Put this in the Correct Format.

let$$s start by loading the necessary packages and the palmerpenguins dataset:

library$($tidyverse$)$ library$($palmerpenguins$)$

penguins$\_$data $<-$ penguins # Using sapply to identify continuous and categorical variables continuous$\_$vars $<-$ sapply$($penguins$\_$data, is$.$numeric$)$ categorical$\_$vars $<-$ sapply$($penguins$\_$data, is$.$factor$)$

Extract variable names based on the logical vectors

continuous$\_$names $<-$ names$($penguins$\_$data$)[$continuous$\_$vars$]$ categorical$\_$names $<-$ names$($penguins$\_$data$)[$categorical$\_$vars$]$

Print the identified variables

print$($Continuous Variables:$)$ print$($continuous$\_$names$)$

Means and Standard Deviations of Continuous Variables

summary$\_$stats $<-$ summarise$\_$if$($penguins$\_$data$[,$ c$(1$:$4,6$:$7)],$ is$.$numeric, list$($mean $=$ ~ifelse$($all$($is$.$na$(.)),$ NA$,$ mean$(.,$ na$.$rm $=$ TRUE$)),$ sd $=$ ~sd$(.,$ na$.$rm $=$ TRUE$)))$ summary$\_$stats

Means and Standard Deviations of Continuous Variables by Species

species$\_$summary $<-$ penguins$\_$data $\%>\%$ group$\_$by$($species$)\%>\%$ summarise$\_$if$($is$.$numeric, list$($mean $=$ mean, sd $=$ sd$),$ na$.$rm $=$ TRUE$)$ species$\_$summary # Five Number Summaries and IQR of Continuous Variables five$\_$num$\_$summaries $<-$ penguins$\_$data $\%>\%$ summarise$($across$($where$($is$.$numeric$),$ list$($Q$1=$ quantile, median $=$ median, Q$3=$ quantile, IQR $=$ IQR$),$ na$.$rm $=$ TRUE$))$ five$\_$num$\_$summaries # Five Number Summaries and IQR of Continuous Variables by Species library$($dplyr$)$

species$\_$five$\_$num$\_$summaries $<-$ penguins$\_$data $\%>\%$ group$\_$by$($species$)\%>\%$ summarise$($across$($where$($is$.$numeric$),$ list$($Q$1=$ ~quantile$(.,0\mathrm{.}25,$ na$.$rm $=$ TRUE$),$ median $=$ ~median$(.,$ na$.$rm $=$ TRUE$),$ Q$3=$ ~quantile$(.,0\mathrm{.}75,$ na$.$rm $=$ TRUE$),$ IQR $=$ ~IQR$(.,$ na$.$rm $=$ TRUE$))))\%>\%$ ungroup$()$

species$\_$five$\_$num$\_$summaries #Categorical Variables print$($Categorical Variables:$)$ print$($categorical$\_$names$)$

Percentages of Penguin Species

species$\_$percentages $<-$ penguins$\_$data $\%>\%$ count$($species$)\%>\%$ mutate$($percentage $=$ n $/$ sum$($n$)*100)$ species$\_$percentages #Percentages of Penguin Species by Island species$\_$island$\_$percentages $<-$ penguins$\_$data $\%>\%$ count$($species$,$ island$)\%>\%$ group$\_$by$($species$)\%>\%$ mutate$($percentage $=$ n $/$ sum$($n$)*100)$ species$\_$island$\_$percentages #Scatterplot of Body Mass and Flipper Length by Species ggplot$($penguins$\_$data, aes$($x $=$ body$\_$mass$\_$g$,$ y $=$ flipper$\_$length$\_$mm$,$ color $=$ species$))+$ geom$\_$point$()$ # Side$-$by$-$Side Boxplot of Body Mass by Species ggplot$($penguins$\_$data, aes$($x $=$ species, y $=$ body$\_$mass$\_$g$,$ fill $=$ species$))+$ geom$\_$boxplot$()$