data(quakes)
library(sp)
coordinates(quakes) <- ~long+lat
library(spdplyr)
## plot a subset of locations by number of stations
quakes %>% dplyr::filter(mag <5.5 & mag > 4.5) %>% dplyr::select(stations) %>% spplot()

library(maptools)
data(wrld_simpl)
## put the centre-of-mass centroid on wrld_simpl as an attribute and filter/select
worldcorner <- wrld_simpl %>% 
  mutate(lon = coordinates(wrld_simpl)[,1], lat = coordinates(wrld_simpl)[,2]) %>% 
  filter(lat < -20, lon > 60) %>% 
  dplyr::select(NAME)

## demonstrate that we have a faithful subset of the original object
plot(worldcorner, asp = "")
text(coordinates(worldcorner), label = worldcorner$NAME, cex = 0.6)

worldcorner
#> class       : SpatialPolygonsDataFrame 
#> features    : 6 
#> extent      : -178.6131, 179.0769, -54.74973, -10.05167  (xmin, xmax, ymin, ymax)
#> coord. ref. :  +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs +towgs84=0,0,0 
#> variables   : 1
#> # A tibble: 6 x 1
#>                                  NAME
#>                                <fctr>
#> 1                           Australia
#> 2                       New Caledonia
#> 3                      Norfolk Island
#> 4 French Southern and Antarctic Lands
#> 5   Heard Island and McDonald Islands
#> 6                         New Zealand

## we can chain together standard operations as well as dplyr specific ones
wrld_simpl %>% as("SpatialLinesDataFrame") %>% summarise(big = max(AREA))
#> class       : SpatialLinesDataFrame 
#> features    : 1 
#> extent      : -180, 180, -90, 83.57027  (xmin, xmax, ymin, ymax)
#> coord. ref. : +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs +towgs84=0,0,0 
#> variables   : 1
#> # A tibble: 1 x 1
#>       big
#>     <dbl>
#> 1 1638094