In this lab we will be working with data from $2016-23$ of the Portland Thorns, a highlysuccessful National Women$$s Soccer League $($NWSL$)$ team located in Portland, OR$.$ Our goalsinclude$$visualizing categorical data$$investigating associations between categorical data$$investigating associations with numerical dataWe will also see some new ways of working with data with R$\mathrm{.}1$ Packages and Data$$There$$s nothing in this section that you actually need to do $$ just read through tomake sure you understand what$$s happening.Thetidyversepackage includes many of the R commands we need to work with data.library$($tidyverse$)$The data for this lab was sourced from thenwslRpackage on Github. The code below readsthis data from a csv file and then assigns the namethornsto the dataset.thorns$<-$read$\_$csv$("$thorns$.$csv$")$Thethornsdataset has $197$ rows and $9$ variables. The observations are all the Thorns gamesup through the $2013$ season. The variables are as follows:$1$

Variable Descriptongame$\_$idAn unique ID for the gamegame$\_$dateGame datehome$\_$teamName of the home team, abbreviatedaway$\_$teamName of the away team, abbreviatedopponentThe team Thorns played againsthome$\_$ptsNumber of points by the home teamaway$\_$ptsNumber of points by the away teamresultResult of the game for Thorns $($win$,$ loss, tie$)$yearSeason $(2017-2023)2$ ThornsresultsIn this section we start looking at the categorical variableresultwhich records the result$($win$,$ loss, or tie$)$ for each game.Task $1$Create a bar plot for the variableresult.Additionally, calculate the numbers of wins, losses, and ties. Hint: in previous activities, wehave used thecount$()$function to do this kind of calculation.# add code here