Data Visualization

STAT 20: Introduction to Probability and Statistics

Warmup Questions

Equivalent or Different commands?

Are the following commands equivalent (i.e. give you the same plot)?

Are the following commands equivalent (i.e. give you the same plot)?

# command 1.1
ggplot(iris, aes(x = Petal.Length, y = Petal.Width, color = Species)) +
  geom_point()

# command 1.2
ggplot(iris, aes(x = Petal.Length, y = Petal.Width)) +
  geom_point(aes(color = Species))

• Yes, they are equivalent.
• color mapping can be specified at the ggplot() level or at the geom_point() level

Are the following commands equivalent (i.e. give you the same plot)?

# command 2.1
ggplot(iris, aes(Petal.Length, Petal.Width)) +
  geom_point(color = "blue")

# command 2.2
ggplot(iris, aes(Petal.Length, Petal.Width, color = "blue")) +
  geom_point()

• No, they are different.
• color = "blue" is a setting
• aes(..., color = "blue") is mapping a string "blue" to color.

Are the following commands equivalent (i.e. give you the same plot)?

# command 3.1
ggplot(iris, aes(Petal.Length, Petal.Width)) +
  geom_point()

# command 3.2
ggplot(iris) +
  geom_point(aes(Petal.Length, Petal.Width))

• Yes, they are equivalent.
• the aesthetic mappings can be placed at the ggplot() level or at the geom_point() level.

What is the issue in these commands?

Can you spot the bug?

Can you spot the bug?

ggplot(iris) +
  geom_point(x = Petal.Width, y = Petal.Length)

the x and y mappings need to be specified inside aes()

Can you spot the bug?

ggplot(iris, aes(Petal.Length, Petal.Width))
  geom_point(aes(color = Species))

the plus sign + is missing after ggplot() and before geom_point()

Can you spot the bugs?

ggplot(iris, aes(x = Petal.Length y = Petal.Width) |>
  goem_point(aes(color = Species))

• missing comma between arguments x and y inside 1st aes()
• missing closing parenthesis of ggplot()
• cannot use pipe operator |>; must be +
• misspelled goem_point()

Agenda

• Announcements

• Review

• Worksheet

• Lab Global Temperatures

Announcements: Retake of Quiz 1

Retake of Quiz-1

• Timeslots: through Sep 25
• Content: Weeks 1-2

Review

Palmer Penguins

# A tibble: 333 × 8
   species island    bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
   <fct>   <fct>              <dbl>         <dbl>             <int>       <int>
 1 Adelie  Torgersen           39.1          18.7               181        3750
 2 Adelie  Torgersen           39.5          17.4               186        3800
 3 Adelie  Torgersen           40.3          18                 195        3250
 4 Adelie  Torgersen           36.7          19.3               193        3450
 5 Adelie  Torgersen           39.3          20.6               190        3650
 6 Adelie  Torgersen           38.9          17.8               181        3625
 7 Adelie  Torgersen           39.2          19.6               195        4675
 8 Adelie  Torgersen           41.1          17.6               182        3200
 9 Adelie  Torgersen           38.6          21.2               191        3800
10 Adelie  Torgersen           34.6          21.1               198        4400
# ℹ 323 more rows
# ℹ 2 more variables: sex <fct>, year <int>

Question: In terms of the way they are constructed …

What do these plots have in common? How do they differ?

01:30

Common:

• they are univariate visualizations
• graphics to see distribution of a continuous variable
• continuous variable in x-axis

Differences:

• the geometries
• the meaning of the y-axis scale

Question: What do these plots have in common? How do they differ?

01:30

Common:

• same geom: they are both bar charts

Differences:

• type of bar chart (stacked normalized vs standard)
• number of variables (2 vs 1)
• what’s in x-axis, what’s in y-axis

Question: What are the aesthetic mappings and geometries used here?

01:30

Mappings:

• bill_length_mm to x-axis
• flipper_length_mm to y-xias
• species to color
• sex to shape

Geoms:

• points

Analytical Tasks (by Stephen Few)

7-Core Analytical Tasks (by Stephen Few)

• Times-series analysis
• Ranking analysis
• Part-to-Whole analysis
• Deviation & Comparisons against a benchmark
• Distribution analysis
• Correlation & Regression
• Multivariate
• Other*

Your Turn: Worksheet

For each graphic below, answer the following questions:

1. What geometry/geometries are used?
2. What variable is mapped to the x-axis?
3. What variable is mapped to the y-axis?
4. Are other visual attributes used (e.g., size, shape, facets)?
5. How is color used: data-encoding or decorative?
6. How many total variables are represented in the graphic?
7. What primary analytical task(s) (Few) does the plot serve?
8. If annotations are present:
   • do they describe data points?
   • or do they highlight a specific takeaway?

Write your answers in today’s worksheet

Plot 1

Plot 2

Plot 3

Plot 4

Plot 5

Plot 6

Plot 7

Plot 8

Lab 4: Flights II (cont’d)

End of Lecture