One Pager Cheat Sheet

• R and Python both offer great capabilities for machine learning projects, but have different syntax, libraries, and community support.
• R is a statistical language and environment while Python is a general purpose programming language.
• R and Python both provide a variety of libraries for data collection, data wrangling/exploration, and data visualization.
• R offers ggplot2 for more complex graphical representations, whereas Python relies on Matplotlib and Seaborn for basic and more advanced visualizations, respectively.
• R is generally considered to be less readable and accessible than Python due to its complex syntax and low-level programming language abstractions.
• Python is regarded as easier to read and pick up than R due to its emphasis on code readability.
• Python and R are both open source, however Python is generally considered easier to read and learn with a growing number of libraries for data analysis while R has more packages available devoted to analytics but can run slowly due to data storage.
• The software code of open source programming languages like R and Python can be freely used, modified, and distributed without any restriction, encouraging collaboration and enabling commercial and research applications.
• It really depends on yourML project, but generally speaking, R is best for heavily statistics-based projects, while Python is better for larger-scale, production-ready projects.