numpy.cos() in Python Last Updated : 08 Mar, 2024 Comments Improve Suggest changes Like Article Like Report numpy.cos(x[, out]) = ufunc 'cos') : This mathematical function helps user to calculate trigonometric cosine for all x(being the array elements). Parameters : array : [array_like]elements are in radians. 2pi Radians = 360 degrees Return : An array with trigonometric cosine of x for all x i.e. array elements Code #1 : Working Python # Python program explaining # cos() function import numpy as np import math in_array = [0, math.pi / 2, np.pi / 3, np.pi] print ("Input array : \n", in_array) cos_Values = np.cos(in_array) print ("\nCosine values : \n", cos_Values) Output : Input array : [0, 1.5707963267948966, 1.0471975511965976, 3.141592653589793] Cosine values : [ 1.00000000e+00 6.12323400e-17 5.00000000e-01 -1.00000000e+00] Code #2 : Graphical representation Python # Python program showing # Graphical representation of # cos() function import numpy as np import matplotlib.pyplot as plt in_array = np.linspace(-(2*np.pi), 2*np.pi, 20) out_array = np.cos(in_array) print("in_array : ", in_array) print("\nout_array : ", out_array) # red for numpy.cos() plt.plot(in_array, out_array, color = 'red', marker = "o") plt.title("numpy.cos()") plt.xlabel("X") plt.ylabel("Y") plt.show() Output : in_array : [-6.28318531 -5.62179738 -4.96040945 -4.29902153 -3.6376336 -2.97624567 -2.31485774 -1.65346982 -0.99208189 -0.33069396 0.33069396 0.99208189 1.65346982 2.31485774 2.97624567 3.6376336 4.29902153 4.96040945 5.62179738 6.28318531] out_array : [ 1. 0.78914051 0.24548549 -0.40169542 -0.87947375 -0.9863613 -0.67728157 -0.08257935 0.54694816 0.94581724 0.94581724 0.54694816 -0.08257935 -0.67728157 -0.9863613 -0.87947375 -0.40169542 0.24548549 0.78914051 1. ] Comment More info M mohit gupta_omg :) Follow Improve Article Tags : Python Python-numpy Python numpy-Mathematical Function Explore Python FundamentalsPython Introduction 3 min read Input and Output in Python 4 min read Python Variables 5 min read Python Operators 5 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 7 min read Python Functions 5 min read Recursion in Python 6 min read Python Lambda Functions 5 min read Python Data StructuresPython String 5 min read Python Lists 5 min read Python Tuples 4 min read Dictionaries in Python 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 12 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 6 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 7 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 3 min read Python Coding Practice 1 min read Python Interview Questions and Answers 15+ min read Like