I have a dataframe df1 with 10 columns. Two of these columns are lng and lat.
I want to create a SpatialPointsDataframe from df1.
When I read on how to create a SpatialPointsDataframe it feels like I have to create a matrix m1 from my two coordinates columns and then assign that matrix to the dataframe df1.
That would be a detour since my coordinates are already a column in my dataframe df1. Furthermore, how do I assure that the coordinates from my matrix m1 are assign to the correct rows in my dataframe df1?
thats how my df1 would look like
> df1
a b c d e lat lng
1 12 f2 23 dd 2d 15.6 80.9
2 12 g5 99 NA hh 20.9 10.9
3 13 g4 12 aa 3r3 1.2 81.8
4 .. .. .. .. .. .. ..
It uses the row order to ensure the match between coordinates and the data. And, you can tell it what columns to use for lon/lat. Here's a few examples that hopefully make it a bit clearer:
library(sp)
dat_orig <- read.table(text=" a b c d e lat lng
12 f2 23 dd 2d 15.6 80.9
12 g5 99 NA hh 20.9 10.9
13 g4 12 aa 3r3 1.2 81.8", header=TRUE, stringsAsFactors=FALSE)
dat <- dat_orig
coordinates(dat) <- ~lng+lat
dat
## coordinates a b c d e
## 1 (80.9, 15.6) 12 f2 23 dd 2d
## 2 (10.9, 20.9) 12 g5 99 <NA> hh
## 3 (81.8, 1.2) 13 g4 12 aa 3r3
dat_1 <- dat_orig
colnames(dat_1) <- c(colnames(dat_1)[1:5], "steve", "larry")
coordinates(dat_1) <- ~larry+steve
dat_1
## coordinates a b c d e
## 1 (80.9, 15.6) 12 f2 23 dd 2d
## 2 (10.9, 20.9) 12 g5 99 <NA> hh
## 3 (81.8, 1.2) 13 g4 12 aa 3r3
dat_2 <- SpatialPointsDataFrame(dat_orig[,c("lng", "lat")], dat_orig[,1:5])
dat_2
## coordinates a b c d e
## 1 (80.9, 15.6) 12 f2 23 dd 2d
## 2 (10.9, 20.9) 12 g5 99 <NA> hh
## 3 (81.8, 1.2) 13 g4 12 aa 3r3
dat_3 <- dat_orig
colnames(dat_3) <- c(colnames(dat_3)[1:5], "steve", "larry")
dat_3 <- SpatialPointsDataFrame(dat_3[,c("larry", "steve")], dat_3[,1:5])
dat_3
## coordinates a b c d e
## 1 (80.9, 15.6) 12 f2 23 dd 2d
## 2 (10.9, 20.9) 12 g5 99 <NA> hh
## 3 (81.8, 1.2) 13 g4 12 aa 3r3
And, here's what coordinates<- is doing under the covers:
setReplaceMethod("coordinates", signature(object = "data.frame", value = "ANY"),
function(object, value) {
coord.numbers = NULL
if (inherits(value, "formula")) {
cc = model.frame(value, object, na.action = na.fail) # retrieve coords
if (dim(cc)[2] == 2) {
nm = as.character(as.list(value)[[2]])[2:3]
coord.numbers = match(nm, names(object))
} else if (dim(cc)[2] == 3) {
nm = c(as.character(as.list((as.list(value)[[2]])[2])[[1]])[2:3],
as.character(as.list(value)[[2]])[3])
coord.numbers = match(nm, names(object))
} # else: give up.
} else if (is.character(value)) {
cc = object[, value] # retrieve coords
coord.numbers = match(value, names(object))
} else if (is.null(dim(value)) && length(value) > 1) { # coord.columns?
if (any(value != as.integer(value) || any(value < 1)))
stop("coordinate columns should be positive integers")
cc = object[, value] # retrieve coords
coord.numbers = value
} else # raw coordinates given; try transform them to matrix:
cc = coordinates(value)
if (any(is.na(cc)))
stop("coordinates are not allowed to contain missing values")
if (!is.null(coord.numbers)) {
object = object[ , -coord.numbers, drop = FALSE]
stripped = coord.numbers
# ... but as.data.frame(x) will merge them back in, so nothing gets lost.
if (ncol(object) == 0)
#stop("only coords columns present: use SpatialPoints to create a points object")
return(SpatialPoints(cc))
} else
stripped = numeric(0)
SpatialPointsDataFrame(coords = cc, data = object, coords.nrs = stripped,
match.ID = FALSE)
}
)
Which shows it's just doing the SpatialPointsDataFrame idiom for you in a shorter call.