Mapping 2

library(sp)
library(rgdal)

## rgdal: version: 0.9-1, (SVN revision 518)
## Geospatial Data Abstraction Library extensions to R successfully loaded
## Loaded GDAL runtime: GDAL 1.11.1, released 2014/09/24
## Path to GDAL shared files: /usr/local/Cellar/gdal/1.11.1/share/gdal
## Loaded PROJ.4 runtime: Rel. 4.8.0, 6 March 2012, [PJ_VERSION: 480]
## Path to PROJ.4 shared files: (autodetected)

library(rgeos)

## rgeos version: 0.3-8, (SVN revision 460)
##  GEOS runtime version: 3.4.2-CAPI-1.8.2 r3921 
##  Polygon checking: TRUE

library(maptools)

## Checking rgeos availability: TRUE

library(ggmap)

## Loading required package: ggplot2

library(ggplot2)

map_sp <- readOGR("/Users/rikku8221/Desktop/Mapping/nhgis-shp/","state_1860")

## OGR data source with driver: ESRI Shapefile 
## Source: "/Users/rikku8221/Desktop/Mapping/nhgis-shp/", layer: "state_1860"
## with 41 features and 7 fields
## Feature type: wkbPolygon with 2 dimensions

plot(map_sp)
title("Map of United States")

class(map_sp)

## [1] "SpatialPolygonsDataFrame"
## attr(,"package")
## [1] "sp"

Since I wasn’t sure what to map first, I began with places that I have lived over the years. These are listed below in the cities dataframe.

cities <- data.frame(name = c("Dyersburg,TN",
                    "Murfreesboro,TN",
                    "Lake Mary, FL",
                    "Oviedo, FL",
                    "Alexandria, VA"),
           stringsAsFactors = FALSE)

Now we can get the geocodes for these cities.

cities_geocoded <- geocode(cities$name)

## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Dyersburg,TN&sensor=false
## Google Maps API Terms of Service : http://developers.google.com/maps/terms
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Murfreesboro,TN&sensor=false
## Google Maps API Terms of Service : http://developers.google.com/maps/terms
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Lake+Mary,+FL&sensor=false
## Google Maps API Terms of Service : http://developers.google.com/maps/terms
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Oviedo,+FL&sensor=false
## Google Maps API Terms of Service : http://developers.google.com/maps/terms
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Alexandria,+VA&sensor=false
## Google Maps API Terms of Service : http://developers.google.com/maps/terms

cities <- cbind(cities, cities_geocoded)
ggplot(cities, aes(x = lon, y = lat)) +
  geom_point() +
  geom_text(aes(label = name), vjust = -1) +
  coord_map()

map_df <- fortify(map_sp, region = "GISJOIN")
map_1860 <- ggplot() + 
  geom_map(data = map_df,
           map = map_df,
           aes(x = long, y = lat, group = group, map_id = id),
           fill = "white",
           color = "black",
           size = 0.2) +
  coord_map() +
  theme_minimal()

map_1860

map_1860 +
  geom_point(data = cities, aes(x = lon, y = lat),
             color = "blue", size = 3) +
  geom_text(data = cities, aes(x = lon, y = lat, label = name),
            vjust = -1)

Now I’m going to map the cities where I lived on an actual map!

map_1860 +
  geom_point(data = cities,
             aes(x = lon, y = lat, size = 1),
             color = "blue", shape = 1) +
  theme(legend.position = "bottom") +
  scale_size(range = c(2, 8)) + 
  ggtitle("Cities Where Anne Lived")

This one shows the density of where I lived, rather than just locations.

map_1860 +
  geom_density2d(data = cities,
             aes(x = lon, y = lat)) +
  theme(legend.position = "bottom") +
  ggtitle("Cities Where Anne Lived")

Now that I have figured it out with relatively meaningless information, I decided to map some of the early game development hotspots in the United States. Although the map is old, and it does not have all of the states, it gives an idea of where they were.

cities <- data.frame(name = c("Cambridge, MA",
                    "Salt Lake City, UT",
                    "Sunnyvale, CA",
                    "Nashua, NH"),
           stringsAsFactors = FALSE)

cities_geocoded <- geocode(cities$name)

## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Cambridge,+MA&sensor=false
## Google Maps API Terms of Service : http://developers.google.com/maps/terms
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Salt+Lake+City,+UT&sensor=false
## Google Maps API Terms of Service : http://developers.google.com/maps/terms
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Sunnyvale,+CA&sensor=false
## Google Maps API Terms of Service : http://developers.google.com/maps/terms
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Nashua,+NH&sensor=false
## Google Maps API Terms of Service : http://developers.google.com/maps/terms

cities <- cbind(cities, cities_geocoded)
ggplot(cities, aes(x = lon, y = lat)) +
  geom_point() +
  geom_text(aes(label = name), vjust = -1) +
  coord_map()

map_df <- fortify(map_sp, region = "GISJOIN")
map_1860 <- ggplot() + 
  geom_map(data = map_df,
           map = map_df,
           aes(x = long, y = lat, group = group, map_id = id),
           fill = "white",
           color = "black",
           size = 0.2) +
  coord_map() +
  theme_minimal()

map_1860

map_1860 +
  geom_point(data = cities, aes(x = lon, y = lat),
             color = "red", size = 3) +
  geom_text(data = cities, aes(x = lon, y = lat, label = name),
            vjust = -1)

map_1860 +
  geom_point(data = cities,
             aes(x = lon, y = lat, size = 1),
             color = "red", shape = 1) +
  theme(legend.position = "bottom") +
  scale_size(range = c(2, 8)) + 
  ggtitle("Early Game Development")