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MATLAB vs Matplotlib: What are the differences?

Key Differences between MATLAB and Matplotlib

In this comparison, we will analyze the key differences between MATLAB and Matplotlib.

  1. Coding Syntax: One of the major differences between MATLAB and Matplotlib is their coding syntax. MATLAB uses a proprietary scripting language, whereas Matplotlib is a Python library that utilizes Python's syntax. This difference implies that MATLAB code cannot be directly executed in Matplotlib, and vice versa.

  2. Functionality: MATLAB offers a wide range of functionalities and toolboxes to handle mathematical and scientific computations, including signal processing, image processing, and control system design. On the other hand, Matplotlib focuses on creating high-quality data visualizations, making it a suitable library for data exploration and presentation tasks.

  3. Integration with Other Libraries: Matplotlib integrates seamlessly with other Python libraries such as NumPy and Pandas, which allows for efficient data handling and manipulation. MATLAB, however, requires additional toolboxes or manual efforts to integrate with external libraries and to achieve similar functionality.

  4. Cost of Usage: MATLAB is a commercial software that requires a paid license to access its full capabilities. In contrast, Matplotlib is an open-source library that is freely available and can be easily installed using Python's package manager. This cost difference makes Matplotlib more accessible to users with limited resources.

  5. Development Environment: MATLAB provides an integrated development environment (IDE) that offers a user-friendly interface, interactive debugging, and direct execution of code blocks. Matplotlib, being a Python library, primarily relies on third-party IDEs or notebooks (e.g., Jupyter) for coding and execution.

  6. Community Support: Python and its associated libraries, including Matplotlib, have a vast and active community of users and developers. This widespread support offers a wealth of resources such as forums, tutorials, and documentation, making it easier to troubleshoot issues and learn new techniques. While MATLAB also has a significant user community, its size and resources may be comparatively limited.

In summary, the key differences between MATLAB and Matplotlib lie in their coding syntax, functionalities, integration with other libraries, cost of usage, development environment, and community support.

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Pros of MATLAB
Pros of Matplotlib
  • 20
    Simulink
  • 5
    Model based software development
  • 5
    Functions, statements, plots, directory navigation easy
  • 3
    S-Functions
  • 2
    REPL
  • 1
    Simple variabel control
  • 1
    Solve invertible matrix
  • 11
    The standard Swiss Army Knife of plotting

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Cons of MATLAB
Cons of Matplotlib
  • 2
    Parameter-value pairs syntax to pass arguments clunky
  • 2
    Doesn't allow unpacking tuples/arguments lists with *
  • 2
    Does not support named function arguments
  • 5
    Lots of code

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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 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.

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What companies use MATLAB?
What companies use Matplotlib?
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What tools integrate with MATLAB?
What tools integrate with Matplotlib?

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What are some alternatives to MATLAB and Matplotlib?
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.
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.
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.
See all alternatives