into a Column Vector

To reshape a numpy array,write: np.arange(size).reshape(size,1).

To reshape a numpy array into 9 rows and 1 column ,write: np.arange(9).reshape(9,1).

Here is how the array is stored is stored in memory:

   ┌───┐
   │ 0 │
   ├───┤
   │ 1 │
   ├───┤
   │ 2 │
   ├───┤
   │ 3 │
   ├───┤
 Z │ 4 │
   ├───┤
   │ 5 │
   ├───┤
   │ 6 │
   ├───┤
   │ 7 │
   ├───┤
   │ 8 │
   └───┘

Generate Array of Random Numbers and in Grid Format

To generate an array of random size, write: np.random.randint(0,size,(x_dimension,y_dimension)).

To generate an array of random numbers from 0 to 9 and x dimension 3 and y dimension 3, write: np.random.randint(0,9,(3,3)).

Here is how the array is stored in memory:

   ┌───┬───┬───┐
   │ 4 │ 5 │ 7 │
   ├───┼───┼───┤
 Z │ 0 │ 2 │ 6 │
   ├───┼───┼───┤
   │ 8 │ 4 │ 0 │
   └───┴───┴───┘

Create a Linspace

To create evenly spaced numbers over a specified interval write : np.linspace(start, stop, size)

To create a linspace of range 0-1 and size 5 , write : Z = np.linspace(0, 1, 5).

Here is how it is stored in memory:

   ┌──────┬──────┬──────┬──────┬──────┐
Z  │ 0.00 │ 0.25 │ 0.50 │ 0.75 │ 1.00 │
   └──────┴──────┴──────┴──────┴──────┘

Create a Mesh Grid

To create a dense multi-dimensional “meshgrid”. ,write: np.mgrid[0:x_dimension,0:y_dimenion]

To create a grid in numpy of size(3*3),write: np.mgrid[0:3,0:3]

Here is how a mesh grid is stored in memory:

    ┌───┬───┬───┐   ┌───┬───┬───┐
    │ 0 │ 0 │ 0 │   │ 0 │ 1 │ 2 │
    ├───┼───┼───┤   ├───┼───┼───┤
 Z  │ 1 │ 1 │ 1 │   │ 0 │ 1 │ 2 │
    ├───┼───┼───┤   ├───┼───┼───┤
    │ 2 │ 2 │ 2 │   │ 0 │ 1 │ 2 │
    └───┴───┴───┘   └───┴───┴───┘

Now that we have learned to create a NumPy, let’s move on to the next lesson “Reshaping in NumPy”.