1+2
## [1] 3
library(tidyverse)
mpg
## # A tibble: 234 × 11
##    manufacturer model      displ  year   cyl trans drv     cty   hwy fl    class
##    <chr>        <chr>      <dbl> <int> <int> <chr> <chr> <int> <int> <chr> <chr>
##  1 audi         a4           1.8  1999     4 auto… f        18    29 p     comp…
##  2 audi         a4           1.8  1999     4 manu… f        21    29 p     comp…
##  3 audi         a4           2    2008     4 manu… f        20    31 p     comp…
##  4 audi         a4           2    2008     4 auto… f        21    30 p     comp…
##  5 audi         a4           2.8  1999     6 auto… f        16    26 p     comp…
##  6 audi         a4           2.8  1999     6 manu… f        18    26 p     comp…
##  7 audi         a4           3.1  2008     6 auto… f        18    27 p     comp…
##  8 audi         a4 quattro   1.8  1999     4 manu… 4        18    26 p     comp…
##  9 audi         a4 quattro   1.8  1999     4 auto… 4        16    25 p     comp…
## 10 audi         a4 quattro   2    2008     4 manu… 4        20    28 p     comp…
## # ℹ 224 more rows
ggplot(data= mpg) +
    geom_point(mapping = aes(x = displ, y = hwy, color = class))
How to get help
ggplot(data= mpg) +
    geom_point(mapping = aes(x = displ, y = hwy, color = class)) + facet_wrap(~class, nrow = 2)
different visual object to represent data
ggplot(data= mpg) +
    geom_point(mapping = aes(x = displ, y = hwy))
ggplot(data= mpg) +
    geom_smooth(mapping = aes(x = displ, y = hwy))
not every aesthetic works with every geom
two geoms in the same graph!
ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) + 
    geom_point(mapping = aes(color = class)) +
    geom_smooth()
local vs. global mappings This makes it possible to display different aesthetics in different layers.
specify different data for each layer
adjustments for bar charts
ggplot(data = diamonds) +
    geom_bar(mapping = aes(x = cut, fill = clarity), position = "dodge")
adjustments for scatterplots
switch x and y
set the aspect ratio correctly for maps
Polar coordinates reveal an interesting connection between a bar chart and a Coxcomb chart.
ggplot(data = diamonds) +
    geom_bar(mapping = aes(x = cut, fill = cut)) + 
    coord_polar()
The grammar of graphics is based on the insight that you can uniquely describe any plot as a combination of: