The R package tmap includes extensive functionality for making quality maps. We will use it here.

Set-Up

library(tmap)
library(dplyr)
library(sf)

Import shape file of class sf (created in Weighting and Transformations tutorial):

pv <- read_sf(dsn="../data", layer="pov_uscounties_sf")
class(pv)
## [1] "sf"         "tbl_df"     "tbl"        "data.frame"

For the example, we will only look at a single state, Wisconsin (state FIPS code 55):

wisc <- pv %>%
    filter(STATEFP=="55")
str(wisc)
## Classes 'sf', 'tbl_df', 'tbl' and 'data.frame':  72 obs. of  21 variables:
##  $ FIPS      : chr  "55001" "55003" "55005" "55007" ...
##  $ AREA      : num  0.2 0.311 0.265 0.457 0.157 ...
##  $ PERIMETER : num  2.13 3.75 2.09 3.07 2.1 ...
##  $ STATE_x   : chr  "55" "55" "55" "55" ...
##  $ COUNTY    : chr  "001" "003" "005" "007" ...
##  $ CO99_D00_ : chr  "553" "250" "387" "257" ...
##  $ CO99_D00_I: chr  "552" "249" "386" "256" ...
##  $ NAME_x    : chr  "Adams" "Ashland" "Barron" "Bayfield" ...
##  $ LSAD      : chr  "06" "06" "06" "06" ...
##  $ LSAD_TRANS: chr  "County" "County" "County" "County" ...
##  $ COUNTYFP  : chr  "001" "003" "005" "007" ...
##  $ STATEFP   : chr  "55" "55" "55" "55" ...
##  $ X1        : num  3047 3048 3049 3050 3051 ...
##  $ STATE_y   : chr  "55" "55" "55" "55" ...
##  $ NAME_y    : chr  "Adams County" "Ashland County" "Barron County" "Bayfield County" ...
##  $ totpopn   : num  18643 16866 44963 15013 226778 ...
##  $ poverty   : num  102.3 113.8 86.8 124 66.7 ...
##  $ ag        : num  22.05 20.87 37.61 27.11 6.63 ...
##  $ manu      : num  74.1 79.2 128.3 41 112.2 ...
##  $ retail    : num  48.2 48.7 61.7 47.6 67.2 ...
##  $ geometry  :sfc_MULTIPOLYGON of length 72; first list element: List of 1
##   ..$ :List of 1
##   .. ..$ : num [1:321, 1:2] -89.8 -89.8 -89.8 -89.7 -89.7 ...
##   ..- attr(*, "class")= chr  "XY" "MULTIPOLYGON" "sfg"
##  - attr(*, "sf_column")= chr "geometry"
##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA NA NA ...
##   ..- attr(*, "names")= chr  "FIPS" "AREA" "PERIMETER" "STATE_x" ...

Thematic Mapping

#basic grey map with county borders
basemap <- tm_shape(wisc) +
    tm_borders() 
basemap + tm_fill()

We can also plot one of the variables, poverty:

povmap <- basemap + tm_fill(col="poverty")
povmap

Create a map with panels of maps:

#create and store maps
agmap <- basemap + tm_fill(col="ag")
retailmap <- basemap + tm_fill(col="retail")
manumap <- basemap + tm_fill(col="manu")    

#those maps into panels
tmap_arrange(povmap, agmap, retailmap, manumap)

Make an interactive map you can scroll over and visually explore poverty in Wisconsin:

tmap_mode("view")
basemap + tm_polygons(col="poverty")
tmap_mode("plot")
basemap + tm_polygons(col="poverty") + 
    tm_symbols(col = "red", size = "totpopn", alpha=0.5) +
    tm_layout(legend.title.size = 0.7,
          legend.text.size = 0.5,
          legend.position = c("right","top"),
          legend.bg.color = "white",
          legend.bg.alpha = 1)

Add a point to Madison, Wisconsin:

mad <- data.frame(c("Madison,Wisconsin"),
                  lat=43.0731,
                  long = -89.4012)
site_mad <- sf::st_as_sf(mad, coords = c("long", "lat"),
                         crs = "+proj=longlat +datum=WGS84",
                         agr="identity")

basemap + tm_shape(site_mad) + 
    tm_dots(size=2, col="red", shape=21) +
    tm_compass() +
    tm_layout(title="Madison, WI", title.position = c("center","top"))