#Demographic Data
TexasCountyData <- read.csv("Texas.csv")
head(TexasCountyData)
## FIPS County County.Name Total Anglo Black Hispanic Other
## 1 1 1 Anderson 58458 36064 12489 9287 618
## 2 3 2 Andrews 14786 7164 226 7195 201
## 3 5 3 Angelina 86771 55230 13197 17145 1199
## 4 7 4 Aransas 23158 16543 296 5690 629
## 5 9 5 Archer 9054 8255 39 675 85
## 6 11 6 Armstrong 1901 1742 11 124 24
#US Coordinates
USA <- map_data("county")
#Texas coordinates only
TexasCounties <- USA[which(USA$region=="texas"),]
head(TexasCounties)
## long lat group order region subregion
## 74520 -95.75271 31.53560 2492 74520 texas anderson
## 74521 -95.76989 31.55852 2492 74521 texas anderson
## 74522 -95.76416 31.58143 2492 74522 texas anderson
## 74523 -95.72979 31.58143 2492 74523 texas anderson
## 74524 -95.74698 31.61008 2492 74524 texas anderson
## 74525 -95.72405 31.63873 2492 74525 texas anderson
#Data Cleaining
colnames(TexasCountyData)[3] <- "subregion"
TexasCountyData$subregion <- tolower(TexasCountyData$subregion)
#Combining the datasets by county
Combined <- inner_join(TexasCounties,TexasCountyData,by="subregion")
attach(Combined)
theme_update(plot.title = element_text(hjust = 0.5))
Base <- ggplot()
#Hispanic Map
HispanicPercentage <- Base + geom_polygon(data = Combined, aes(x=long, y = lat, group = group,fill=Hispanic/Total),color="black") + theme_void() + coord_map() + scale_fill_gradientn(colours =rev(rainbow(4))) + ggtitle("Percent Hispanic by County")
HispanicPercentage
#Anglo Map
AngloPercentage <- Base + geom_polygon(data = Combined, aes(x=long, y = lat, group = group,fill=Anglo/Total),color="black") + theme_void() + coord_map() + scale_fill_gradientn(colours =rev(rainbow(4))) + ggtitle("Percent White by County")
AngloPercentage
#Black Map
BlackPercentage <- Base + geom_polygon(data = Combined, aes(x=long, y = lat, group = group,fill=Black/Total),color="black") + theme_void() + coord_map() + scale_fill_gradientn(colours =rev(rainbow(4))) + ggtitle("Percent Black by County")
BlackPercentage
