我在纽约的纬度和经度方面有出租车提货数据 1.我希望将数据离散化为2km的网格，并使用每个网格中的数据进行进一步的计算 2.代码应灵活，以便在需要时轻松更改网格大小 3.
样品提货数据 -
pickup_longitude pickup_latitude
-73.9903717 40.73469543
-73.98078156 40.7299118
-73.98455048 40.67956543
-73.99346924 40.71899033
-73.96062469 40.78133011
-73.9801178 40.74304962
-73.9940567 40.71998978
-73.97942352 40.74461365
-73.94715118 40.79104614
-73.99834442 40.72389603
-74.00614929 40.74491882
-73.96932983 40.76353836
-73.9890213 40.72153854
-74.00430298 40.74224091
-73.99199677 40.71857834
-73.98516083 40.76895142
-73.97309113 40.79536057
-73.98210144 40.77469635
-73.99484253 40.71849823
-73.95303345 40.67211533
-73.98916626 40.7265892
-73.99906921 40.72017288
-73.99713898 40.74721909
-73.99741364 40.73667526
我使用过光栅包并尝试创建网格。我希望可视化网格，并运行循环以从网格中收集数据 纬度（40.757295,40.817147）和经度（-73.994057-73.929255）
min_lat <- 40.5774
max_lat <- 40.9176
min_long <- -74.15
max_long <- -73.7004
#make raster
size_raster <- 3/110.574 #
nlat <- ceiling((max_lat - min_lat)/size_raster)
r <- raster(ncol=nlat, xmn=min_long, ymn=min_lat, xmx=max_long, ymx=max_lat)
ncol(r) <- nlat
nrow(r) <- nlat
r[] <- 0
ngrid <- nlat^2