In-Class Exercise 03

Chloropleth Mapping

pacman::p_load(sf, tmap, tidyverse)

NGA_wp <- read_rds("data/rds/NGA_wp.rds")

Plotting map of rate

p1 <- tm_shape(NGA_wp) + 
  tm_fill("wp_functional",
          n = 10,
          style = "equal",
          palette = "Blues") +
  tm_borders(lwd = 0.1,
             alpha = 1) +
  tm_layout(main.title = "Distribution of functional water points of LGAs",
            legend.outside = FALSE)

tmap_arrange(p1, nrow = 1)

Rate map of functional water point by LGAs

NGA_wp <- NGA_wp %>%
  mutate(pct_functional = wp_functional/total_wp) %>%
  mutate(pct_nonfunctional = wp_nonfunctional/total_wp)

tm_shape(NGA_wp) + 
  tm_fill("pct_functional",
          n = 10,
          style = "equal",
          palette = "Reds") +
  tm_borders(lwd = 0.1,
              alpha = 1) +
  tm_layout(main.title = "Rate map of functional water points",
            legend.outside = TRUE)

Extreme Value Map

Percentile Map

Exclude records with NA

NGA_wp <- NGA_wp %>%
  drop_na()

Creating customised classification and extracting values

#percent <- c(0,.01,.1,.5,.9,.99,1)
#var <- NGA_wp['pct_functional'] %>%
  #st_set_geometry(NULL)
#quantile(var[,1],percent)

get.var <- function (vname, df) { 
  v <- df[vname] %>%
    st_set_geometry(NULL)
  v <- unname (v[,1])
  return(v)
}

percentmap <- function(vnam, df, legtitle=NA, mtitle="Percentile Map"){
  percent <- c(0,.01,.1,.5,.9,.99,1) 
  var <- get.var(vnam, df) 
  bperc <- quantile(var, percent) 
  tm_shape(df) + 
  tm_polygons() + 
  tm_shape(df) + 
    tm_fill(vnam,
            title=legtitle, 
            breaks=bperc, 
            palette="Blues",
            labels= c("< 1%", "1% - 10%", "10% - 50%", "50% - 90%", "90%", "90% - 99%", "> 99%"))
  tm_borders() +
  tm_layout(main.title = mtitle,
            title.position = c("right", "bottom"))
  }

#percentmap("wp_functional",NGA_wp)

Box map

ggplot(data = NGA_wp,
       aes(x = "",
           y = wp_nonfunctional)) +
  geom_boxplot()