MATLAB vs NumPy

Overview

MATLAB

Stacks1.1K

Followers702

Votes37

NumPy

Stacks4.3K

Followers799

Votes15

GitHub Stars30.7K

Forks11.7K

MATLAB vs NumPy: What are the differences?

What is MATLAB? A high-level language and interactive environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java.

What is NumPy? Fundamental package for scientific computing with Python. Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.

MATLAB belongs to "Languages" category of the tech stack, while NumPy can be primarily classified under "Data Science Tools".

NumPy is an open source tool with 11.1K GitHub stars and 3.67K GitHub forks. Here's a link to NumPy's open source repository on GitHub.

Instacart, Suggestic, and Twilio SendGrid are some of the popular companies that use NumPy, whereas MATLAB is used by Empatica, Wham City Lights, and Walter. NumPy has a broader approval, being mentioned in 63 company stacks & 34 developers stacks; compared to MATLAB, which is listed in 12 company stacks and 23 developer stacks.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs

CLI (Node.js)

Manual

Detailed Comparison

MATLAB	NumPy
Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java.	Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
-	Powerful n-dimensional arrays; Numerical computing tools; Interoperable; Performant; Easy to use
Statistics
GitHub Stars -	GitHub Stars 30.7K
GitHub Forks -	GitHub Forks 11.7K
Stacks 1.1K	Stacks 4.3K
Followers 702	Followers 799
Votes 37	Votes 15
Pros & Cons
Pros 20 Simulink 5 Model based software development 5 Functions, statements, plots, directory navigation easy 3 S-Functions 2 REPL Cons 2 Does not support named function arguments 2 Doesn't allow unpacking tuples/arguments lists with * 2 Parameter-value pairs syntax to pass arguments clunky 1 Costs a lot	Pros 10 Great for data analysis 4 Faster than list
Integrations
No integrations available	Python

What are some alternatives to MATLAB, NumPy?

JavaScript

JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles.

Python

Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.

PHP

Fast, flexible and pragmatic, PHP powers everything from your blog to the most popular websites in the world.

Ruby

Ruby is a language of careful balance. Its creator, Yukihiro “Matz” Matsumoto, blended parts of his favorite languages (Perl, Smalltalk, Eiffel, Ada, and Lisp) to form a new language that balanced functional programming with imperative programming.

Java

Java is a programming language and computing platform first released by Sun Microsystems in 1995. There are lots of applications and websites that will not work unless you have Java installed, and more are created every day. Java is fast, secure, and reliable. From laptops to datacenters, game consoles to scientific supercomputers, cell phones to the Internet, Java is everywhere!

Golang

Go is expressive, concise, clean, and efficient. Its concurrency mechanisms make it easy to write programs that get the most out of multicore and networked machines, while its novel type system enables flexible and modular program construction. Go compiles quickly to machine code yet has the convenience of garbage collection and the power of run-time reflection. It's a fast, statically typed, compiled language that feels like a dynamically typed, interpreted language.

HTML5

HTML5 is a core technology markup language of the Internet used for structuring and presenting content for the World Wide Web. As of October 2014 this is the final and complete fifth revision of the HTML standard of the World Wide Web Consortium (W3C). The previous version, HTML 4, was standardised in 1997.

C#

C# (pronounced "See Sharp") is a simple, modern, object-oriented, and type-safe programming language. C# has its roots in the C family of languages and will be immediately familiar to C, C++, Java, and JavaScript programmers.

Scala

Scala is an acronym for “Scalable Language”. This means that Scala grows with you. You can play with it by typing one-line expressions and observing the results. But you can also rely on it for large mission critical systems, as many companies, including Twitter, LinkedIn, or Intel do. To some, Scala feels like a scripting language. Its syntax is concise and low ceremony; its types get out of the way because the compiler can infer them.

Elixir

Elixir leverages the Erlang VM, known for running low-latency, distributed and fault-tolerant systems, while also being successfully used in web development and the embedded software domain.