cartography (version 1.3.0)

getGridData: Compute Data for a Grid Layer

Description

This function computes data to match a grid layer (as outputed by getGridLayer ) according to the surface intersections.

Usage

getGridData(x, df, dfid = NULL, var)

Arguments

x

a list generated by the getGridLayer function.

df

a data frame that contains the values to adapt to the grid. It must correspond to the spdf argument in getGridLayer.

dfid

identifier field in df, default to the first column of df. (optional)

var

name of the numeric field in df to adapt to the grid.

Value

A data frame is returned. id_cell are ids of the grid, the two other variable are the share of the variable in each cell and the share of the variable in each cell divided by its area (in map units).

See Also

getGridLayer

Examples

## Not run: 
# data(nuts2006)
# # Create a grid layer
# mygrid <- getGridLayer(spdf=nuts2.spdf,cellsize = 200000)
# # Compute data for the grid layer
# datagrid.df <- getGridData(mygrid, nuts2.df, "pop2008",dfid=NULL)
# 
# # Plot total population
# plot(mygrid$spdf, col="#CCCCCC",border="white")
# propSymbolsLayer(spdf = mygrid$spdf, df = datagrid.df, legend.style = "e",
#                  legend.pos = "right", border = "white",legend.title.txt = "Total population",
#                  var = "pop2008", k=0.005, col="black", add=TRUE)
# 
# # Plot dentsity of population 
# ## conversion from square meter to square kilometers
# datagrid.df$densitykm <- datagrid.df$pop2008_density*1000*1000 
# cols <- carto.pal(pal1 = "taupe.pal", n1 = 6)
# choroLayer(spdf = mygrid$spdf,df = datagrid.df,var = "densitykm", add=FALSE,
#            border = "grey80",col=cols,
#            legend.pos = "right", method = "q6",
#            legend.title.txt = "Population density")
#            ## End(Not run)