MATLAB vs R

Overview

R Language

Stacks3.9K

Followers1.9K

Votes418

MATLAB

Stacks1.1K

Followers702

Votes37

MATLAB vs R: What are the differences?

<Write Introduction here>

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.
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.
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.
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.
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.
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.

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Advice on R Language, MATLAB

Samuel

Oct 11, 2021

Decided

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.

158k views158k

Comments

Mohiuddin

Mar 7, 2022

Needs advice

Extract the daily COVID-19 confirmed cases for City1, City2, and City3 from all the cities. Normalize the daily COVID-19 confirmed cases for the three cities using their respective populations. The 2019 mid-year estimated population figures for City1, City2, and City3 are 100,000, 200,000, and 300,000 respectively.

df <- read.csv ("coronavirus.csv", header = TRUE ) library(dplyr) df %>% group_by(City.name) %>% summarise(Sum = sum(Daily.cases))

Cant select multiple variables from dplyr::Groupby. Can anyone help me with the right code along with the second part of the question as I am not able to find solution as well.

3.15k views3.15k

Comments

Detailed Comparison

R Language	MATLAB
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.	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.
Statistics
Stacks 3.9K	Stacks 1.1K
Followers 1.9K	Followers 702
Votes 418	Votes 37
Pros & Cons
Pros 86 Data analysis 64 Graphics and data visualization 55 Free 45 Great community 38 Flexible statistical analysis toolkit Cons 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	Pros 20 Simulink 5 Functions, statements, plots, directory navigation easy 5 Model based software development 3 S-Functions 2 REPL Cons 2 Doesn't allow unpacking tuples/arguments lists with * 2 Parameter-value pairs syntax to pass arguments clunky 2 Does not support named function arguments 1 Costs a lot

What are some alternatives to R Language, MATLAB?

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.

Related Comparisons

MATLAB vs R: What are the differences?

<Write Introduction here>

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.
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.
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.
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.
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.
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.

MATLAB vs R

Overview