1. Mark the locations of NTU Libraries
2. Find out the nearest library

(Note that I use random numbers to represent the user's choice) I created a dataframe with information of NTU libraries and the user's current location. Then I use leaflet to display the locations up to the user's choice.

Here, I construct a for loop to calculate the distance to every library from the user's location. Since the original data are in unit of degree, I transform the unit to meter by multiplying the factor (36788000/360)

i=1L
dist = data.frame(Library_Name = c("LWN","BUS","CHN"), Distance_to_Library=c(0,0,0))
points = data.frame(name = c("LWN","BUS","CHN","USER"),
                              lat = c(1.347488,1.346730,1.343671,input_userX),
                              lng = c(103.680936,103.679081,103.682313,input_userY),
                              popup = c("Lee Wee Nam Library","Business Library","Chinese Library","Current Location"),
                              size = c(5,5,5,10))
for (i in 1:3){
        a = 36788000/360*sqrt((input_userX-points$lat[i])^2+(input_userY-points$lng[i])^2)
        dist[i,2] = a
}
dist

##   Library_Name Distance_to_Library
## 1          LWN            504.3989
## 2          BUS            704.3814
## 3          CHN            580.5719