Cargamos la BD “iris”

data("iris")
head(iris)
##   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1          5.1         3.5          1.4         0.2  setosa
## 2          4.9         3.0          1.4         0.2  setosa
## 3          4.7         3.2          1.3         0.2  setosa
## 4          4.6         3.1          1.5         0.2  setosa
## 5          5.0         3.6          1.4         0.2  setosa
## 6          5.4         3.9          1.7         0.4  setosa
require(ggplot2) 
## Loading required package: ggplot2
require(plotly)
## Loading required package: plotly
## 
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
## 
##     last_plot
## The following object is masked from 'package:stats':
## 
##     filter
## The following object is masked from 'package:graphics':
## 
##     layout

##Gráfico número 1:

g1=ggplot(data = iris,aes(x=Sepal.Length))
g1+geom_histogram()+theme_minimal()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

##Gráfico número 2:

g2=ggplot(data=iris, aes(x=Sepal.Length, y=Sepal.Width))
g2+geom_point()

##Gráfico número 3:

g3=ggplot(data=iris,aes(x=Sepal.Length, y=Sepal.Width,color=Species))
g3+geom_point()

##Gráfico número 4:

g4=ggplot(data=iris,aes(x=Sepal.Length, y=Sepal.Width,color=Species))
g5=g4+geom_point()+theme_minimal()+geom_smooth(method = "gam")
ggplotly(g5)
## `geom_smooth()` using formula 'y ~ s(x, bs = "cs")'

##Gráfico número 5:

p6=ggplot(data=iris,aes(x=Species, y=Sepal.Length,fill=Species))
p7=p6+geom_boxplot()
ggplotly(p7)