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@graebnerc
Created April 9, 2022 06:18
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Creating the descriptive violin plot for the beer data set, as used in the session on linear regression.
library(ggplot2)
library(tidyr)
library(dplyr)
library(DataScienceExercises) # https://github.com/graebnerc/DataScienceExercises/
beer_data <- DataScienceExercises::beer
# Original source: http://www.principlesofeconometrics.com/poe4/poe4stata.htm
beer_data_plot <- beer_data %>%
pivot_longer(
cols = everything(),
names_to = "variable",
values_to = "value") %>%
ggplot(
data = .,
aes(x=variable, y=value, fill=variable)
) +
geom_violin(# To draw a violin plot
draw_quantiles = c(0.25, 0.5, 0.75), # Show quantiles
alpha=0.5 # Transparency
) +
geom_jitter(# To draw non-overlapping points
alpha=0.5, size=0.5 # Transparency and smaller size
) +
scale_fill_brewer(palette = "Dark2") +
facet_wrap(~variable, # To get different sub-plots for each variable
ncol = 5, # Five columns
scales = "free" # Scales adjusted to each variable
) +
theme_icae() +
theme(
axis.title = element_blank(),
strip.text = element_blank(),
legend.position = "none")
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