This is a companion discussion topic for the original entry at:
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.
Slides: The lesser known stars of the tidyverse](https://github.com/robinsones/rstudio-conf-2018-talk)
Website: Emily Robinson
Emily Robinson - Data Analyst
Emily is a data analyst at Etsy with strong background in statistics and the social sciences. She’s experienced in data modeling, analysis, visualization, online experimentation, and reporting in R and Python. On her data science blog, robinsones.github.io, she’s covered topics ranging from managing the business challenges in data science to conference recaps to giving your first data science talk.