#Introduction
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values <- rnorm(5)
values
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Finally, we can make a nice tables.
mpg_sm <- head(mpg)
kable(mpg_sm)
manufacturer | model | displ | year | cyl | trans | drv | cty | hwy | fl | class |
---|---|---|---|---|---|---|---|---|---|---|
audi | a4 | 1.8 | 1999 | 4 | auto(l5) | f | 18 | 29 | p | compact |
audi | a4 | 1.8 | 1999 | 4 | manual(m5) | f | 21 | 29 | p | compact |
audi | a4 | 2.0 | 2008 | 4 | manual(m6) | f | 20 | 31 | p | compact |
audi | a4 | 2.0 | 2008 | 4 | auto(av) | f | 21 | 30 | p | compact |
audi | a4 | 2.8 | 1999 | 6 | auto(l5) | f | 16 | 26 | p | compact |
audi | a4 | 2.8 | 1999 | 6 | manual(m5) | f | 18 | 26 | p | compact |
theme_set(theme_bw()) # pre-set the bw theme.
g <- ggplot(mpg, aes(cty, hwy))
g + geom_jitter(width = .5, size=1) + labs(subtitle="mpg: city vs highway mileage",
y="hwy",
x="cty",
title="Jittered Points")
footnotes↩︎