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NumPy
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NumPy

Overview
Synopsis

NumPy provides a comprehensive package for scientific computing using a python programming language.

Category

Predictive Analytics Software Free

Features

• Powerful N-dimensional array object
• Sophisticated (broadcasting) functions
• Tools for integrating C/C++ and Fortran code
• Useful linear algebra
• Fourier transform
• Random number

License

Proprietary

Price

Contact for Pricing

Pricing

Subscription

Free Trial

Available

Users Size

Small (<50 employees), Medium (50 to 1000 employees), Enterprise (>1001 employees)

Website
Company

NumPy

What is best?

• Tools for integrating C/C++ and Fortran code
• Useful linear algebra
• Fourier transform
• Random number

What are the benefits?

• Seamlessly and speedily integrate with a wide variety of databases
• Defines data types
• Efficient multi-dimensional container for generic data
• Able to reuse with few restrictions
• It is licensed

PAT Rating™ ( Beta)
Editor Rating
Aggregated User Rating
Rate Here
Ease of use
7.6
Features & Functionality
7.6
Advanced Features
7.6
Integration
7.6
Performance
7.6
Customer Support
7.6
Implementation
Renew & Recommend
Bottom Line

NumPy is a fundamental and complete suite library used for scientific computing by data scientists when using Python programming language and supports large matrices and multi-dimensional arrays and high level mathematics.

7.6
Editor Rating
Aggregated User Rating
You have rated this

NumPy provides a comprehensive package for scientific computing using a python programming language. The NumPy library provides support to big multi-dimensional arrays and matrices. NumPy fully integrated package contains several features that makes it ideal for scientific computing, calculation of multi-dimensional arrays, matrices and even high level mathematics calculations. The first feature of NumPy is the powerful N-dimensional array object that is used in the multi-dimensional arrays. Data scientists and developers performing broadcasting are also sorted out as NumPy provides detailed and easy to use functions. NumPy also provides C or C++ tools to developers and data scientists. The C++ or C tools are integrated making them to be easily used by end users. The C and C++ tools also come with Fortran code used by data scientists. NumPy provides developers, end users, and data scientists useful linear algebra capabilities. The linear algebra capabilities are useful in the high level mathematics calculations. The useful Fourier transform capabilities provided by NumPy are also useful in the high level mathematics calculations. NumPy also provides the random number capabilities to developers and data scientists for calculating high level matrices along other high level calculations. NumPy enables data scientists, end users and developers use generic data in the scientific computing. This is achieved as NumPy provides an efficient multi-dimensional container for such type of scientific computing. The multi-dimensional container is also capable of defining the data types available in scientific computing. NumPy having the ability to define the data types enables it to seamlessly and quickly integrate with a broad range of databases used in scientific computing.

NumPy
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