sf

I have the following map boundaries in this .gdb folder and here I have a csv which contains the variables that I want to plot and the coordinates of the points that need to be displayed on the map. My final goal is to create a map with polygons and inside every polygon there should be points according to the coordinates. Every polygon should be colored according to the count of studentid (students) for the year 2019. Any alternative is accepted I believe that the 1st code chunk below is correct: library(sf) library(tidyverse) library(data.table) library(tigris) library(leaflet) library

The task I'm trying to do is very simple with the sp package in R but I'm trying to learn sf hence my question. I'm trying to create a shape of points in R. I have lots of points so it has to be efficient. I've succeeded doing it in both sp and sf but the sf method is slow. Being new to sf , I have a feeling I'm not doing it the most efficient way. I've made 3 different functions which do the same thing: 1) 100% sp f_rgdal <- function(dat) { coordinates(dat) <- ~x+y } 2) 100% sf (probably bad...) f_sf <- function(dat) { dat <- st_sfc( lapply( apply(dat[,c("x", "y")], 1, list), function(xx) st

I want to import a very large geojson into a simple features object using st_read in R, however the hardware demands seem to be large when converting from geojson to sf. for example, importing the microsoft data for building footprints for Ohio ( https://github.com/Microsoft/USBuildingFootprints ) which is a 1.2 GB geojson eats up over 32 GB of RAM when converting. Is their a method for iterating through rows of a geojson in a function so I can import parts of the whole file without eating up all that RAM, similar to skip rows in read.csv? Using library(geojsonsf) seems to work without issue

The standard means of removing gridlines seem futile when plotting with geom_sf . For instance, if we plot a simple ggplot object, this works to remove the grid library(tidyverse) library(sf) mtcars %>% ggplot( aes(disp, hp) ) + geom_point() + theme( panel.grid.major = element_blank(), panel.grid.minor = element_blank() ) returns but the same code fails to remove the grid when you plot using geom_sf "shape/nc.shp" %>% system.file( package = "sf" ) %>% st_read( quiet = TRUE ) %>% ggplot() + geom_sf(aes(fill = AREA)) + theme( panel.grid.major = element_blank(), panel.grid.minor = element_blank()

Hi all, I am struggling with this and hope someone could come out with a simple solution. My objective is to create a regular polygon grid over the extent of a polygon, but rotated by a user-defined angle . I know that I can easily create a North/South polygon grid in sf using for example: library(sf) #> Linking to GEOS 3.6.2, GDAL 2.2.3, proj.4 4.9.3 inpoly <- st_read(system.file("shape/nc.shp", package="sf"))[1,] %>% sf::st_transform(3857) %>% sf::st_geometry() grd <- sf::st_make_grid(inpoly, cellsize = 3000) plot(inpoly, col = "blue") plot(grd, add = TRUE) I also know that I can easily

I tried the following code: library(ggplot2) library(ggmap) library(sf) nc <- st_read(system.file("shape/nc.shp", package = "sf")) str(nc) Classes ‘sf’ and 'data.frame': 100 obs. of 15 variables: $ AREA : num 0.114 0.061 0.143 0.07 0.153 0.097 0.062 0.091 0.118 0.124 ... $ PERIMETER: num 1.44 1.23 1.63 2.97 2.21 ... $ CNTY_ : num 1825 1827 1828 1831 1832 ... $ CNTY_ID : num 1825 1827 1828 1831 1832 ... $ NAME : Factor w/ 100 levels "Alamance","Alexander",..: 5 3 86 27 66 46 15 37 93 85 ... $ FIPS : Factor w/ 100 levels "37001","37003",..: 5 3 86 27 66 46 15 37 93 85 ... $ FIPSNO : num 37009