While most R programmers have heard of ggplot2 and dplyr, many are unfamiliar with the breath of the Tidyverse and the variety of problems it can solve. In this talk, we will give a brief introduction to the concept of the Tidyverse and then describe three packages and how they can be used to write a short, reproducible report. The first package is forcats, designed for making working with categorical variables easier; the second is glue, for programmatically combining data and strings; and the third package is tibble, an alternative to data.frames. We will cover their basic functions so that, at the end of the talk, we will be able to use and learn more about the broader Tidyverse.
I work at DataCamp as a Data Scientist on the growth team. Previously, I was a Data Analyst at Etsy working with their search team to design, implement, and analyze experiments on the ranking algorithm, UI changes, and new features. In summer 2016, I completed Metis’s three-month, full-time Data Science Bootcamp, where I did several data science projects, ranging from using random forests to predict successful projects on DonorsChoose.org to building an application in R Shiny that helps data science freelancers find their best-fit jobs. Before Metis, I graduated from INSEAD with a Master’s degree in Management (specialization in Organizational Behavior). I also earned my bachelor’s degree from Rice University in Decision Sciences, an interdisciplinary major I designed that focused on understanding how people behave and make decisions.