This page is principally for me to save the links that I intend to come back to time and time again. However, anyone is welcome to take a look at what I have collected. I have listed below some data science resources, followed by R-specific and Python-specific resources.

Data Science


I have absolutely enjoyed working in R. The libraries ggplot2, dplyr, htmltools, and d3 integrations make developing data-viz in R an exciting experience. At the R console raw data can be transformed in moments into rich visualizations, and this always makes R exciting for me.


Python is ubiquitous, writing Python feels natural, and its community has written packages for anything and everything. The quality of reproducible research enabled by Jupyter notebooks and the speed of Python in parallel makes Python a powerful skill to have in one’s pocket. Increased access to such incredibly performant tools like Python is always creating new opportunites for more subtle and more computationally intensive projects.