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NumPy

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583
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6
R Language

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1.4K
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368
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NumPy vs R: What are the differences?

NumPy: Fundamental package for scientific computing with Python. 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; 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.

NumPy belongs to "Data Science Tools" category of the tech stack, while R can be primarily classified under "Languages".

NumPy is an open source tool with 11.1K GitHub stars and 3.67K GitHub forks. Here's a link to NumPy's open source repository on GitHub.

Instacart, Zalando, and Thumbtack are some of the popular companies that use R, whereas NumPy is used by Instacart, Suggestic, and Twilio SendGrid. R has a broader approval, being mentioned in 128 company stacks & 97 developers stacks; compared to NumPy, which is listed in 63 company stacks and 34 developer stacks.

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Pros of NumPy
Pros of R Language
  • 6
    Great for data analysis
  • 77
    Data analysis
  • 60
    Graphics and data visualization
  • 51
    Free
  • 40
    Great community
  • 36
    Flexible statistical analysis toolkit
  • 25
    Access to powerful, cutting-edge analytics
  • 24
    Easy packages setup
  • 17
    Interactive
  • 10
    R Studio IDE
  • 9
    Hacky
  • 5
    Preferred Medium
  • 4
    Shiny interactive plots
  • 4
    Shiny apps
  • 3
    Cutting-edge machine learning straight from researchers
  • 3
    Automated data reports

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Cons of NumPy
Cons of R Language
    Be the first to leave a con
    • 4
      Very messy syntax
    • 2
      Tables must fit in RAM
    • 1
      Messy character encoding
    • 0
      Messy syntax for string concatenation
    • 0
      Messy syntax for array/vector combination
    • 0
      No push command for vectors/lists
    • 0
      Poor syntax for classes
    • 0
      Arrays indices start with 1

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    - No public GitHub repository available -

    What is 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.

    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.

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

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

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    Blog Posts

    Aug 28 2019 at 3:10AM

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    What are some alternatives to NumPy and R Language?
    Pandas
    Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.
    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.
    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.
    Panda
    Panda is a cloud-based platform that provides video and audio encoding infrastructure. It features lightning fast encoding, and broad support for a huge number of video and audio codecs. You can upload to Panda either from your own web application using our REST API, or by utilizing our easy to use web interface.<br>
    TensorFlow
    TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
    See all alternatives
    How developers use NumPy and R Language
    benyomin uses
    R Language

    What are my other choices for a vectorized statistics language. Professor was pushing SAS Jump (or was that SPSS) with a menu-driven point and click approach. (Reproducibility can still be accomplished, you publish the script generated by all your clicks.) But I want to type everything, great online tutorials for R. I think I made the right pick.

    Ralic Lo uses
    R Language

    Connect to database, data analytics, draw diagram. Machine Learning application, and also used Spark-R for big data processing.

    Vital Labs, Inc. uses
    NumPy

    We utilize NumPy, SciPy, Pandas, and iPython Notebooks to power our analysis and analytics tools.

    Tino Gehlert uses
    R Language

    Visualisation of air quality in various rooms by RShiny (hosted free on shinyapps.io)

    Sesync uses
    R Language

    R is primarily used by SESYNC's researchers

    STILLWATER SUPERCOMPUTING INC uses
    R Language

    Offline deep analytics and modeling

    GadgetSteve uses
    NumPy

    Fast Numeric Processing

    Nough You uses
    NumPy

    Fast array operations.

    BobStein uses
    NumPy

    big data analysis

    Andrea Catalucci uses
    NumPy

    Number crunching