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Random Arrays

It is often the case that we need to generate a random number or an array of random numbers. Luckily, NumPy has a module named random specifically for this purpose.

The two most commonly used functions of the random module are:

rand();
randint().

rand()

The numpy.random.rand() function is used to generate either a random float number or an array of random floats from a uniform distribution over [0, 1).

Note

Square brackets [ or ] in interval notation indicate that the value is included, while parentheses ( or ) indicate that the value is excluded. For example, [0, 1) means the interval includes 0 but not 1. Don't confuse this mathematical notation with brackets used in code — they serve different purposes.

Its only possible arguments are the dimensions of the array. If no argument is passed, rand() generates a random float number (scalar).


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import numpy as np
# Generating a random number
random_number = np.random.rand()
print(random_number)
# Generating a random 1D array with 5 elements
random_array = np.random.rand(5)
print(random_array)
# Generating a random 2D array (matrix) of shape 4x3
random_matrix = np.random.rand(4, 3)
print(random_matrix)

Note

Dimensions in the rand() function should be specified as separate integer parameters, not as a tuple of integers. For example, rand(4, 3) is correct, while rand((4, 3)) is incorrect.

randint()

The numpy.random.randint function is used to generate either a random integer or an array of random integers from a discrete uniform distribution within a specified interval.

Its three most important parameters are low (the only required parameter), high, and size. The interval is [low, high) (from low inclusive to high exclusive). However, if high is not specified, then the interval is [0, low).


              12345678910111213
            
import numpy as np
# Generating a random integer from 0 to 3 exclusive
random_integer = np.random.randint(3)
print(random_integer)
# Generating a 1D array of random integers in [0, 5) with 4 elements
random_int_array = np.random.randint(5, size=4)
print(random_int_array)
# Generating a 1D array of random integers in [2, 5) with 4 elements
random_int_array_2 = np.random.randint(2, 5, size=4)
print(random_int_array_2)
# Generating a random 2D array of random integers in [1, 6) of shape 4x2
random_int_matrix = np.random.randint(1, 6, size=(4, 2))
print(random_int_matrix)

Note

Unlike rand(), we specify the dimensions of the array via a single parameter size, passing either an integer or a tuple of integers.

Task

Swipe to start coding

Create a 1D array of random floats from a uniform distribution in [0, 1) with 4 elements for random_floats_array.
Create a 2D array of random floats from a uniform distribution in [0, 1) with a shape of 3x2 for random_floats_matrix.
Use the correct function to create a 2D array of random integers for random_integers_matrix.
Set the interval to [10, 21) (from 10 to 21 exclusive) by specifying the first two arguments of the function.
Set the shape of the random_integers_matrix to 3x2 by specifying the third keyword argument of the function.

Solution

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Section 1. Chapter 7

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Random Arrays

It is often the case that we need to generate a random number or an array of random numbers. Luckily, NumPy has a module named random specifically for this purpose.

The two most commonly used functions of the random module are:

rand();
randint().

rand()

The numpy.random.rand() function is used to generate either a random float number or an array of random floats from a uniform distribution over [0, 1).

Note

Square brackets [ or ] in interval notation indicate that the value is included, while parentheses ( or ) indicate that the value is excluded. For example, [0, 1) means the interval includes 0 but not 1. Don't confuse this mathematical notation with brackets used in code — they serve different purposes.

Its only possible arguments are the dimensions of the array. If no argument is passed, rand() generates a random float number (scalar).


              12345678910
            
import numpy as np
# Generating a random number
random_number = np.random.rand()
print(random_number)
# Generating a random 1D array with 5 elements
random_array = np.random.rand(5)
print(random_array)
# Generating a random 2D array (matrix) of shape 4x3
random_matrix = np.random.rand(4, 3)
print(random_matrix)

Note

Dimensions in the rand() function should be specified as separate integer parameters, not as a tuple of integers. For example, rand(4, 3) is correct, while rand((4, 3)) is incorrect.

randint()

The numpy.random.randint function is used to generate either a random integer or an array of random integers from a discrete uniform distribution within a specified interval.


              12345678910111213
            
import numpy as np
# Generating a random integer from 0 to 3 exclusive
random_integer = np.random.randint(3)
print(random_integer)
# Generating a 1D array of random integers in [0, 5) with 4 elements
random_int_array = np.random.randint(5, size=4)
print(random_int_array)
# Generating a 1D array of random integers in [2, 5) with 4 elements
random_int_array_2 = np.random.randint(2, 5, size=4)
print(random_int_array_2)
# Generating a random 2D array of random integers in [1, 6) of shape 4x2
random_int_matrix = np.random.randint(1, 6, size=(4, 2))
print(random_int_matrix)

Note

Unlike rand(), we specify the dimensions of the array via a single parameter size, passing either an integer or a tuple of integers.

Task

Swipe to start coding

Create a 1D array of random floats from a uniform distribution in [0, 1) with 4 elements for random_floats_array.
Create a 2D array of random floats from a uniform distribution in [0, 1) with a shape of 3x2 for random_floats_matrix.
Use the correct function to create a 2D array of random integers for random_integers_matrix.
Set the interval to [10, 21) (from 10 to 21 exclusive) by specifying the first two arguments of the function.
Set the shape of the random_integers_matrix to 3x2 by specifying the third keyword argument of the function.

Solution

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Swipe to show menu

Random Arrays

rand()

randint()

Solution

Awesome!

Awesome!

Random Arrays

rand()

randint()

Solution

Awesome!