How to create a raster from a data frame in r?

I have a data frame in which values (l) are specified for Cartesian coordinates (x, y) as in the following minimal working example.

set.seed(2013) df <- data.frame( x = rep( 0:1, each=2 ), y = rep( 0:1, 2), l = rnorm( 4 )) df # x y l # 1 0 0 -0.09202453 # 2 0 1 0.78901912 # 3 1 0 -0.66744232 # 4 1 1 1.36061149 

I want to create a raster using the raster package, but my reading of the documentation has not revealed a simple method for loading data in the form that I have it into the raster cells. I've come up with a couple ways to do it using for loops, but I suspect that there's a much more direct approach that I'm missing.

3 Answers

An easier solution exists as

 library(raster) dfr <- rasterFromXYZ(df) #Convert first two columns as lon-lat and third as value plot(dfr) dfr class : RasterLayer dimensions : 2, 2, 4 (nrow, ncol, ncell) resolution : 1, 1 (x, y) extent : -0.5, 1.5, -0.5, 1.5 (xmin, xmax, ymin, ymax) coord. ref. : NA data source : in memory names : l values : -2.311813, 0.921186 (min, max) 

Further, you may specify the CRS string. Detailed discussion is available here.

Here is one approach, via SpatialPixelsDataFrame

library(raster) # create spatial points data frame spg <- df coordinates(spg) <- ~ x + y # coerce to SpatialPixelsDataFrame gridded(spg) <- TRUE # coerce to raster rasterDF <- raster(spg) rasterDF # class : RasterLayer # dimensions : 2, 2, 4 (nrow, ncol, ncell) # resolution : 1, 1 (x, y) # extent : -0.5, 1.5, -0.5, 1.5 (xmin, xmax, ymin, ymax) # coord. ref. : NA # data source : in memory # names : l # values : -0.6674423, 1.360611 (min, max) 

help('raster') describes a number of methods to create a raster from objects of different classes.

Updating this corresponding to @zubergu about Rasterizing irregular data.

So the answer that I have adapted from the link below and possibly makes it even more simpler to understand is:

library(raster) library(rasterize) # Suppose you have a dataframe like this lon <- runif(20, -180, 180) lat <- runif(20, -90, 90) vals <- rnorm(20) df <- data.frame(lon, lat, vals) # will need to rename colnames for raster colnames(df) <- c('x', 'y', 'vals') # create a raster object r_obj <- raster(xmn=-180, xmx=180, ymn=-90, ymx=90, resolution=c(5,5)) # use rasterize to create desired raster r_data <- rasterize(x=df[, 1:2], # lon-lat data y=r_obj, # raster object field=df[, 3], # vals to fill raster with fun=mean) # aggregate function plot(r_data) 

Original response:

for those of you like @yuliaUU looking to convert irregular data to a raster, please see @RobertH's answer here.