Using "flights" data from nycflights$13$ package:

$1.$ Use the flights data frame to determine the average delay for each destination. Add a column called avg$\_$delay to the airports data frame and put the calculated averages for each airport into this column.

$2.$ The statements below join two data frames, and plots the airport location on a map of the United States. Use the averages you calculated to control the sizes of the points plotted on this map $($i$.$e$.,$ larger dots for higher delay average$).$

air$\_$flights semi$\_$join$($airports$,$ flights, c$("$faa$"=$ "dest"$))$

ggplot$($air$\_$flights, aes$($lon$,$ lat$))+$

borders$("$state$")+$

geom$\_$point$()+$

coord$\_$quickmap$()$

#$3.$ Determine the $48$ hour period that had the worst delays. Cross$-$reference this time with the weather data frame using appropriate join functions and identify any relationships or patterns.