Plotting in R: ggplot2
Introduction to ggplot2
- Author: Sarah Meister
- Lesson topic: Plotting in R using ggplot2
- Lesson content URL: https://github.com/UofTCoders/studyGroup/tree/gh-pages/lessons/ggplot2
What is ggplot2?
ggplot2 is meant to be an implementation of the Grammar of Graphics, hence gg-plot. The basic notion is that there is a grammar to the composition of graphical components in statistical graphics, and by direcly controlling that grammar, you can generate a large set of carefully constructed graphics tailored to your particular needs. Each component is added to the plot as a layer.
Components of a ggplot2 plot
Plots convey information through various aspects of their aesthetics. Some aesthetics that plots use are:
- x position
- y position
- size of elements
- shape of elements
- color of elements
The elements in a plot are geometric shapes, like
- points
- lines
- line segments
- bars
- text
Some of these geometries have their own particular aesthetics. For instance:
points
- point shape
- point size
lines
- line type
- line weight
bars
- y minimum
- y maximum
- fill color
- outline color
text
- label value
R code
library(ggplot2)
summary(mpg)
## manufacturer model displ year
## Length:234 Length:234 Min. :1.600 Min. :1999
## Class :character Class :character 1st Qu.:2.400 1st Qu.:1999
## Mode :character Mode :character Median :3.300 Median :2004
## Mean :3.472 Mean :2004
## 3rd Qu.:4.600 3rd Qu.:2008
## Max. :7.000 Max. :2008
## cyl trans drv cty
## Min. :4.000 Length:234 Length:234 Min. : 9.00
## 1st Qu.:4.000 Class :character Class :character 1st Qu.:14.00
## Median :6.000 Mode :character Mode :character Median :17.00
## Mean :5.889 Mean :16.86
## 3rd Qu.:8.000 3rd Qu.:19.00
## Max. :8.000 Max. :35.00
## hwy fl class
## Min. :12.00 Length:234 Length:234
## 1st Qu.:18.00 Class :character Class :character
## Median :24.00 Mode :character Mode :character
## Mean :23.44
## 3rd Qu.:27.00
## Max. :44.00
g <- ggplot(mpg, aes(displ, hwy))
g + geom_point()
g + geom_point() + geom_smooth(method="lm")
g + geom_point() + geom_smooth(method="lm") + facet_grid(drv~.)
g + geom_point(color="steelblue", size=4, alpha=1/2)
g + geom_point(aes(color=drv)) +
labs(title="Fuel ecomony...",
x= "Engine displ", y="highway milage") + theme_bw(base_family = "Times")
ggplot(mpg, aes(displ)) + geom_histogram(aes(color=drv)) + theme_bw()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
library(reshape2)
library(plyr)
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:plyr':
##
## arrange, count, desc, failwith, id, mutate, rename, summarise,
## summarize
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
mt <- select(mtcars, c(1,3,4,5,6,7))
mt2 <- cor(mt)
mt3 <- melt(mt2)
ggplot(mt3, aes(x=Var1, y=Var2, fill=value)) + geom_tile()
mtcars %>%
select(c(1,3,4,5,6,7)) %>%
cor() %>%
melt() %>%
ggplot(aes(x=Var1, y=Var2, color=value)) + geom_point()
