##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~## setup ----##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~#..........................load packages.........................library(tidyverse)#..........................import data...........................drought <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2021/2021-07-20/drought.csv')##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~## wrangle drought data ----##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~drought_clean <- drought |># select cols of interest & update names for clarity (as needed) ----select(date = valid_start, state_abb, drought_lvl, area_pct) |># add year, month & day cols using {lubridate} fxns ----# NOTE: this step isn't necessary for our plot, but I'm including as examples of how to extract different date elements from a object of class Date using {lubridate} ----mutate(year =year(date),month =month(date, label =TRUE, abbr =TRUE),day =day(date)) |># add drought level conditions names ----mutate(drought_lvl_long =factor(drought_lvl,levels =c("D4", "D3", "D2", "D1","D0", "None"),labels =c("(D4) Exceptional", "(D3) Extreme","(D2) Severe", "(D1) Moderate", "(D0) Abnormally Dry", "No Drought"))) |># reorder cols ----relocate(date, year, month, day, state_abb, drought_lvl, drought_lvl_long, area_pct)##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~## create stacked area plot of CA drought conditions through time ----##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~drought_clean |># remove drought_lvl "None" & filter for just CA ----filter(drought_lvl !="None", state_abb =="CA") |># initialize ggplot ----ggplot(mapping =aes(x = date, y = area_pct, fill = drought_lvl_long)) +# reverse order of groups so level D4 is closest to x-axis ----geom_area(position =position_stack(reverse =TRUE)) +# update colors to match US Drought Monitor ----# (colors identified using ColorPick Eyedropper extension on the original USDM data viz) scale_fill_manual(values =c("#853904", "#FF0000", "#FFC100", "#FFD965", "#FFFF00")) +# set x-axis breaks & remove padding between data and x-axis ----scale_x_date(breaks = scales::breaks_pretty(n =10),expand =c(0, 0)) +# set y-axis breaks & remove padding between data and y-axis & convert values to percentages ----scale_y_continuous(breaks =seq(0, 100, by =10),expand =c(0, 0),labels = scales::label_percent(scale =1)) +# add title ----labs(title ="Drought area in California")
