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There are around 12000 packages available in CRAN (open-source repository). R has now one of the richest ecosystems to perform data analysis. RĪcademics and statisticians have developed R over two decades. R, however, is built by statisticians and encompasses their specific language. Python is a general-purpose language with a readable syntax. R and Python requires a time-investment, and such luxury is not available for everyone. Learning both of them is, of course, the ideal solution. R and Python are state of the art in terms of programming language oriented towards data science. R is mainly used for statistical analysis while Python provides a more general approach to data science.
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New libraries or tools are added continuously to their respective catalog. R and Python are both open-source programming languages with a large community. In this R vs Python tutorial, you will learn: R consists various packages and libraries like tidyverse, ggplot2, caret, zoo whereas Python consists packages and libraries like pandas, scipy, scikit-learn, TensorFlow, caret.R can be used on the R Studio IDE while Python can be used on Spyder and Ipython Notebook IDEs.
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