create_arrays.py

import numpy as np
### Create your array by directly loading in the data. You can use a list or a tuple. 
### If you want to be super thorough, specify the array type
np_array = np.array([[ 0,  1,  2,  3,  4],
                     [ 5,  6,  7,  8,  9],
                     [10, 11, 12, 13, 14]])
np_array = np.array([(1.5,2,3), (4,5,6)], dtype=float)

### Sometimes, the contents of the initial array may not be known, but we would like 
### to initialise one anyways to use it later. We have a number of functions at out 
### disposal here.

# Creates a 3x4 array of 0's
np.zeros((3,4))

# Creates a 2x3x4 array of int 1's
np.ones((2,3,4), dtype=np.int16) 

# Creates an empty 2x3 array
np.empty((2,3))

### You can also create arrays with certain patterns like so

# Creating a 1D array of numbers from 10 to 30 in increments of 5
np.arange( 10, 30, 5 )

# Creating a 1D array of numbers from 0 to 2 in increments of 0.3
np.arange( 0, 2, 0.3 ) 

# Creating a 1D array of 9 numbers equally spaced from 0 to 2 
np.linspace( 0, 2, 9 )