In the world of ‘Data Science’ there has been a simmering debate over the advantages of R and Python. Ultimately, this debate is futile. Each language has the tools needed to produce high quality data analysis. Hoping to expand and complement my existing tool kit I’ve spent the last couple of months learning Python. The bulk of my learning has been through Coursera’s Python For Everybody Specialization. Developed by Dr. Charles Severance at the University of Michigan, the material is presented with dynamic and detailed lectures.
Last Week I had the pleasure to attend a talk given by Hadley Wickham to the Statistical Programming DC Meetup. It was great to have Hadley speak to the group about developing fluent interfaces for R. While the talk was aimed at using Pure, Predictable and Pipeable functions to do software (package) development, these ideas can also be applied to data analysis to create more readable code. In both software development and data analysis, it is important to create code that is easy to read for collaboration and reproducibility.
Welcome to Let’s Ask The Data. I have launched my first website/blog in an endeavour to share my experience and learning with others doing similar work in the Data Science and/or Applied Statistic community. I’m plan to use it as a place to document my adventures exploring and practising new methods or showcase projects with cool data sets. In doing so, I hope that others doing similar work can learn from my blog.