Chapter 1 tl;dr

  • Exploratory data analysis (EDA) is the foundation for all data tasks. Do most of your EDA with just dplyr::count() and ggplot2::geom_point(). Use more ggplot functions to polish your final plot. But don’t worry about remembering all the ggplot functions and arguments, use Google. Follow three simple rules to layout your code clearly so that each line does one thing, name where each function comes from, and name all function arguments you set. Use interactive tools for EDA and presenting your final plot too (plotly, dygraphs, apexcharter, and rpivotTables). Use animation sparingly, and usually only to show change over time. Present your final plots in one of: flexdashhboards, R Markdown with a floating table of contents and tabbed sections, or a bookdown book.