Slides and readings

1 Introduction 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

• 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 (required)

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

4 Read and writing data

• Slides

• readr/tidyr cheat sheet

• Readings and actively work examples in chapters

  • Data import
  • website readr
  • website tidyr
  • website openxlsx
  • website writexl

5 Data manipulation / descriptive analysis II

• Slides

• Readings and actively work examples in chapters

  • Basic statistical terms
  • Normal distribution
  • Data wrangling 3.1-3.6
  • Descriptive statistics and data manipulation 4.3-4.3.6

6 Data manipulation / joining data

• Slides

7 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
• 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 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

• 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

9 Data visualization / storytelling

This topic is largely based on slides 73-108 of Thomas Lin Pedersen’s, excellent webinar “Plotting Anything with ggplot2”. With his permission, I divided up the video into shorter parts. His videos are here and here

• pdf of slides

  • gganimiate cheat sheet
    
  • website gganimate
  • website ggforce
  • website ggrepel

• Rmarkdown for slides 73-108

• website tidyquant

• Videos

  • animation using gganimate, slides 73-77
  • annotation using ggrepel and ggforce, slides 78-82
  • networks using ggraph, slides 83-86
  • theme extensions, draw anything, inspiration, slides 87-108
  • tidyquant example
    • Timeline of the COVID-19 pandemic in the United States

10 Introduction to machine learning

• Differences supervised vs unsupervised machine learning
  • Read Ch 1 Introduction to Machine Learning
• Complete Chapter 1 of Supervised Machine Learning Case Studies in R

11 Create and publish a website

• blogdown: Creating Websites with R Markdown
  • 1.3 in RStudio IDE
• website in demo videos
  • How to make the resume
    
• final website

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