Convert GRaster or GVector to a data frame

Convert a GRaster to a table, or a GVector's data table to a data.frame or data.table.

Usage

# S4 method for class 'GRaster'
as.data.table(x, na.rm = TRUE, labels = TRUE, xy = FALSE, cells = FALSE)

# S4 method for class 'GRaster'
as.data.frame(x, na.rm = TRUE, labels = TRUE, xy = FALSE, cells = FALSE)

# S4 method for class 'GVector'
as.data.frame(x)

# S4 method for class 'GVector'
as.data.table(x)

Arguments

x: A GRaster or GVector.
na.rm: Logical: Indicates whether to remove NA values (default is TRUE; GRasters only)`.
labels: Logical: If TRUE, a "factor" (categorical) GRaster will have its factor level labels returned. If FALSE, the integer codes are returned. Default is TRUE (for GRasters only, and only has an effect if the GRaster is of type "factor").
xy: Logical: If TRUE, return coordinates of cell centers (default is FALSE, for GRasters only).
cells: Logical: If TRUE, return cell columns and rows (default is FALSE, for GRasters only).

Value

A data.frame or NULL (if the GVector has no data table, or if GRaster's values are all NA).

Examples

if (grassStarted()) {

# Setup
library(sf)
library(terra)

# Example data
madElev <- fastData("madElev")
madForest2000 <- fastData("madForest2000")
madCoast0 <- fastData("madCoast0")
madRivers <- fastData("madRivers")
madDypsis <- fastData("madDypsis")

### GRaster properties

# convert SpatRasters to GRasters
elev <- fast(madElev)
forest <- fast(madForest2000)

# plot
plot(elev)

dim(elev) # rows, columns, depths, layers
nrow(elev) # rows
ncol(elev) # columns
ndepth(elev) # depths
nlyr(elev) # layers

res(elev) # resolution

ncell(elev) # cells
ncell3d(elev) # cells (3D rasters only)

topology(elev) # number of dimensions
is.2d(elev) # is it 2D?
is.3d(elev) # is it 3D?

minmax(elev) # min/max values

# name of object in GRASS
sources(elev)

# "names" of the object
names(elev)

# coordinate reference system
crs(elev)

# extent (bounding box)
ext(elev)

# data type
datatype(elev)

### operations on GRasters

# assigning
pie <- elev
pie[] <- pi # assign all cells to the value of pi
pie

# concatenating multiple GRasters
rasts <- c(elev, forest)
rasts

# number of layers
nlyr(elev)

# adding a raster "in place"
add(rasts) <- ln(elev)
rasts

# subsetting
rasts[[1]]
rasts[["madForest2000"]]

# assigning
rasts[[4]] <- elev > 500

# names
names(rasts)
names(rasts) <- c("elev_meters", "forest", "ln_elev", "high_elevation")
rasts

# converting to data.tables/data.frames
as.data.table(rasts)
head(as.data.frame(rasts))

### GVector properties

# convert sf vectors to GVectors
coast <- fast(madCoast4)
rivers <- fast(madRivers)
dypsis <- fast(madDypsis)

# extent
ext(rivers)

W(rivers) # western extent
E(rivers) # eastern extent
S(rivers) # southern extent
N(rivers) # northern extent
top(rivers) # top extent (NA for 2D rasters like this one)
bottom(rivers) # bottom extent (NA for 2D rasters like this one)

# coordinate reference system
crs(rivers)
st_crs(rivers)

# column names and data types
names(coast)
datatype(coast)

# name of object in GRASS
sources(rivers)

# points, lines, or polygons?
geomtype(dypsis)
geomtype(rivers)
geomtype(coast)

is.points(dypsis)
is.points(coast)

is.lines(rivers)
is.lines(dypsis)

is.polygons(coast)
is.polygons(dypsis)

# dimensions
nrow(rivers) # how many spatial features
ncol(rivers) # hay many columns in the data frame

# number of geometries and sub-geometries
ngeom(coast)
nsubgeom(coast)

# 2- or 3D
topology(rivers) # dimensionality
is.2d(elev) # is it 2D?
is.3d(elev) # is it 3D?

# Update values from GRASS
# (Reads values from GRASS... will not appear to do anything in this case)
coast <- update(coast)

### operations on GVectors

# convert to data frame
as.data.frame(rivers)
as.data.table(rivers)

# subsetting
rivers[c(1, 3)] # select 2 rows/geometries
rivers[-3] # remove row/geometry 3
rivers[ , 1] # column 1
rivers[ , "TopElev"] # select column
rivers[["TopElev"]] # select column
rivers[1, 2:3] # row/geometry 1 and column 2 and 3
rivers[c(TRUE, FALSE)] # select every other geometry (T/F vector is recycled)
rivers[ , c(TRUE, FALSE)] # select every other column (T/F vector is recycled)

# removing data table
noTable <- dropTable(rivers)
noTable
nrow(rivers)
nrow(noTable)

# Refresh values from GRASS
# (Reads values from GRASS... will not appear to do anything in this case
# since the rivers object is up-to-date):
rivers <- update(rivers)

# Concatenating multiple vectors
rivers2 <- rbind(rivers, rivers)
dim(rivers)
dim(rivers2)

}

Usage

Arguments

Value

See also

Examples