Random sampling in numpy | randint() function Last Updated : 26 Feb, 2019 Comments Improve Suggest changes 11 Likes Like Report numpy.random.randint() is one of the function for doing random sampling in numpy. It returns an array of specified shape and fills it with random integers from low (inclusive) to high (exclusive), i.e. in the interval [low, high). Syntax : numpy.random.randint(low, high=None, size=None, dtype='l') Parameters : low : [int] Lowest (signed) integer to be drawn from the distribution.But, it works as a highest integer in the sample if high=None. high : [int, optional] Largest (signed) integer to be drawn from the distribution. size : [int or tuple of ints, optional] Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn. Default is None, in which case a single value is returned. dtype : [optional] Desired output data-type. Return : Array of random integers in the interval [low, high) or a single such random int if size not provided. Code #1 : Python3 # Python program explaining # numpy.random.randint() function # importing numpy import numpy as geek # output array out_arr = geek.random.randint(low = 0, high = 3, size = 5) print ("Output 1D Array filled with random integers : ", out_arr) Output : Output 1D Array filled with random integers : [1 1 0 1 1] Code #2 : Python3 # Python program explaining # numpy.random.randint() function # importing numpy import numpy as geek # output array out_arr = geek.random.randint(low = 4, size =(2, 3)) print ("Output 2D Array filled with random integers : ", out_arr) Output : Output 2D Array filled with random integers : [[1 1 0] [1 0 3]] Code #3 : Python3 # Python program explaining # numpy.random.randint() function # importing numpy import numpy as geek # output array out_arr = geek.random.randint(2, 10, (2, 3, 4)) print ("Output 3D Array filled with random integers : ", out_arr) Output : Output 3D Array filled with random integers : [[[4 8 5 7] [6 5 6 7] [4 3 4 3]] [[2 9 2 2] [3 2 2 3] [6 8 3 2]]] Comment J jana_sayantan Follow 11 Improve J jana_sayantan Follow 11 Improve Article Tags : Python Python-numpy Python numpy-Random sampling Explore Python FundamentalsPython Introduction 2 min read Input and Output in Python 4 min read Python Variables 5 min read Python Operators 4 min read Python Keywords 2 min read Python Data Types 8 min read Conditional Statements in Python 3 min read Loops in Python - For, While and Nested Loops 5 min read Python Functions 5 min read Recursion in Python 4 min read Python Lambda Functions 5 min read Python Data StructuresPython String 5 min read Python Lists 4 min read Python Tuples 4 min read Python Dictionary 3 min read Python Sets 6 min read Python Arrays 7 min read List Comprehension in Python 4 min read Advanced PythonPython OOP Concepts 11 min read Python Exception Handling 5 min read File Handling in Python 4 min read Python Database Tutorial 4 min read Python MongoDB Tutorial 2 min read Python MySQL 9 min read Python Packages 10 min read Python Modules 7 min read Python DSA Libraries 15 min read List of Python GUI Library and Packages 3 min read Data Science with PythonNumPy Tutorial - Python Library 3 min read Pandas Tutorial 4 min read Matplotlib Tutorial 5 min read Python Seaborn Tutorial 15+ min read StatsModel Library- Tutorial 4 min read Learning Model Building in Scikit-learn 8 min read TensorFlow Tutorial 2 min read PyTorch Tutorial 6 min read Web Development with PythonFlask Tutorial 8 min read Django Tutorial | Learn Django Framework 7 min read Django ORM - Inserting, Updating & Deleting Data 4 min read Templating With Jinja2 in Flask 6 min read Django Templates 7 min read Python | Build a REST API using Flask 3 min read How to Create a basic API using Django Rest Framework ? 4 min read Python PracticePython Quiz 1 min read Python Coding Practice 1 min read Python Interview Questions and Answers 15+ min read Like