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MATLAB

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539
+ 1
29
NumPy

1K
619
+ 1
7
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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.

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Pros of MATLAB
Pros of NumPy
  • 14
    Simulink
  • 5
    Functions, statements, plots, directory navigation easy
  • 3
    Model based software development
  • 3
    S-Functions
  • 2
    REPL
  • 1
    Simple variabel control
  • 1
    Solve invertible matrix
  • 6
    Great for data analysis
  • 1
    Faster than list

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Cons of MATLAB
Cons of NumPy
  • 1
    Parameter-value pairs syntax to pass arguments clunky
  • 0
    Does not support named function arguments
  • 0
    Doesn't allow unpacking tuples/arguments lists with *
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    - No public GitHub repository available -

    What is MATLAB?

    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?

    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.

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    What companies use MATLAB?
    What companies use NumPy?
    See which teams inside your own company are using MATLAB or NumPy.
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    What tools integrate with MATLAB?
    What tools integrate with NumPy?

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    What are some alternatives to MATLAB and NumPy?
    R Language
    R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible.
    Octave
    It is software featuring a high-level programming language, primarily intended for numerical computations. Octave helps in solving linear and nonlinear problems numerically, and for performing other numerical experiments using a language that is mostly compatible with MATLAB.
    Tableau
    Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.
    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.
    Matplotlib
    It is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. It can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application servers, and four graphical user interface toolkits.
    See all alternatives