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Learn Random Arrays | NumPy Basics
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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 β€” 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)
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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).

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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)
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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

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

Solution

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SectionΒ 1. ChapterΒ 7

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book
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 β€” 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)
copy

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)
copy

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

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

Solution

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

SectionΒ 1. ChapterΒ 7
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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