- Trending Categories
- Data Structure
- Networking
- RDBMS
- Operating System
- Java
- iOS
- HTML
- CSS
- Android
- Python
- C Programming
- C++
- C#
- MongoDB
- MySQL
- Javascript
- PHP

- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who

# Discuss broadcasting in Numpy in Python?

NumPy refers to ‘Numerical’ ‘Python’. It is a library that contains multidimensional array objects and multiple methods that help in processing the arrays.

NumPy can be used to perform a wide variety of operations on arrays. It is used in conjunction with packages like SciPy, Matplotlib and so on. NumPy+Matplotlib can be understood as an alternative to MatLab. It is an open-source package, which means it can be used by anyone. Standard Python distribution doesn’t include NumPy package by default. The package has to be separately installed using the installer ‘pip’.

For Windows, it has been shown below −

pip install numpy

Once this command is executed on the command line, it can be imported into the Python environment and used.

The most important object present in NumPy package is an n-dimensional array which is known as ‘ndarray’. It defines the collection of items of the same type. These values inside the ndarray can be accessed using indexing (0-based index). Every item in the ndarray takes the same size of block in the memory space. Every element’s type in the ndarray can be found using the ‘dtype’ function. An item from the ndarray can be extracted using array slicing. It is represented as an object of array scalar type.

With respect to Numpy array, broadcasting refers to the ability of this package to treat arrays that are of different shapes during arithmetic operations. If two arrays are not of same type, no error is thrown up. Instead, the operations go on smoothly.

## Example

import numpy as np arr_1 = np.array([4, 6, 8, 0, 3]) arr_2 = np.array([11,3,7,78, 999]) print("The first ndarray is ") print(arr_1) print("The second ndarray is ") print(arr_2) arr_3 = arr_1 * arr_2 print("The resultant array is ") print(arr_3)

## Output

The first ndarray is [4 6 8 0 3] The second ndarray is [ 11 3 7 78 999] The resultant array is [ 44 18 56 0 2997]

## Explanation

The required libraries are imported into Python environment.

Two ndarrays are defined with numeric values inside them.

They ae printed on the console.

The third array is defined as the product of the first two ndarrays.

The resultant array is displayed on the console.

- Related Questions & Answers
- Broadcasting with NumPy Arrays in Python
- Add two vectors using broadcasting in Numpy
- Discuss how the sort function can be applied on NumPy arrays in Python?
- What is Broadcasting in Computer Network?
- Discuss the Hardware Algorithm in Computer Architecture?
- Discuss the MultiLevel Interrupts in Computer Architecture?
- Discuss the Memory Hierarchy in Computer Architecture?
- Discuss the Associative Mapping in Computer Architecture?
- Discuss few characteristics of MySQL
- Discuss the history of MySQL
- Discuss the I/O Interface in Computer Architecture?
- Discuss the Data Transfer Schemes in Computer Architecture?
- Discuss the Single Level Interrupts in Computer Architecture?
- Discuss the Set Associative Mapping in Computer Architecture?
- Discuss the various Input-Output Instructions in Computer Architecture?