CODEWITHSUNDEEP
rdataframe
maximusdooku
maximusdooku

Reputation: 5512

How can I extract row from a second dataframe based on data-pairs from first dataframe?

I have two dataframes, df1 (2000 rows) and df2 (100,000 rows). And I want to:

How can I go about it?

df1
lat      long       val
33.29083 -109.19556 12.5000
32.96583 -109.30972 11.5000
33.04944 -109.29528 1.7500
33.06444 -109.44167 1.7500
33.61944 -110.92083 0.2500
33.98000 -111.30278 3.7500
33.79806 -110.49917 1.00008
38.37972 -119.44917 3.2500

And

df2<-structure(list(lat = c(33.29, 32.96, 48.15, 48.1, 48.18, 48.14
    ), lon = c(-109.19, -109.31, -124.69, -124.69, -124.68, -124.68
    ), m = c(0.4713, 0.8998, 0.4891, 0.8418, 0.7998, 0.5292), flagar = c(0L, 
    1L, 0L, 1L, 1L, 0L), flagk = c(0L, 0L, 0L, 0L, 0L, 0L), flagsi = c(0L, 
    0L, 0L, 0L, 0L, 0L), flags2o = c(0L, 0L, 0L, 0L, 0L, 0L), flagap = c(0L, 
    0L, 0L, 0L, 0L, 0L), flagmt = c(0L, 0L, 0L, 0L, 0L, 0L), flagcn = c(0L, 
    0L, 0L, 0L, 0L, 0L), flagkf = c(1L, 1L, 1L, 1L, 1L, 1L), flagrd = c(1L, 
    1L, 1L, 1L, 1L, 1L), flagrv = c(2L, 2L, 2L, 2L, 2L, 2L), flagpt = c(1L, 
    1L, 1L, 1L, 1L, 1L)), .Names = c("lat", "lon", "m", "flagar", 
    "flagk", "flagsi", "flags2o", "flagap", "flagmt", "flagcn", "flagkf", 
    "flagrd", "flagrv", "flagpt"), row.names = c(NA, 6L), class = "data.frame")

Upvotes: 1

Views: 61

Answers (1)

Jaap
Jaap

Reputation: 83215

Using the data.table package you could do it as follows:

library(data.table)
# convert the dataframes to datatables (which are an extended form of a dataframe)
# and round the lat & lon variables to one decimal
setDT(df1)[, `:=` (lat = round(lat,1), lon = round(lon,1))]
setDT(df2)[, `:=` (lat = round(lat,1), lon = round(lon,1))]

# joining the m column of df2 to df1 based on exact matches of the rounded lat/lon values
# m = i.m transfers the matching values to the df1 dataframe
df1[df2, m := i.m, on=c("lat","lon")]

this gives:

> df1
    lat    lon      val      m
1: 33.3 -109.2 12.50000 0.4713
2: 33.0 -109.3 11.50000 0.8998
3: 33.0 -109.3  1.75000 0.8998
4: 33.1 -109.4  1.75000     NA
5: 33.6 -110.9  0.25000     NA
6: 34.0 -111.3  3.75000     NA
7: 33.8 -110.5  1.00008     NA
8: 38.4 -119.4  3.25000     NA

If you want to match on shortest distance, see this answer for an example.

Upvotes: 2

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