R Language

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R Language

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Arc vs R: What are the differences?

Developers describe Arc as "A dialect of the Lisp programming language developed by Paul Graham and Robert Morris". Arc is designed for exploratory programming: the kind where you decide what to write by writing it. A good medium for exploratory programming is one that makes programs brief and malleable, so that's what we've aimed for. This is a medium for sketching software. On the other hand, R is detailed as "A language and environment for statistical computing and graphics". 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.

Arc and R belong to "Languages" category of the tech stack.

AdRoll, Instacart, and Verba are some of the popular companies that use R, whereas Arc is used by Helpful, Cask, and Icalia Labs. R has a broader approval, being mentioned in 128 company stacks & 97 developers stacks; compared to Arc, which is listed in 7 company stacks and 6 developer stacks.

Decisions about 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 R Language
  • 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
    Shiny interactive plots
  • 6
    Preferred Medium
  • 5
    Automated data reports
  • 4
    Cutting-edge machine learning straight from researchers
  • 3
    Machine Learning
  • 2
    Graphical visualization
  • 1
    Flexible Syntax
Cons of R Language
  • 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

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

Blog Posts

Aug 28 2019 at 3:10AM

Segment

PythonJavaAmazon S3+16
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GitHubGitDocker+34
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