How can I match coordinates with their associated values in R - r

Question

I have 250 points that I generated within a rectangle (-4,4)x(-6,6). If the popints are within a certain space they are blue and if they are outside of that space they are red.
The code I used for this is here, where i defined the confined space with squares:
library(sf)
border <- matrix(c(
-6, -4,
-6, 4,
6, 4,
6, -4,
-6, -4
), ncol = 2, byrow = TRUE) |>
sfheaders::sfc_polygon()
# sample random points
rand_points <- st_sample(border, size = 250)
squares1 <- matrix(c(
-4, 0,
-4, 3,
-1, 3,
-1, 0,
-4, -0
), ncol = 2, byrow = TRUE) |>
sfheaders::sfc_polygon()
squares2 <- matrix(c(
-2, -4,
-2, -1,
1, -1,
1, -4,
-2, -4
), ncol = 2, byrow = TRUE) |>
sfheaders::sfc_polygon()
squares3 <- matrix(c(
2, -2,
2, 1,
5, 1,
5, -2,
2, -2
), ncol = 2, byrow = TRUE) |>
sfheaders::sfc_polygon()
squares <- c(squares1, squares2, squares3)
red_vals <- st_difference(rand_points, squares)
blue_vals <- st_intersection(rand_points, squares)`
plot(border)
plot(negative_vals, add = TRUE, col = "red")
plot(positive_vals, add = TRUE, col = "blue")
My goal is to match the points' coordinates with their expected value. Example:
In the table, the third column is for the blue points and the fourth column for the red. If the point at that coordinate is blue it gets a +1 and if it is not blue at that coordinate -1, and vice versa for the red points.
So far, I have attained the coordinates of all the points.
y <- c(red_vals)
x <- c(blue_vals)
cdata <- c(x, y)
coord <- st_coordinates(cdata)`
I am now stuck on trying to figure out how I can classify x and y to their respective coordinates and indicate this in a dataframe.
Any help is appreciated.

Answer 1

You could do:
red_vals <- rand_points[rowSums(st_intersects(rand_points, squares, F)) == 0]
blue_vals <- st_intersection(rand_points, squares)
df <- rbind(cbind(st_coordinates(red_vals), PosGroup = 1, NegGroup = -1),
cbind(st_coordinates(red_vals), PosGroup = -1, NegGroup = 1)) |>
as.data.frame()
head(df)
#> X Y PosGroup NegGroup
#> X1 -5.2248158 0.03710509 1 -1
#> X2 -5.8932331 -1.41421992 1 -1
#> X3 -0.0609895 0.26541100 1 -1
#> X4 1.7345333 -3.04312404 1 -1
#> X5 -4.6801643 0.24656851 1 -1
#> X6 1.3190239 3.36491623 1 -1
Obviously the first few values are all red dots.
We can see that the points are correct by using this data frame to draw points in ggplot:
library(ggplot2)
df %>%
ggplot() +
geom_sf(data = squares) +
geom_point(aes(X, Y, color = factor(PosGroup)), pch = 1, size = 3) +
theme_classic() +
scale_color_brewer(palette = "Set1", direction = -1)