Companies that use NumPy

Frequently asked questions

What is the source of this data?

Our data is sourced from job postings collected from millions of companies. We monitor these postings on company websites, job boards, and other recruitment platforms. Analyzing job postings provides a reliable method to understand the technologies companies are employing, including their use of internal tools.

How often is the data updated?

We refresh our data daily to ensure you are accessing the most current information available. This frequent updating process guarantees that our insights and intelligence reflect the latest developments and trends within the industry.

What is NumPy?

NumPy, short for Numerical Python, is a fundamental package in Python that is widely used for scientific computing. It provides support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays. NumPy's main feature is its efficient implementation of mathematical functions, making it an essential tool for tasks such as linear algebra, Fourier transforms, and random number capabilities.

In the realm of Data Science Tools, NumPy plays a crucial role in data manipulation, analysis, and visualization. It serves as the backbone for many other libraries and frameworks in the data science ecosystem due to its high performance and ease of use. NumPy arrays are used in various applications, including machine learning algorithms, statistical analysis, image processing, and more.

NumPy was first created in 2005 by Travis Oliphant with the motivation to provide a powerful array processing capability to Python, bridging the gap between numeric computing and a general-purpose programming language. Since then, NumPy has gained immense popularity and has become a cornerstone in the Python data science and scientific computing communities.

Currently, NumPy holds a significant market share within the Data Science Tools category, largely due to its widespread adoption and robust functionality. With the increasing demand for data-driven solutions in various industries, the market share of NumPy is expected to continue growing in the foreseeable future. Its versatility, performance, and extensive library of functions make NumPy a preferred choice for data scientists, researchers, and developers working on numerical computations and data analysis tasks.

How to get an updated list of companies that use NumPy?

You can access an updated list of companies using NumPy by visiting TheirStack.com. Our platform provides a comprehensive database of companies utilizing various technologies and internal tools.

How many customers does NumPy have?

As of now, we have data on 16,918 companies that use NumPy.

Who uses NumPy?

NumPy is used by a diverse range of organizations across various industries, including "Retail", "Software Development", "Technology, Information And Internet", "Motor Vehicle Manufacturing", "Software Development", "It Services And It Consulting", "Software Development", "Oil And Gas", "Research Services", "Higher Education". For a comprehensive list of all industries utilizing NumPy, please visit TheirStack.com.

What companies use NumPy?

Some of the companies that use NumPy include Amazon.com, Amazon, myGwork - LGBTQ+ Business Community, Tesla, Intuit, Granify, Blue Yonder, Validere, CNRS, Carnegie Mellon University and many more. You can find a complete list of 16,918 companies that use NumPy on TheirStack.com.

In which countries NumPy is used the most?

Based on our data, NumPy is most popular in United States (4,854 companies), United Kingdom (1,147 companies), India (565 companies), France (443 companies), Germany (414 companies), Canada (347 companies), Spain (315 companies), Brazil (207 companies), Netherlands (170 companies), Australia (121 companies). However, it is used by companies all over the world.

How to find companies that use NumPy?

You can find companies using NumPy by searching for it on TheirStack.com, We track job postings from millions of companies and use them to discover what technologies and internal tools they are using.