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Groovy vs R: What are the differences?
What is Groovy? A dynamic language for the Java platform. Groovy builds upon the strengths of Java but has additional power features inspired by languages like Python, Ruby and Smalltalk. It makes modern programming features available to Java developers with almost-zero learning curve.
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.
Groovy and R can be primarily classified as "Languages" tools.
"Java platform" is the top reason why over 38 developers like Groovy, while over 58 developers mention "Data analysis " as the leading cause for choosing R.
Groovy is an open source tool with 1.49K GitHub stars and 414 GitHub forks. Here's a link to Groovy's open source repository on GitHub.
According to the StackShare community, R has a broader approval, being mentioned in 128 company stacks & 97 developers stacks; compared to Groovy, which is listed in 79 company stacks and 73 developer stacks.
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.
Pros of R Language
- Data analysis84
- Graphics and data visualization63
- Free54
- Great community45
- Flexible statistical analysis toolkit38
- Easy packages setup27
- Access to powerful, cutting-edge analytics27
- Interactive18
- R Studio IDE13
- Hacky9
- Shiny apps7
- Shiny interactive plots6
- Preferred Medium6
- Automated data reports5
- Cutting-edge machine learning straight from researchers4
- Machine Learning3
- Graphical visualization2
- Flexible Syntax1
Cons of R Language
- Very messy syntax6
- Tables must fit in RAM4
- Arrays indices start with 13
- Messy syntax for string concatenation2
- No push command for vectors/lists2
- Messy character encoding1
- Poor syntax for classes0
- Messy syntax for array/vector combination0
What is R Language?
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What tools integrate with R Language?
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