5NG - Five Named Graphs

Scatterplots and overplotting

Consider the data set evals from the moderndive package. First load both tidyverse and moderndive.

Code

library(tidyverse)
library(moderndive)

What is evals measuring?

Code

?evals

The data are gathered from end of semester student evaluations for a sample of 463 courses taught by 94 professors from the University of Texas at Austin. In addition, six students rate the professors’ physical appearance. The result is a data frame where each row contains a different course and each column has information on either the course or the professor.

Create a scatterplot of score versus bty_avg

I can’t wait to see the code

ggplot(data = evals, aes(x = bty_avg, y = score)) + 
  labs(x = "Teacher's average beauty score", 
       y = "Teacher's average course evaluation") -> p1
p1 +geom_point() 

Let’s look at a few ways to fix some of the over plotting.

1. Use a different geom (geom_jitter).
2. Use alpha
3. Use geom_count() or stat_sum()

Show the code

p1 + geom_jitter()

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p1 + geom_point(alpha = .25)

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p1 + geom_count()

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p1 + stat_sum()

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p1 + geom_count(alpha = .25)

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p1 + geom_count(alpha = 0.25) + scale_size(range = c(1, 10))

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p1 + stat_sum(alpha = 0.25, aes(size = after_stat(prop)))

Code

p1 + 
  geom_count(alpha = 0.25, aes(color = gender)) + 
  scale_size(range = c(1, 10)) +
  geom_smooth(aes(color = gender), method = "loess", se = FALSE) + 
  labs(color = "Sex") + 
  scale_color_manual(values = c("female" = "pink", "male" = "darkblue")) + 
  theme_classic()

Consider the early_january_weather from the moderndive package.

origin	year	month	day	hour	temp	dewp	humid	wind_dir	wind_speed	wind_gust	precip	pressure	visib	time_hour
EWR	2013	1	1	1	39.02	26.06	59.37	270	10.35702	NA	0	1012.0	10	2013-01-01 01:00:00
EWR	2013	1	1	2	39.02	26.96	61.63	250	8.05546	NA	0	1012.3	10	2013-01-01 02:00:00
EWR	2013	1	1	3	39.02	28.04	64.43	240	11.50780	NA	0	1012.5	10	2013-01-01 03:00:00
EWR	2013	1	1	4	39.92	28.04	62.21	250	12.65858	NA	0	1012.2	10	2013-01-01 04:00:00
EWR	2013	1	1	5	39.02	28.04	64.43	260	12.65858	NA	0	1011.9	10	2013-01-01 05:00:00
EWR	2013	1	1	6	37.94	28.04	67.21	240	11.50780	NA	0	1012.4	10	2013-01-01 06:00:00

Linegraphs via geom_line()

Code

ggplot(data = early_january_weather, aes(x = time_hour, y = temp)) + 
  geom_point(size = 0.2, color = "blue") + 
  geom_line(color = "pink") + 
  labs(x = "Date and time",
       y = "Temperature (in Fahrenheit)")

Histograms via geom_histogram()

Code

library(palmerpenguins)
penguins |> 
  ggplot(aes(x = bill_length_mm)) + 
  geom_histogram() + 
  labs(x = "Penguin bill length (in mm)")

Code

penguins |> 
  ggplot(aes(x = bill_length_mm)) + 
  geom_histogram(binwidth = 3, color = "black", fill = "lightblue") + 
  labs(x = "Penguin bill length (in mm)")

Code

penguins |> 
  ggplot(aes(x = bill_length_mm, fill = species)) + 
  geom_histogram(binwidth = 3) +
  labs(x = "Penguin bill length (in mm)")

Code

penguins |> 
  ggplot(aes(x = bill_length_mm, fill = species)) + 
  geom_histogram(binwidth = 3, color = "black") +
  facet_wrap(vars(species), ncol = 1) + 
  theme_bw() + 
  labs(x = "Penguin bill length (in mm)",
       fill = "Species")

Boxplots via geom_boxplot()

Code

penguins |> 
  ggplot(aes(x = species, y = bill_length_mm, fill = species)) + 
  geom_boxplot() + 
  labs(y = "Penguin bill length (in mm)")

Code

# Note that the legend is not needed
penguins |> 
  ggplot(aes(x = species, y = bill_length_mm, fill = species)) + 
  geom_boxplot() + 
  guides(fill = "none") + 
  labs(y = "Penguin bill length (in mm)",
       x = "")

Barplots

• geom_bar()

Code

penguins |> 
  ggplot(aes(x = species)) +
  geom_bar() + 
  labs(x = "")

Code

#
penguins |> 
  ggplot(aes(x = species, fill = species)) +
  geom_bar() + 
  guides(fill = "none") + 
  labs(x = "")