using sf for points in polygon spatial join

gistfile1.txt

library(sf) 
library(tidyverse)

# read in the shapefile first, that gives us the CRS for the analysis
polygons <- st_read("polygons.shp")

# read in the points
points <- read_csv('points.csv')

# convert the points to an sf object
points_sf <- st_as_sf(points, coords = c("decimalLongitude", "decimalLatitude"))

# set CRS for the points to be the same as shapefile
st_crs(points_sf) <- st_crs(polygons)

# plot to see how they relate
ggplot() +
  geom_sf(data = polygons) +
  geom_sf(data = points_sf) +
  theme_minimal()

# some points are out of the polygon, lets filter out
# so we get only points in the polygon
points_sf_joined <- 
  st_join(points_sf, polygons) %>%  # spatial join to get intersection of points and poly
  filter(!is.na(rgn_name)) # rgn_name just one col from the polygon data that I chose to filter on, could use any. The idea is to get only the points that fall in the polygon

# plot again 
ggplot() +
  geom_sf(data = polygons) +
  geom_sf(data = points_sf_joined) +
  theme_minimal()

# we see only points in the polygon, great!

# the st_bbox method is less ideal because the bbox is the rectangle that the polygon fits in, not the exact shape of the polygon. With a spatial join, we can filter by location in/out of the exact shape of the polygon. 

This is EXACTLY what I needed. Thank you so much.

Thumbs up! filter requirement was not obvious to me until I saw your code, so thanks.

Interesting solution, definitely going to apply it. Athough, like filter it changes the duplicated names like if there is a variable name in both dataframes sf it would rename it like name.x and name.y. Is there a more efficient way to "crop" just the points that are inside the polygons without altering the names? Thanks in advance.