Operations on NumPy Array

Why Numpy ?

NumPy revolutionized the way we handle numerical data in Python. It is created to address the limitations of traditional Python lists when it comes to numerical computing. It is developed by Travis Olliphant in 2005....

Introduction

Introduction to Numpy Python NumPy NumPy array in Python Basics of NumPy Arrays Python Lists VS Numpy Arrays Numpy – ndarray Data type Object (dtype) in NumPy Python...

Creating NumPy Array

Numpy – Array Creation The Arange Method The Zero Method Create a Numpy array filled with all ones The linspace Method The eye Method Numpy Meshgrid function Creating a one-dimensional NumPy array How to create an empty and a full NumPy array? Create a Numpy array filled with all zeros Create a Numpy array filled with all ones How to generate 2-D Gaussian array using NumPy? How to create a vector in Python using NumPy Create the record array from list of individual records...

NumPy Array Manipulation

Copy and View in NumPy Array How to Copy NumPy array into another array? Appending values at the end of an NumPy array How to swap columns of a given NumPy array? Insert a new axis within a NumPy array Stack the sequence of NumPy array horizontally Stack the sequence of NumPy array vertically Joining NumPy Array Combining a one and a two-dimensional NumPy Array Concatenate two arrays – np.ma.concatenate() Combined array index by index Splitting Arrays in NumPy Compare two NumPy arrays Find the union of two NumPy arrays Find unique rows in a NumPy array Get the unique values from an array Trim the leading and/or trailing zeros from a 1-D array...

Matrix in NumPy

Matrix manipulation in Python numpy matrix operations | empty() function numpy matrix operations | zeros() function numpy matrix operations | ones() function numpy matrix operations | eye() function numpy matrix operations | identity() function Adding and Subtracting Matrices in Python Matrix Multiplication in NumPy Dot product of two arrays NumPy | Vector Multiplication How to calculate dot product of two vectors in Python? Multiplication of two Matrices in Single line using Numpy in Python Get the eigen values of a matrix Calculate the determinant of a matrix using NumPy Find the transpose of the matrix Find the variance of a matrix Compute the inverse of a matrix using NumPy...

Operations on NumPy Array

Numpy – Binary Operations Numpy – Mathematical Function Numpy – String Operations...

Reshaping NumPy Array

Reshape NumPy Array Resize the shape of the given matrix Reshape the shape of the given matrix Get the Shape of NumPy Array Change the dimension of a NumPy array Change shape and size of array in-place Flatten a Matrix in Python using NumPy Flatten a matrix – matrix.ravel() Move axes of an array to new positions Interchange two axes of an array Swap the axes a matrix Split an array into multiple sub-arrays vertically Split an array into multiple sub-arrays horizontally Give a new shape to the masked array without changing its data Squeeze the size of a matrix...

Indexing NumPy Array

Basic Slicing and Advanced Indexing in NumPy Python Get selected slices of an array along mentioned axis Accessing Data Along Multiple Dimensions Arrays in Python Numpy How to access different rows of a multidimensional NumPy array? Get the indices for the lower-triangle of an (n, m) array...

Arithmetic operations on NumPy Array

Broadcasting with NumPy Arrays Estimation of Variable Python: Operations on Numpy Arrays How to use the NumPy sum function? Divide the NumPy array element wise Computes the inner product of two arrays Absolute Deviation and Absolute Mean Deviation using NumPy Find the standard deviation a matrix Calculate the GCD of the NumPy array...

Linear Algebra in NumPy Array

Numpy | Linear Algebra Get the QR factorization of a given NumPy array How to get the magnitude of a vector in NumPy? Compute the eigenvalues and right eigenvectors of a given square array using NumPy?...

NumPy and Random Data

Random sampling in numpy | ranf() function Random sampling in numpy | random() function Random sampling in numpy | random_sample() function Random sampling in numpy | sample() function Random sampling in numpy | random_integers() function Random sampling in numpy | randint() function Get random elements from NumPy – random.choice() How to choose elements from the list with different probability using NumPy? How to get weighted random choice in Python? How to get the random positioning of different integer values? Get Random Elements form geometric distribution Get Random samples of a sequence of permutation...

Sorting and Searching in NumPy Array

Searching in a NumPy array How to sort a Numpy Array Numpy – Sorting, Searching and Counting Variations in different Sorting techniques in Python Sort a complex array Get the minimum value of masked array Sort the values in a matrix Sort the elements in the given matrix having one or more dimension...

Universal Functions

Numpy ufunc | Universal functions Create your own universal function in NumPy...

Working With Images

Create a white image using NumPy in Python Convert a NumPy array to an image How to Convert images to NumPy array? Convert an image to NumPy array and save it to CSV file using Python?...

Projects and Applications with NumPy

Print checkerboard pattern of nxn using numpy Implementation of neural network from scratch using NumPy Analyzing selling price of used cars using Python...

Python Numpy Exercises

Python NumPy – Practice Exercises, Questions, and Solutions Python MCQ (Multiple Choice Questions) with Answers...

Numpy Program Examples

Python import numpy as np    # Create two NumPy arrays array1 = np.array([1, 2, 3]) array2 = np.array([4, 5, 6])    # Perform element-wise addition result_addition = array1 + array2    # Display the original arrays and the results print("Array 1:", array1) print("Array 2:", array2) print("Element-wise Addition:", result_addition)...

Conclusion

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FAQs: NumPy Tutorial

From simple calculations to complex data manipulation, NumPy empowers you to tackle any numerical challenge, no matter the dimensionality. Its intuitive syntax and powerful functionality make you feel like you’re working with single numbers, even when manipulating vast datasets....