NumPy random.randint() function in Python is used to return random integers from the values specified with low (inclusive) to high (exclusive) param. It creates an array of a given shape and fills it with random integers from low (inclusive) to high (exclusive).
This function takes a tuple as an integer to specify the size of an array and the behavior of this function is same as the other NumPy functions like the numpy.ones() and numpy.zeros(). In this article, I will explain how to use the NumPy random.randint()
function and using its syntax and parameters how we can generate random integers between two values.
1. Quick Examples of NumPy Random Integer
If you are in a hurry, below are some quick examples of how to use Python NumPy random integer.
# Below are the quick examples
# Example 1: Get the 1-D array of random integers
arr = np.random.randint(low=1, high=6, size = 8)
# Example 2: Get the 2-D array of random integers
arr = np.random.randint(low=1, high=9, size=(2, 4))
# Example 3: Get the 3-D array of random integers
arr = np.random.randint(low=3, high=8, (2, 3, 4))
2. Syntax of NumPy random.randint()
Following is the syntax of random.randint() function.
# Syntax of random.randint()
random.randint(low, high=None, size=None, dtype=int)
2.1 Prameters of random.randint()
Following are the parameters of random.randint().
low
– Lowest (signed) integers, get from the distribution. All the numbers generate usingrandint()
are greater than or equal tolow
.high
– The largest (signed) integers, get from the distribution. It is the upper bound. All the numbers generate fromrandint()
are less thanhigh
.size
– Integer or tuple of integers. Using this to specify the array size or dimension. For instance,size=(3,4)
fills three rows and four columns array with integers.dtype
– Desired dtype of the result.
2.2 Return Value of randint()
It returns a size and shaped array of random integers in the interval [low, high), or by default returns a single random integer.
3. Usage of NumPy random.randint()
The random.randint()
is a NumPy library function that returns an array of random integers that are discrete uniform
distribution of the specified dtype in the half-open interval [low, high). By default the value of high is None. If no value is used for high param then the results are from [0, low).
import numpy as np
# Get the random integers of array
arr = np.random.randint(low=1, high=6, size = 8)
print(arr)
# Output
# [5 3 5 5 4 3 1 5]
4. Generate 2-D Array of Random Integers
Create two-dimensional random arrays by providing a default lower limit and provide high limit to this function. It will return the random integers of 2-D NumPy array of a given shape. use size param to provide the shape of the return array.
# Generate 2D numpy array
arr = np.random.randint(low=1, high=9, size=(2, 4))
print(arr)
# Output
# [[4 8 6 3]
# [7 5 4 4]]
5. Generate Random Integers of 3-D NumPy Array
You can generate the 3-dimensional array of random numbers by providing a tuple of integers into this function. It will return the random integers of a 3-D array of the specified shape.
# Generate randint 3D array
arr = np.random.randint(low=3, high=8, (2, 3, 4))
print(arr)
# Output
# [[[5 3 7 5]
# [5 6 7 4]
# [7 7 6 7]]
# [[6 4 6 6]
# [3 4 4 7]
# [4 6 7 6]]]
6. Conclusion
In this article, I have explained np.random.randint()
function and using this how we can generate random integers of single and multi-dimensional NumPy array of specified shape with python examples.
Happy Learning!!
Related Articles
- Python NumPy array copy
- Python NumPy Concatenate() Function
- How to create an array using ones() function?
- Get the shape of an array
- How to create an array using the zeros() function?
- How to Use NumPy random.uniform() in Python?
- How to Use Numpy random.rand() in Python
- How to Use NumPy random.randn() in Python?
- How to Use NumPy Random choice() in Python?