Week 6 Class Notes

Today’s Agenda

• Review of data verbs & summary functions with your small group
• Class discussion of new functions and key concepts
• Work in groups on Popular Names Activity
• Minute Paper

Small Group Discussion:

• Each person in the group should explain one command from each list:
  • List 1: data verbs:
    • mutate()
    • filter()
    • select()
    • arrange()
  • List 2: more data verbs:
    • head() & tail()
    • transmute()
    • rename()
    • sample_n()
    • summarise() & group_by()
  • List 3: summary functions:
    • glimpse()
    • str()
    • summary()
    • nrow() & ncol()
    • names()
    • View()

Three Important Concepts (Again)

1. As we’ve been discussing, Data can be usefully organized into tables with “cases” and “variables.”
   1. In “tidy data,” every case is the same sort of thing, e.g. a person, a car, a year, a country in a year.
   2. We sometimes even modify data in order to change what the cases represent in order to better represent a point.

2. Data graphics can be constructed easily when each case corresponds to a “glyph” (mark) on the graph, and each variable to a graphical attribute of that glyph such as x- or y-position, color, size, length, shape, etc. Such data is called “glyph-ready.” (The same is true for more technical presentations of data, e.g., models, predictions, etc. — once the data are set up with appropriate cases and variables, the presentation is straightforward.)

3. When data are not yet in glyph-ready form, you can transform them into glyph-ready form.
   1. Such transformations are accomplished by performing one or more of a small set of basic operations on data tables
   2. This is the work of data “verbs”

Activity: Popular Names (DC page 159)

Instructions:

• complete the activity as a group
• submit an HTML file with embedded .Rmd (i.e. use class template) to “Activity: Popular Names” on Canvas
• Submit one for each group by Friday at 11:59pm

Assignment is worth 10 points:

The following steps must be clearly shown in the file you submit (except white board steps) so they can be graded as follows:

• [1 point] Turn in HTML with embedded .Rmd file (e.g. “DataComputing simple” template)
• [1 point] Step 1: show how you used summary functions to explore the raw data set
• Step 2 on the white board
• [0.5 points] Step 3: attempt to answer all questions about the data
• [0.5 points] Step 4: attempt to answer all questions about the data
• [1 points] Step 5: explaination of data wrangling steps in English (not code)
• Step 6 on the white board
• [3 points] Step 7: Data wrangling
• [3 points] ggplot() graph of first names for those in your group

Homework

• Minute Paper (before leaving class today)
• Submit Activity: Popular Names on Canvas by midnight Friday
• DC Ch 7 Exercises: 7.1, 7.5, 7.6 (Note: these Chapter 7 exercises use Chapter 9 material)
  
• DC Ch 9 Exercises: 9.3
  
• DC chapter 10 reading quiz on Canvas

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