To do yourself

• O’Donoghue, Sen I., Benedetta Frida Baldi, Susan J. Clark, Aaron E. Darling, James M. Hogan, Sandeep Kaur, Lena Maier-Hein, et al. “Visualization of Biomedical Data.” Annual Review of Biomedical Data Science 1, no. 1 (July 20, 2018) - Visualization best practices (the use of length, area, color etc.)

• RStudio Webinars - Code and slides for RStudio webinars

• ggplot2 tutorial/slides/code examples/references by Jenny Bryan

• The R Graph Gallery, all graphs with code

• Collection of ggplot2 materials

• A Gentle Guide to the Grammar of Graphics with ggplot2 by Garrick Aden-Buie

• Plotting/reporting best practices

To submit on Canvas

Create RMarkdown document with headers, text, and code to answer/visualize questions. Submit both Rmd and knitted PDF. Pay attention to code clarity, variable names, comments.

• Get names of all packages installed on your computer, check the installed.packages() function. Split package names into characters. Calculate frequency of each letter, case sensitive. Create a horizontal barplot, Y-axis - letters/characters, X-axis - frequency. Make it sorted, so the most frequently occurring letters (highest bars) are on top. Color each bar by its own color. Do not output legend.

• Download the CDC US Birth dataset from https://github.com/fivethirtyeight/data/tree/master/births. Answer the following questions:

  • Make barplots of most-to-least popular a) day of week, b) day of month, c) month to give birth, irrespectively of year. X-axis - date, Y-axis - number of births. Color by date
  • Visually demonstrate the total birth trend over the years. X-axis - years, Y-axis - total number of births per year.
  • For each a) day of week, b) day of month, c) month, collect the number of births, irrespectively of year. Plot them as a) scatterplots, b) boxplots, with X-axis being the corresponding data (days of week, month, etc.) and Y-axis - the number of births. For scatterplots, fit a smoothing line with the default nonlinear fit. Color by date.
  • Bonus question: Make the time series curve similar to the second plot of the accompanying article.