install.packages("ggplot2")
## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.4'
## (as 'lib' is unspecified)
data("iris")
summary(iris)
##   Sepal.Length    Sepal.Width     Petal.Length    Petal.Width   
##  Min.   :4.300   Min.   :2.000   Min.   :1.000   Min.   :0.100  
##  1st Qu.:5.100   1st Qu.:2.800   1st Qu.:1.600   1st Qu.:0.300  
##  Median :5.800   Median :3.000   Median :4.350   Median :1.300  
##  Mean   :5.843   Mean   :3.057   Mean   :3.758   Mean   :1.199  
##  3rd Qu.:6.400   3rd Qu.:3.300   3rd Qu.:5.100   3rd Qu.:1.800  
##  Max.   :7.900   Max.   :4.400   Max.   :6.900   Max.   :2.500  
##        Species  
##  setosa    :50  
##  versicolor:50  
##  virginica :50  
##                 
##                 
##

Graficos cuantitativos

en la siguiente figura se observa el histograma de la variable longitud del sepalo

library(ggplot2)
ggplot(iris, aes(x=Sepal.Length))+
  geom_histogram(fill="deeppink")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

ggplot(iris, aes(x=Sepal.Width))+
  geom_histogram(fill="deeppink4")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

ggplot(iris, aes(x=Petal.Length))+
  geom_histogram(fill="pink")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

ggplot(iris, aes(x=Petal.Width))+
  geom_histogram(fill="deeppink")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Diagrama de caja

a continuación se presenta los diagramas de cajas

ggplot(iris, aes(y=Sepal.Length))+
  geom_boxplot(fill="orange")

ggplot(iris, aes(y=Sepal.Width))+
  geom_boxplot(fill="yellow")

ggplot(iris, aes(y=Petal.Length))+
  geom_boxplot(fill="orangered")

ggplot(iris, aes(y=Sepal.Length))+
  geom_boxplot(fill="gold")

Diagramas de cajas por grupo

ggplot(iris, aes(y=Sepal.Length, x=Species, fill=Species))+
  geom_boxplot()

ggplot(iris, aes(y=Sepal.Width, x=Species, fill=Species))+
  geom_boxplot()

ggplot(iris, aes(y=Petal.Length, x=Species, fill=Species))+
  geom_boxplot()

ggplot(iris, aes(y=Petal.Length ,x=Species, fill=Species))+
  geom_boxplot()

Conclusiones

*Se observa que la especie Virginia presenta características más grandes y las setotas más pequeña

*la especie setosa presneta daatos más datos atipicos

Imagen