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R Language

2.9K
1.8K
+ 1
409
SciPy

587
163
+ 1
0
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R vs SciPy: What are the differences?

What is R? 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.

What is SciPy? Scientific Computing Tools for Python. Python-based ecosystem of open-source software for mathematics, science, and engineering. It contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.

R and SciPy are primarily classified as "Languages" and "Data Science" tools respectively.

SciPy is an open source tool with 6.01K GitHub stars and 2.85K GitHub forks. Here's a link to SciPy's open source repository on GitHub.

Instacart, Zalando, and Thumbtack are some of the popular companies that use R, whereas SciPy is used by Suggestic, Botimize, and Zetaops. R has a broader approval, being mentioned in 128 company stacks & 97 developers stacks; compared to SciPy, which is listed in 12 company stacks and 4 developer stacks.

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Pros of R Language
Pros of SciPy
  • 83
    Data analysis
  • 62
    Graphics and data visualization
  • 53
    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 R Language
    Cons of SciPy
    • 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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      - No public GitHub repository available -

      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.

      What is SciPy?

      Python-based ecosystem of open-source software for mathematics, science, and engineering. It contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.

      Need advice about which tool to choose?Ask the StackShare community!

      Jobs that mention R Language and SciPy as a desired skillset
      What companies use R Language?
      What companies use SciPy?
      See which teams inside your own company are using R Language or SciPy.
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      What tools integrate with R Language?
      What tools integrate with SciPy?

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      Blog Posts

      Aug 28 2019 at 3:10AM

      Segment

      PythonJavaAmazon S3+16
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      GitHubGitDocker+34
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      What are some alternatives to R Language and SciPy?
      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.
      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.
      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.
      SAS
      It is a command-driven software package used for statistical analysis and data visualization. It is available only for Windows operating systems. It is arguably one of the most widely used statistical software packages in both industry and academia.
      Rust
      Rust is a systems programming language that combines strong compile-time correctness guarantees with fast performance. It improves upon the ideas of other systems languages like C++ by providing guaranteed memory safety (no crashes, no data races) and complete control over the lifecycle of memory.
      See all alternatives