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  1. Stackups
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  3. Languages
  4. Languages
  5. Haskell vs R

Haskell vs R

OverviewDecisionsComparisonAlternatives

Overview

Haskell
Haskell
Stacks1.4K
Followers1.2K
Votes527
R Language
R Language
Stacks3.9K
Followers1.9K
Votes418

Haskell vs R: What are the differences?

Introduction

Haskell and R are two popular programming languages, each with its own unique features and functionalities. While both languages are used for data analysis and manipulation, there are key differences between the two.

  1. Syntax: One major difference between Haskell and R lies in their syntax. Haskell follows a statically-typed, functional programming paradigm, with an emphasis on strong type checking and immutability. On the other hand, R is a dynamically-typed language that supports both functional and object-oriented programming styles. R's syntax is more flexible and forgiving compared to Haskell's.

  2. Data Manipulation: Haskell and R have different approaches when it comes to data manipulation. Haskell focuses on the concept of pure functions and immutable data structures, which ensures that functions do not have side effects and can be composed easily. In contrast, R provides built-in functions and packages specifically designed for data manipulation and analysis, making it more convenient for tasks such as data cleaning, transformation, and exploration.

  3. Performance: Performance is another aspect where Haskell and R differ. Haskell is known for its highly optimized, compiled code, which can offer significant performance advantages in terms of execution speed and memory usage. R, on the other hand, is interpreted and often relies on external libraries for performance-critical tasks. While R provides convenient high-level functions, it may be slower compared to Haskell for computationally intensive operations.

  4. Type System: The type systems of Haskell and R also exhibit differences. Haskell has a strong static type system that enforces type safety at compile-time, reducing the chances of runtime errors and improving program correctness. R, being dynamically typed, allows for more flexibility but may exhibit unexpected behavior if types are not carefully handled. This difference can have implications for the maintainability and reliability of code written in these languages.

  5. Community and Libraries: The communities surrounding Haskell and R differ in terms of size and focus. Haskell has a smaller but highly active community that emphasizes creating elegant and optimized code. R, on the other hand, has a larger community with a strong focus on data analysis and statistical computing. As a result, R has a wide range of libraries and packages specifically tailored for data analysis, making it a popular choice in the field.

  6. Domain-specific Focus: Another key difference lies in the domain-specific focus of Haskell and R. Haskell is a general-purpose language that can be used for various applications, including web development, systems programming, and formal verification. R, on the other hand, is primarily designed for statistical computing and data analysis. It provides a rich set of statistical functions and packages, making it a preferred choice for statisticians and data scientists.

In Summary, Haskell and R differ in terms of syntax, approach to data manipulation, performance, type system, community and libraries, and domain-specific focus.

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Advice on Haskell, R Language

Timm
Timm

VP Of Engineering at Flexperto GmbH

Nov 10, 2020

Decided

We have a lot of experience in JavaScript, writing our services in NodeJS allows developers to transition to the back end without any friction, without having to learn a new language. There is also the option to write services in TypeScript, which adds an expressive type layer. The semi-shared ecosystem between front and back end is nice as well, though specifically NodeJS libraries sometimes suffer in quality, compared to other major languages.

As for why we didn't pick the other languages, most of it comes down to "personal preference" and historically grown code bases, but let's do some post-hoc deduction:

Go is a practical choice, reasonably easy to learn, but until we find performance issues with our NodeJS stack, there is simply no reason to switch. The benefits of using NodeJS so far outweigh those of picking Go. This might change in the future.

PHP is a language we're still using in big parts of our system, and are still sometimes writing new code in. Modern PHP has fixed some of its issues, and probably has the fastest development cycle time, but it suffers around modelling complex asynchronous tasks, and (on a personal note) lack of support for writing in a functional style.

We don't use Python, Elixir or Ruby, mostly because of personal preference and for historic reasons.

Rust, though I personally love and use it in my projects, would require us to specifically hire for that, as the learning curve is quite steep. Its web ecosystem is OK by now (see https://www.arewewebyet.org/), but in my opinion, it is still no where near that of the other web languages. In other words, we are not willing to pay the price for playing this innovation card.

Haskell, as with Rust, I personally adore, but is simply too esoteric for us. There are problem domains where it shines, ours is not one of them.

682k views682k
Comments
Samuel
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
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

Haskell
Haskell
R Language
R Language

It is a general purpose language that can be used in any domain and use case, it is ideally suited for proprietary business logic and data analysis, fast prototyping and enhancing existing software environments with correct code, performance and scalability.

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.

Statically typed; Purely functional; Type inference; Concurrent
-
Statistics
Stacks
1.4K
Stacks
3.9K
Followers
1.2K
Followers
1.9K
Votes
527
Votes
418
Pros & Cons
Pros
  • 90
    Purely-functional programming
  • 66
    Statically typed
  • 59
    Type-safe
  • 39
    Open source
  • 38
    Great community
Cons
  • 9
    Too much distraction in language extensions
  • 8
    Error messages can be very confusing
  • 5
    Libraries have poor documentation
  • 3
    No best practices
  • 3
    No good ABI
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
    No push command for vectors/lists
  • 2
    Messy syntax for string concatenation

What are some alternatives to Haskell, R Language?

JavaScript

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

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

PHP

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

Ruby

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

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

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

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#

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

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

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.

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