###the objective off this notebook is to show this table as a plot using basic commands of R
dates <-data.frame(
birdsp=c("sparrow","kingfisher","eagle","hummingbird","sparrow","kingfisher","eagle","hummingbird","sparrow","kingfisher","eagle","hummingbird"),
wings_pan =c(22,26,195,8,24,23,201,9,21,25,185,9)
)
dates
##use the function mean() to calculate the wingspan for each bird specie
sparrow <- mean(22,24,21)
kingfisher <- mean(26,23,25)
eagle <- mean(195,201,185)
hummingbird <- mean(8,9,9)
##chain these four objects in a vector
wingspan<- c(sparrow,kingfisher,eagle,hummingbird)
##create a vector with the species name
bird_sp <-c("sparrow","kingfisher","eagle","hummingbird")
to plot bird_sp, this object should be a factor, letโs do it
bird_sp<-as.factor(bird_sp)
##the next step is create a dataframe using the vectors bird_sp and wingspan
wings<-data.frame(bird_sp,wingspan)
##the last step is plot the barplot
barplot(wings$wingspan, names.arg = wings$bird_sp,xlab = "Bird species",ylab ="Average wingspan (cm)",ylim = c(0, 200),col ="gold")

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