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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What is NumPy?
What is R Language?
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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.
Connect to database, data analytics, draw diagram. Machine Learning application, and also used Spark-R for big data processing.
We utilize NumPy, SciPy, Pandas, and iPython Notebooks to power our analysis and analytics tools.
Visualisation of air quality in various rooms by RShiny (hosted free on shinyapps.io)