Slides

Example website for BUS 320

1 Introduction to R/RStudio

Slides

• Readings

  • Introduction: Using R for Data Journalism

  • Evolve from Excel to R

  • What is R

  • Why R instead of Excel

    • The Excel mistake heard around the world
    • An Oops for Goldman Sachs in Its Advice on Vista-Tibco Merger

• Reference: R Markdown: The Definitive Guide

2 Excel to R

Slides

Links in slides

• Postcards for about page

• Readings

  • Getting to know RStudio
  • Objects, types and useful R functions to get started

3 Data manipulation / descriptive analysis I

Slides

• dplyr cheat sheet

• Readings and actively work examples in chapters

  • Data wrangling 3.1-3.6
  • Descriptive statistics and data manipulation 4.3-4.3.6
  • Data transformation
  • package dplyr
  • package here

4 Reading and writing data

Slides

• readr

5 Data manipulation

Slides

• dplyr
• ggplot2
• scales package

6 Joining data

Slides

• dplyr
• ggplot2
• echarts4r
• hrbrthemes

7 Exploratory analysis: Data visualization I

This topic is largely based on slides 1-49 of Thomas Lin Pedersen’s, excellent webinar “Plotting Anything with ggplot2”. With his permission, I divided up the video into shorter parts. The full video is here.

• pdf of slides
• Rmarkdown for slides 1-49
  • Create a separate folder called examples and put the Rmarkdown file in it
• Videos
  • Introduction, slides 1-5
  • The grammar, slides 6-17
  • The grammar, slides 18-24
  • The ggplot2 API intro, slides 25-35
    • set dataset
    • columns for x and y map in aes()
    • draw the plot with geom_
    • use + at end of line to combine ggplot2 elements
    • map colour to variable/condition in aes()
    • set colour outside of aes()
  • ggplot2, geom layer, slides 36-38
    • many geoms - mapping requirements in aes() vary by geom. Find out about mapping requirements:?geom_*
    • layers stack on plot by order in code
  • ggplot2, stat layer, slides 39-45
    • stat_*()
    • after_stat() to modify output from default stats m apping
  • ggplot2, scale, slides 46-48
    • default colour in aes() mapping based in variable type
  • ggplot2, scale, slide 49
    • scale x, y axes

8 Exploratory analysis: Data visualization II

This topic is largely based on slides 50-72 of Thomas Lin Pedersen’s, excellent webinar “Plotting Anything with ggplot2”. With his permission, I divided up the video into shorter parts. The full video is here.

• pdf of slides

• ggplot2 cheat sheet
  

• website ggplot2

• website patchwork

• Rmarkdown for slides 50-72

• Rmarkdown for slides 1-49

  • Put the Rmarkdown file in the examples folder

• Videos

  • ggplot2, faceting, slides 50-52
    • Note: change in arguments of facet_*
      • slide 51 shows old way facet_wrap(~ class)
        • Rmarkdown shows new way facet_wrap(vars(class))
      • slide 52 shows old way facet_grid(year ~ drv)
        • Rmarkdown shows new way facet_grid(rows = vars(year), cols = vars(drv))
  • ggplot2, coordinates, slides 53-57
  • ggplot2, themes, slides 58-60
  • why ggplot2 extensions, plot composition with patchwork, slides 61-72