verify that you actually have five-digit zip codes stored as
characters. New Jersey and Massachusetts have zero as
the first digit. When these codes are saved as numbers, they become
four-digit codes and will probably cause errors.
For example Cambridge, Mass is '02138', and would be reported as 2138
when interpreted as a number..
On Tue, Aug 4, 2020 at 9:29 PM Debasmita Sur <ds071...@gmail.com> wrote:
>
> Dear R-experts,
> I have two lists of US zip codes and want to pick the nearest zip code from
> second list against my first list.e.g.30043 (from second list) is closest
> to the zip code 30094 (from first list).So,it should come against 30094.The
> code should compare the distance from each zip and pick the nearest one.
> I have written the following code. It is giving proper results for many,
> but in mindist, it is showing 'NAs'. But for some of the zip codes, it is
> giving proper minimum distance. Please note it will be effective for 5
> digit zip codes. Any help will be highly appreciated.
>
> df1<-read.csv("C:/Users/dxsur/Desktop/ZIP1.csv")
> df2<-read.csv("C:/Users/dxsur/Desktop/ZIP2.csv")
>
> results<-merge(x=df1,y=zipcode,all.x=TRUE)
> results1<-merge(x=df2,y=zipcode,all.x=TRUE)
> distance<-distm(subset(results,select=c(longitude,latitude)),subset(results1,select=c(longitude,latitude)))
>
> rnum=apply(distance, 1, which.min)
> mindist=apply(distance, 1, min)
>
> final<-cbind(results,results1$zip[unlist(rnum)],mindist)
>
>
> Thanks & Regards,
> *Debasmita *
>
> [[alternative HTML version deleted]]
>
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