Convert marks (S3:data.frame) to factors with levels

Question

In relation to this question I have a sptatstat ppp object sf_owin which has marks as S3:data.frame as seen below:

The sf_object looks like this:

Simple feature collection with 131 features and 3 fields
geometry type:  MULTIPOINT
dimension:      XY
bbox:           xmin: -1932934 ymin: 4958872 xmax: -1439558 ymax: 5861173
projected CRS:  NAD83(2011) / UTM zone 16N
# A tibble: 131 x 4
# Groups:   COOPID [131]
   COOPID STATION_NA                         geometry Annual_Precipitation
 *  <dbl> <chr>                      <MULTIPOINT [m]>                <dbl>
 1      0 Ontario                ((-1899685 5335073))                 9.24
 2 100010 ABERDEEN EXPERIMNT STN ((-1610453 5091311))                12.4 
 3 100227 AMERICAN FALLS 3 NW    ((-1623401 5075011))                20.4 
 4 100282 ANDERSON DAM           ((-1807106 5212322))                16.3 
 5 100347 ARBON 2 NW             ((-1606302 5034484))                10.2 
 6 100375 ARCO                   ((-1622855 5179969))                19.5 
 7 100448 ARROWROCK DAM          ((-1834338 5254236))                20.1 
 8 100470 ASHTON                 ((-1458491 5179214))                37.5 
 9 100528 AVERY RS #2            ((-1678382 5654084))                25.3 
10 100667 BAYVIEW MODEL BASIN    ((-1691954 5753129))                 9.69

How can I convert marks from S3:data.frame to factor with three levels (COOP_ID, STATION_NA and Annual_Precipitation) ? Or I think it would be better to just drop/remove COOP_ID and Annual_Precipitation as I don't really need them for the particular task.

Answer 1

With spatstat loaded and the ppp object saved as sf_owin (very counterintuitive name for a ppp object) you can simply overwrite the marks as:

marks(sf_owin) <- factor(marks(sf_owin)$STATION_NA)

This omits the info about precipitation etc.