I have two dataframes that have three variables each: location_id
, latitude
and longitude
. For every location_id
in the first data frame, I have to find the closest location_id
in the second dataframe, in addition to the distance between the location_id
from each df.
I've tried using expand.grid
to give me every possible combination of the two data frames together (worked), but then when I tried to merge the latitude and longitudes from the original lists onto my super list, I ran out of memory (there are 7000 location_ids in the first dataframe and 5000 location_ids
in the second data frame).
I was able to get the equation to calculate the distance between two points from elsewhere on stack overflow:
earth.dist <- function (long1, lat1, long2, lat2)
{
rad <- pi/180
a1 <- lat1 * rad
a2 <- long1 * rad
b1 <- lat2 * rad
b2 <- long2 * rad
dlon <- b2 - a2
dlat <- b1 - a1
a <- (sin(dlat/2))^2 + cos(a1) * cos(b1) * (sin(dlon/2))^2
c <- 2 * atan2(sqrt(a), sqrt(1 - a))
R <- 6378.145
d <- R * c
return(d)
}
but I'm having a hard time applying it in the context of this problem. Any help is appreciated!
EDIT:
The sets of data look exactly like this:
location_id LATITUDE LONGITUDE
211099 32.40913 -99.78064
333547 32.45192 -100.39325
369561 32.47458 -99.69176
123141 33.68169 -96.60887
386913 33.99921 -96.40743
123331 31.96173 -83.75830
This might help you. It's not the most elegant answer but for a data.frame for your size this should do the job fairly well.
require(geosphere)
require(dplyr)
DB1 <- data.frame(location_id=1:7000,LATITUDE=runif(7000,min = -90,max = 90),LONGITUDE=runif(7000,min = -180,max = 180))
DB2 <- data.frame(location_id=7001:12000,LATITUDE=runif(5000,min = -90,max = 90),LONGITUDE=runif(5000,min = -180,max = 180))
DistFun <- function(ID){
TMP <- DB1[DB1$location_id==ID,]
TMP1 <- distGeo(TMP[,3:2],DB2[,3:2])
TMP2 <- data.frame(DB1ID=ID,DB2ID=DB2[which.min(TMP1),1],DistanceBetween=min(TMP1) )
print(ID)
return(TMP2)
}
DistanceMatrix <- rbind_all(lapply(DB1$location_id, DistFun))
head(DistanceMatrix)
Source: local data frame [6 x 3]
DB1ID DB2ID DistanceBetween
1 1 9386 24907.35
2 2 11823 264295.86
3 3 9118 12677.62
4 4 11212 237730.78
5 5 11203 26775.01
6 6 7607 83904.84
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