Companies that use SciPy
Python-based ecosystem of open-source software for mathematics, science, and engineering. It contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.
10,116
companies
List of companies using SciPy
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-d "{
\"company_technology_slug_or\": [
\"scipy\"
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is any of
SciPy
Employees760kSoftware DevelopmentSciPyHigh confidence
Employees4.1kRevenue$1.5BInvestment ManagementSciPyHigh confidence
Employees147kIT Services and IT ConsultingSciPyHigh confidence
Employees166kSoftware DevelopmentSciPyHigh confidence
Employees16kRevenue$422MConsumer ServicesSciPyHigh confidence
Employees37kRevenue$6.6BSoftware DevelopmentSciPyHigh confidence
Employees10kRevenue$34MDefense and Space ManufacturingSciPyHigh confidence
Employees53kRevenue$27BComputer Hardware ManufacturingSciPyHigh confidence
Employees93kRevenue$75BMotor Vehicle ManufacturingSciPyHigh confidence
Employees24kInformation ServicesSciPyHigh confidence
We have data on 10,116 companies and users that use SciPy. Our SciPy users and customers list is available for download and comes enriched with vital company specifics, including industry classification, organizational size, geographical location, funding rounds, and revenue figures, among others.
Technology Usage Statistics and Market Share
How to target SciPy users
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Frequently asked questions
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.
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.
SciPy is a comprehensive open-source library for scientific computing in Python. It provides a wide range of functionalities for mathematical operations, numerical routines, optimization, linear algebra, integration, interpolation, and more. SciPy is built on top of NumPy, another popular Python library for numerical computing, and together they form a powerful ecosystem for scientific computing and data analysis.
Within the category of Data Science Tools, SciPy plays a crucial role in enabling data scientists, researchers, and engineers to perform complex scientific computations efficiently. Its extensive collection of modules and functions makes it a go-to choice for tasks ranging from simple computations to advanced scientific experiments and simulations. By leveraging SciPy, professionals can streamline their workflows, enhance productivity, and tackle intricate data analysis challenges with ease.
Initially founded in 2001 by Travis Oliphant, SciPy emerged as a response to the need for a robust scientific computing toolset in the Python programming language. Over the years, it has evolved into a cornerstone of the Python ecosystem, attracting a vast community of users and contributors dedicated to advancing scientific computing capabilities. With a strong emphasis on performance, usability, and extensibility, SciPy continues to be a pivotal tool for realizing innovative research projects and data-driven insights.
In terms of current market share within the Data Science Tools category, SciPy holds a significant position due to its widespread adoption and reputation among data science and research communities. As the demand for sophisticated data analysis tools continues to rise, SciPy is expected to maintain its growth trajectory and solidify its presence in the market. With ongoing developments, improvements, and expansions, SciPy is poised to further enhance its capabilities and appeal to a broader audience of data enthusiasts and professionals.