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MATLAB vs R: What are the differences?

<Write Introduction here>
  1. Syntax: MATLAB uses a more intuitive syntax similar to traditional mathematical notations, making it easier for beginners to understand and write code. R, on the other hand, has a more complex syntax with extensive use of brackets and parentheses.

  2. Flexibility: MATLAB is primarily designed for numerical computing and matrix operations, while R is a language specifically designed for statistical computing and graphics. This difference in focus gives R an edge when it comes to complex statistical analysis and visualization tasks.

  3. Cost: MATLAB is a commercial software and requires a paid license for full functionality, which can be a significant cost barrier for individual users or organizations. R, being open-source, is free to use and has a vast community contributing to its development and support.

  4. Graphics: R offers superior data visualization capabilities through its wide range of packages like ggplot2, lattice, and plotly, which provide more customization options and better quality of graphs compared to MATLAB's plotting functions.

  5. Community Support: The R community is known for its active participation and collaboration, offering a wealth of resources, extensive documentation, and frequent updates to packages. MATLAB, while having a strong user base, may lack the same level of community engagement and support.

  6. Interoperability: While both MATLAB and R can integrate with other programming languages, MATLAB is more commonly used in engineering and scientific applications due to its compatibility with tools like Simulink for simulation and modeling, whereas R excels in statistical analysis and research with seamless integration with databases and web applications.

In Summary, MATLAB and R differ in syntax, flexibility, cost, graphics, community support, and interoperability, catering to diverse needs in numerical computing and statistical analysis.

Decisions about MATLAB and R Language

MACHINE LEARNING

Python is the default go-to for machine learning. It has a wide variety of useful packages such as pandas and numpy to aid with ML, as well as deep-learning frameworks. Furthermore, it is more production-friendly compared to other ML languages such as R.

Pytorch is a deep-learning framework that is both flexible and fast compared to Tensorflow + Keras. It is also well documented and has a large community to answer lingering questions.

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Pros of MATLAB
Pros of R Language
  • 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
  • 84
    Data analysis
  • 63
    Graphics and data visualization
  • 54
    Free
  • 45
    Great community
  • 38
    Flexible statistical analysis toolkit
  • 27
    Easy packages setup
  • 27
    Access to powerful, cutting-edge analytics
  • 18
    Interactive
  • 13
    R Studio IDE
  • 9
    Hacky
  • 7
    Shiny apps
  • 6
    Preferred Medium
  • 6
    Shiny interactive plots
  • 5
    Automated data reports
  • 4
    Cutting-edge machine learning straight from researchers
  • 3
    Machine Learning
  • 2
    Graphical visualization
  • 1
    Flexible Syntax

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Cons of MATLAB
Cons of R Language
  • 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
  • 6
    Very messy syntax
  • 4
    Tables must fit in RAM
  • 3
    Arrays indices start with 1
  • 2
    Messy syntax for string concatenation
  • 2
    No push command for vectors/lists
  • 1
    Messy character encoding
  • 0
    Poor syntax for classes
  • 0
    Messy syntax for array/vector combination

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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 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.

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

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Aug 28 2019 at 3:10AM

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What are some alternatives to MATLAB and R Language?
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.
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