Convert an object of class prevR into a data.frame.

Source: R/as.data.frame.prevR.r

This function merges the slots clusters et rings of a object of class prevR.

# S3 method for prevR
as.data.frame(x, ..., N = NULL, R = NULL, clusters.only = FALSE)

Arguments

x

object of class prevR.

...

not used, for compatibility with the generic method base::as.data.frame().

N

integer or list of integers setting elements of rings to extract.

R

integer or list of integers setting elements of rings to extract.

clusters.only

return only the slot clusters of x?

Value

If clusters.only = TRUE, the function will return only the slot clusters of x.

Otherwise, slots clusters and rings of x will be merged in a unique data frame. The columns of rings will be renamed adding a suffix like .N300.RInf.

N and R define the elements of rings to extract. If not specified (NULL), all the elements of rings will be included.

Examples

str(fdhs)
#> Formal class 'prevR' [package "prevR"] with 4 slots
#>   ..@ clusters:'data.frame':	401 obs. of  10 variables:
#>   .. ..$ id    : int [1:401] 1 10 100 101 102 103 104 105 106 107 ...
#>   .. ..$ x     : num [1:401] -1.21 -1.79 -2.29 -2.71 -1.96 ...
#>   .. ..$ y     : num [1:401] 7.29 6.13 5.96 6.04 5.12 ...
#>   .. ..$ n     : num [1:401] 23 22 22 28 21 21 11 24 23 15 ...
#>   .. ..$ pos   : num [1:401] 0 0 0 0 3 4 0 1 0 0 ...
#>   .. ..$ c.type: Factor w/ 2 levels "Rural","Urban": 1 1 1 1 1 1 1 1 1 1 ...
#>   .. ..$ wn    : num [1:401] 19.8 19.8 20.2 20.2 20.2 ...
#>   .. ..$ wpos  : num [1:401] 0 0 0 0 2.88 ...
#>   .. ..$ prev  : num [1:401] 0 0 0 0 14.3 ...
#>   .. ..$ wprev : num [1:401] 0 0 0 0 14.3 ...
#>   ..@ boundary:Classes ‘sf’ and 'data.frame':	1 obs. of  1 variable:
#>   .. ..$ geometry:sfc_POLYGON of length 1; first list element: List of 1
#>   .. .. ..$ : num [1:4056, 1:2] 1.28 1.25 1.23 1.22 1.22 ...
#>   .. .. ..- attr(*, "class")= chr [1:3] "XY" "POLYGON" "sfg"
#>   .. ..- attr(*, "sf_column")= chr "geometry"
#>   .. ..- attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: 
#>   .. .. ..- attr(*, "names")= chr(0) 
#>   .. ..- attr(*, "valid")= logi TRUE
#>   ..@ proj    :List of 2
#>   .. ..$ input: chr "+proj=longlat +datum=WGS84"
#>   .. ..$ wkt  : chr "GEOGCRS[\"unknown\",\n    DATUM[\"World Geodetic System 1984\",\n        ELLIPSOID[\"WGS 84\",6378137,298.25722"| __truncated__
#>   .. ..- attr(*, "class")= chr "crs"
#>   ..@ rings   : list()
str(as.data.frame(fdhs))
#> 'data.frame':	401 obs. of  10 variables:
#>  $ id    : int  1 10 100 101 102 103 104 105 106 107 ...
#>  $ x     : num  -1.21 -1.79 -2.29 -2.71 -1.96 ...
#>  $ y     : num  7.29 6.13 5.96 6.04 5.12 ...
#>  $ n     : num  23 22 22 28 21 21 11 24 23 15 ...
#>  $ pos   : num  0 0 0 0 3 4 0 1 0 0 ...
#>  $ c.type: Factor w/ 2 levels "Rural","Urban": 1 1 1 1 1 1 1 1 1 1 ...
#>  $ wn    : num  19.8 19.8 20.2 20.2 20.2 ...
#>  $ wpos  : num  0 0 0 0 2.88 ...
#>  $ prev  : num  0 0 0 0 14.3 ...
#>  $ wprev : num  0 0 0 0 14.3 ...
if (FALSE) {
r.fdhs <- rings(fdhs, N = c(100, 200, 300))
str(r.fdhs)
str(as.data.frame(r.fdhs, clusters.only = TRUE))
str(as.data.frame(r.fdhs))
str(as.data.frame(r.fdhs, N = 300))
}