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R you ready for Python?

1 Preface

R is the choice of language for many statisticians. While R supports a comprehensive range of statistical tools in diverse disciplines, we recognise the extensive development of Python in recent times, particularly in the data science world of machine learning and deep learning.

Both R and Python users may embrace both languages and enhance their productivity by leveraging the best of both worlds. Using bite-sized simple R and Python scripts, the website highlights similarities and differences between these two programming environments – its syntax, semantics, and implementation framework. It demonstrates how understanding these basic and subtle concepts could benefit the efficient usage of both programming languages.

A broad outline of the materials is given here:

  • Section 1: An overview of both languages and introduce objects like vector, matrix, array, list, dictionary, and data frame.

  • Section 2: Essential data manipulation functionalities covering the R data.frame and Python pandas library.

  • Section 3: Plotting functionalities using well-known libraries in both languages, such as ggplot2, matplotlib, plotnine and seaborn.

  • Section 4: Implementation of standard statistical models; the framework of the scikit-learn library in Python and the principles of training and evaluating machine-learning models.