Figuras utiles ggplot2
Oscar Ramirez Alan
10 de junio de 2016
# geom_bar is designed to make it easy to create bar charts that show
# counts (or sums of weights)
library(car)
library(ggplot2)
str(mpg)## 'data.frame': 234 obs. of 11 variables:
## $ manufacturer: Factor w/ 15 levels "audi","chevrolet",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ model : Factor w/ 38 levels "4runner 4wd",..: 2 2 2 2 2 2 2 3 3 3 ...
## $ displ : num 1.8 1.8 2 2 2.8 2.8 3.1 1.8 1.8 2 ...
## $ year : int 1999 1999 2008 2008 1999 1999 2008 1999 1999 2008 ...
## $ cyl : int 4 4 4 4 6 6 6 4 4 4 ...
## $ trans : Factor w/ 10 levels "auto(av)","auto(l3)",..: 4 9 10 1 4 9 1 9 4 10 ...
## $ drv : Factor w/ 3 levels "4","f","r": 2 2 2 2 2 2 2 1 1 1 ...
## $ cty : int 18 21 20 21 16 18 18 18 16 20 ...
## $ hwy : int 29 29 31 30 26 26 27 26 25 28 ...
## $ fl : Factor w/ 5 levels "c","d","e","p",..: 4 4 4 4 4 4 4 4 4 4 ...
## $ class : Factor w/ 7 levels "2seater","compact",..: 2 2 2 2 2 2 2 2 2 2 ...head(mpg)## manufacturer model displ year cyl trans drv cty hwy fl class
## 1 audi a4 1.8 1999 4 auto(l5) f 18 29 p compact
## 2 audi a4 1.8 1999 4 manual(m5) f 21 29 p compact
## 3 audi a4 2.0 2008 4 manual(m6) f 20 31 p compact
## 4 audi a4 2.0 2008 4 auto(av) f 21 30 p compact
## 5 audi a4 2.8 1999 6 auto(l5) f 16 26 p compact
## 6 audi a4 2.8 1999 6 manual(m5) f 18 26 p compactg <- ggplot(mpg, aes(class))
g + geom_bar()
g + geom_bar(aes(weight = hwy))
df <- data.frame(trt = c("a", "b", "c"), Salida = c(5, 3, 3.2))
ggplot(df, aes(trt, Salida)) +
geom_bar(stat = "identity")
ggplot(df, aes(trt, Salida)) +
geom_point()
head(mtcars)## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
## Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
## Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
## Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1str(mtcars)## 'data.frame': 32 obs. of 11 variables:
## $ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
## $ cyl : num 6 6 4 6 8 6 8 4 4 6 ...
## $ disp: num 160 160 108 258 360 ...
## $ hp : num 110 110 93 110 175 105 245 62 95 123 ...
## $ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
## $ wt : num 2.62 2.88 2.32 3.21 3.44 ...
## $ qsec: num 16.5 17 18.6 19.4 17 ...
## $ vs : num 0 0 1 1 0 1 0 1 1 1 ...
## $ am : num 1 1 1 0 0 0 0 0 0 0 ...
## $ gear: num 4 4 4 3 3 3 3 4 4 4 ...
## $ carb: num 4 4 1 1 2 1 4 2 2 4 ...#continuous scale vs. discrete scale
head(mtcars)## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
## Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
## Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
## Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1qplot(wt, mpg, data=mtcars, colour=cyl) 
levels=(mtcars$cyl)
qplot(wt, mpg, data=mtcars, colour=factor(cyl))
# use different aesthetic mappings
qplot(wt, mpg, data=mtcars, shape=factor(cyl)) 
qplot(wt, mpg, data=mtcars, size=qsec)
combine mappings (hint: hollow points, geom-concept, legend combination)
qplot(wt, mpg, data=mtcars, size=qsec, color=factor(carb)) qplot(wt, mpg, data=mtcars, size=qsec, color=factor(carb), shape=I(1)) qplot(wt, mpg, data=mtcars, size=qsec, shape=factor(cyl), geom=“point”) qplot(wt, mpg, data=mtcars, size=factor(cyl), geom=“point”)
# bar-plot
qplot(factor(cyl), data=mtcars, geom="bar") 
# flip plot by 90??
qplot(factor(cyl), data=mtcars, geom="bar") + coord_flip()
# difference between fill/color bars
qplot(factor(cyl), data=mtcars, geom="bar", fill=factor(cyl)) 
qplot(factor(cyl), data=mtcars, geom="bar", colour=factor(cyl))
# fill by variable
qplot(factor(cyl), data=mtcars, geom="bar", fill=factor(gear))
# histogram
qplot(carat, data=diamonds, geom="histogram")## stat_bin: binwidth defaulted to range/30. Use 'binwidth = x' to adjust this.
# change binwidth
qplot(carat, data=diamonds, geom="histogram", binwidth=0.1) 
qplot(carat, data=diamonds, geom="histogram", binwidth=0.01)
# use geom to combine plots (hint: order of layers)
qplot(wt, mpg, data=mtcars, geom=c("point", "smooth"))## geom_smooth: method="auto" and size of largest group is <1000, so using loess. Use 'method = x' to change the smoothing method.
qplot(wt, mpg, data=mtcars, geom=c("smooth", "point"))## geom_smooth: method="auto" and size of largest group is <1000, so using loess. Use 'method = x' to change the smoothing method.
qplot(wt, mpg, data=mtcars, color=factor(cyl), geom=c("point", "smooth"))## geom_smooth: method="auto" and size of largest group is <1000, so using loess. Use 'method = x' to change the smoothing method.
# removing standard error
qplot(wt, mpg, data=mtcars, geom=c("point", "smooth"), se=FALSE)## geom_smooth: method="auto" and size of largest group is <1000, so using loess. Use 'method = x' to change the smoothing method.
# illustrate flip versus changing of variable allocation
qplot(mpg, wt, data=mtcars, facets=cyl~., geom=c("point", "smooth"))## geom_smooth: method="auto" and size of largest group is <1000, so using loess. Use 'method = x' to change the smoothing method.
## geom_smooth: method="auto" and size of largest group is <1000, so using loess. Use 'method = x' to change the smoothing method.
## geom_smooth: method="auto" and size of largest group is <1000, so using loess. Use 'method = x' to change the smoothing method.
qplot(factor(cyl), wt, data=mtcars, geom="boxplot") 