Working With Maps

Part 1: Map presidential elections results with the maps package

1/2 Download the elections file from Harvard database and clean it up

# Retrieve downloaded dataset and rename it
load("1976-2020-president.RData"); elections <- x; remove (x)
colnames(elections)

##  [1] "year"             "state"            "state_po"         "state_fips"      
##  [5] "state_cen"        "state_ic"         "office"           "candidate"       
##  [9] "party_detailed"   "writein"          "candidatevotes"   "totalvotes"      
## [13] "version"          "notes"            "party_simplified"

library(dplyr) # for data wrangling

winners = elections %>% 
  select(year, state, state_fips, candidate,candidatevotes, party_detailed) %>% 
  # select top vote-getter for every year in each state
  group_by(year, state) %>% slice_max(candidatevotes) %>%  
  # assign the usual colors based on winner's political affiliation
  # assign 'white' to three winners outside of the two main parties 
  mutate(color = ifelse(party_detailed == "DEMOCRAT", "blue", 
                        ifelse(party_detailed == "REPUBLICAN", "red", "white")))

3. Election results map for 2020

library(maps) # for mapping 

# try mapping state-level winners for the 2020 presidential election  
win20 <- winners[winners$year == 2020, ]
win20 <- win20[match(state.fips$fips, win20$state_fips),]
map('state', col = win20$color, fill = TRUE)
legend("bottomright", legend = c("Democrat", "Republican"), fill = c("blue", "red"), cex = 0.7)
title("2020 Presidential Elections Results", line = 1)

4. Elections results for all the years

# initialize a 4 x 3 grid to place maps on 
par(mfrow = c(4,3),mar=c(0,0,0,0))

# loop over all years
for (i in seq(min(winners$year),max(winners$year),4)) {
  time <- paste("win", i) # create a temporary dataframe for each year
  time <- winners[winners$year == i,] # select year as defined by 'i' counter 
  time <- time[match(state.fips$fips, time$state_fips),] # match fips
map('state', col = time$color, fill = T) # and plot
title(i, line =1)
}
legend("bottom", legend = c("Democrat", "Republican"), fill = c("blue", "red"), cex = 0.7)

Part 2. Interactive Maps with Leaflet

library(leaflet) # advanced mapping
leaflet() %>% 
  addProviderTiles(providers$OpenStreetMap.Mapnik) %>% 
  # approx. location to a World Heritage site in my hometown famous for one-horned rhinos and Bengal tigers
  setView(lat=27.58626, lng=84.44096, zoom = 10) 

Adding shapefiles for Rohingya refugee camps in Cox Bazaar, Bangladesh

# for interactive mapping with shapefiles 
library(leaflet)
library(sf) 
library(raster) 
# import shapefile
coxBazaar <- shapefile("200908_RRC_Outline_Block_AL2/200908_RRC_Outline_Block_AL2.shp")
# transform the shapefile to make it render-ready
coxBazaarT <- spTransform(coxBazaar, CRS("+proj=longlat +datum=WGS84 +no_defs"))
head(coxBazaarT)

##   Block_Let Camp_SSID Block_Name   Block_SSID SMSD_Cname       Camp_Alias
## 0         I   CXB-232     C04X_I CXB-232_I163   Camp 04X Camp 4 Extension
## 1         B   CXB-232     C04X_B CXB-232_B165   Camp 04X Camp 4 Extension
## 2         F   CXB-232     C04X_F CXB-232_F161   Camp 04X Camp 4 Extension
## 3         C   CXB-232     C04X_C CXB-232_C166   Camp 04X Camp 4 Extension
## 4         E   CXB-232     C04X_E CXB-232_E160   Camp 04X Camp 4 Extension
## 5         H   CXB-232     C04X_H CXB-232_H162   Camp 04X Camp 4 Extension
##           NPM_Cname Area_Acres         CampName         Area_SqM
## 0 Camp 04 Extension  17.597196 Camp 4 Extension 71213.3263972732
## 1 Camp 04 Extension  19.816614 Camp 4 Extension 80194.9934341609
## 2 Camp 04 Extension   8.901736 Camp 4 Extension 36024.0480281611
## 3 Camp 04 Extension  40.230092 Camp 4 Extension  162805.40781136
## 4 Camp 04 Extension  17.447146 Camp 4 Extension 70606.0954539348
## 5 Camp 04 Extension   8.247218 Camp 4 Extension 33375.3063270588

# map the data with OpenStreetMap
leaflet() %>%
  addProviderTiles(providers$OpenStreetMap) %>% 
  setView(lat = 21.18780, lng=92.14871, zoom = 13) %>%  # zooms into SE Bangladesh
  # to map Rohingya refugee campsites and add interactive labels
  addPolygons(data= coxBazaarT, fill = T, stroke =  T, weight = 1, highlight=highlightOptions(fillOpacity = 0.2),label = coxBazaarT$Block_Name)

Adding Rainfall data from Iowa Environmental Mesonet

leaflet() %>% addProviderTiles(providers$OpenStreetMap) %>% 
  setView(lat=38 ,lng= -100,zoom = 4) %>% 
  addWMSTiles(
   "http://mesonet.agron.iastate.edu/cgi-bin/wms/nexrad/n0r.cgi",
   layers = "nexrad-n0r-900913",
   options = WMSTileOptions(format = "image/png", transparent = T),
   attribution = "Weather data © 2012 IEM Nexrad"
  )