Minimum Distance between lat long across multiple data frames

Question

I have a data frame named A which has lat and long in separate columns. Sample Data

ID   Lat          Long    
a          10.773046   76.6392061   
b          10         


        

Answer 1

Here is a solution using the geosphere library, which calculates the distance in meters (the script does convert to km). If you dataset is a reasonable size (ie < 50,000) performance is acceptable.

a <- data.frame(ID = c("a", "b", "c", "d"),    Lat = c(10.773046, 10.7751978, 12.954027, 12.9608638), 
                Long = c(76.6392061, 76.6392061, 78.988818, 77.521573))    


b <- data.frame(Store = c("a", "b", "c", "d", "e"), Lat = c(21.244769,  9.919337, 10.053961, 13.829922, 23.849729), 
                Long = c(81.63861, 78.14844, 76.32757, 77.49369, 77.93647))

library(geosphere)

#calculate the distance matrix
distmatrix<-distm(a[, c(3, 2)], b[,c(3, 2)])
#find closest column and get distance
closest<-apply(distmatrix, 1, which.min)
a$store<-as.character(b$Store[closest])
a$distance<-apply(distmatrix, 1, min)/1000
a

  ID      Lat     Long store  distance
1  a 10.77305 76.63921     c  86.54914
2  b 10.77520 76.63921     c  86.76789
3  c 12.95403 78.98882     d 188.71751
4  d 12.96086 77.52157     d  96.19473

Solution is based on a similar question: Is there an efficient way to group nearby locations based on longitude and latitude?