Find a best row in the data frame

Question

I have a data set with some locations:

ex <- data.frame(lat = c(55, 60, 40), long = c(6, 6, 10))

and than I have climate data

clim <- structure(list(lat = c(55.047, 55.097, 55.146, 55.004, 55.054, 
55.103, 55.153, 55.202, 55.252, 55.301), long = c(6.029, 6.0171, 
6.0051, 6.1269, 6.1151, 6.1032, 6.0913, 6.0794, 6.0675, 6.0555
), alt = c(0.033335, 0.033335, 0.033335, 0.033335, 0.033335, 
0.033335, 0.033335, 0.033335, 0.033335, 0.033335), x = c(0, 0, 
0, 0, 0, 0, 0, 0, 0, 0), y = c(1914, 1907.3, 1901.8, 1921.1, 
1914.1, 1908.3, 1902.4, 1896, 1889.8, 1884)), row.names = c(NA, 
10L), class = "data.frame", .Names = c("lat", "long", "alt", 
"x", "y"))

      lat   long      alt x      y
1  55.047 6.0290 0.033335 0 1914.0
2  55.097 6.0171 0.033335 0 1907.3
3  55.146 6.0051 0.033335 0 1901.8
4  55.004 6.1269 0.033335 0 1921.1
5  55.054 6.1151 0.033335 0 1914.1
6  55.103 6.1032 0.033335 0 1908.3
7  55.153 6.0913 0.033335 0 1902.4
8  55.202 6.0794 0.033335 0 1896.0
9  55.252 6.0675 0.033335 0 1889.8
10 55.301 6.0555 0.033335 0 1884.0

What I want to do is to "merge" both datasets to have climate data in the ex file. The values of lat and long in ex are different than values of lat and long in clim so I they can not be merged directly (it is the same for long). I need to find the best point (closest point in clim for each of row in the ex considering both lat and long)

The expected output for the example is:

  lat long      alt x      y
1  55    6 0.033335 0 1914.0
2  60    6 0.033335 0 1884.0
3  40   10 0.033335 0 1921.1

Answer 1

The function dist can be used to calculate Euclidean (or other) distances between all points in a matrix or data frame, so a way of finding the points in clim that are closest to those in ex is by

# Distance between all points in ex and clim combined,
# with distances between points in same matrix filtered out
n <- nrow(ex)
tmp <- as.matrix(dist(rbind(ex, clim[, 1:2])))[-(1:n), 1:n]

# Indices in clim corresponding to the closest points to those in ex
idx <- apply(tmp, 2, which.min)

# Points from ex with additional info from closest points in clim
cbind(ex, clim[idx, -(1:2)])
#>    lat long      alt x      y
#> 1   55    6 0.033335 0 1914.0
#> 10  60    6 0.033335 0 1884.0
#> 4   40   10 0.033335 0 1921.1