Incite into Liberia’s population, density, household and female percentage

install.packages(“ggplot2”) install.packages(“ggmaps”) install.packages(“rgdal”) install.packages(“rgeos”) install.packages(“sp”) install.packages(“shapefiles”) install.packages(“ggmap”) install.packages(“dplyr”) install.packages(“plyr”) library(dplyr) library(plyr) library(ggplot2) library(ggmaps) library(rgdal) library(rgeos) library(sp) library(shapefiles) library(ggmap)

require(dplyr) require(plyr) require(ggplot2) require(ggmaps) require(rgdal) require(rgeos) require(sp) require(shapefiles) require(ggmap)

counties <- readOGR(dsn=“Liberia_Dean”, layer=“counties”, stringsAsFactors=FALSE, verbose=FALSE)

proj4string(counties)

counties <- spTransform(counties, CRS(“+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0”))

counties_f <- fortify(counties, region = “CCNAME”)

liberia <- get_map(location = c(-11.65, 4.25, -7.25, 8.6), maptype = “watercolor”)

liberia <- ggmap(liberia)

lbr_counties <- liberia + geom_map(data=country_f,map=country_f,aes(x=long, y=lat, map_id=id),color =“white”, alpha = 0, size = .6)

lbr_counties <- lbr_counties + geom_map(data=counties_f,map=counties_f,aes(x=long, y=lat, map_id=id),color =“white”, fill = “orangered”, alpha = .5, size = .3)

lbr_counties <- lbr_counties + ggtitle(“Total Population (in 1000s)”)

trueCentroids = gCentroid(counties,byid=TRUE)

plot(counties)

points(coordinates(counties))

CountyPointsDF<- merge(counties_f, counties@data, by = “id”)

countiesName = counties@data$CCNAME

vecCounties = cbind.data.frame(trueCentroids, countiesName)

lbr_counties <- lbr_counties + annotate(‘text’, x = vecCountiesx,y=vecCountiesy,label =

vecCounties$countiesName, size = 2)

counties_f <- left_join(x = counties_f, y = counties@data, by = c(“id” = “CCNAME”))

lbr_cnty_pop <- lbr_counties + geom_map(data=counties_f,map=counties_f,aes(x=long, y=lat,map_id=id, fill =SUM_TOTAL/1000), color =“white”, alpha = .5, size = .1)

lbr_cnty_pop <- lbr_cnty_pop + scale_fill_gradient2(low = “blue”, mid=“yellow”, high=“red”,midpoint = 600, space=“Lab”, guide = guide_legend(title = NULL))

lbr_cnty_pop

Total Population (in 1000s).

// Person per KM2

lbr_counties <- lbr_counties + ggtitle(“Persons per km2”)

lbr_cnty_Density <- lbr_counties + geom_map(data=counties_f,map=counties_f,aes(x=long, y=lat,map_id=id, fill = SUM_TOTAL / Sq_km), color =“white”, alpha = .5, size = .1)

lbr_cnty_Density <- lbr_cnty_Density + scale_fill_gradient2(low = “blue”, mid=“yellow”, high=“red”,midpoint = 600, space=“Lab”, guide = guide_legend(title = NULL))

Total Persons per km2.

//Percent Female lbr_counties <- lbr_counties + ggtitle(“Percent Female”)

lbr_cnty_FemalePer <- lbr_counties + geom_map(data=counties_f,map=counties_f,aes(x=long, y=lat,map_id=id, fill = SUM_FEMALE / SUM_TOTAL), color =“white”, alpha = .5, size = .1)

lbr_cnty_FemalePer <- lbr_cnty_FemalePer + scale_fill_gradient2(low = “blue”, mid=“yellow”, high=“red”,midpoint = 600, space=“Lab”, guide = guide_legend(title = NULL))

lbr_cnty_FemalePer

lbr_cnty_FemalePer <- lbr_cnty_FemalePer + scale_fill_gradient(low = “blue”, high=“red”, space=“Lab”, + guide = guide_legend(title = NULL))

lbr_cnty_FemalePer

Total Percent of Females.

// Persons per household

lbr_counties <- lbr_counties + ggtitle(“Persons per Household”)

lbr_cnty_HH <- lbr_counties + geom_map(data=counties_f,map=counties_f,aes(x=long, y=lat,map_id=id, fill = SUM_TOTAL / SUM_HH), color =“white”, alpha = .5, size = .1)

lbr_cnty_HH <- lbr_cnty_HH + scale_fill_gradient(low = “blue”, high=“red”, space=“Lab”,guide = guide_legend(title = NULL))

lbr_cnty_HH Total Persons per Household.

Total Persons per Household.