tweenr_test.R

library(tidyverse)
library(animation)
library(tweenr)
library(gtools)

income <- read_csv("income.csv")
income_levels <- mixedsort(unique(income$income_level))
income_levels <- c(income_levels[16], income_levels[1:15])

income <- income %>% mutate(income_level=factor(income_level,
                                                levels=income_levels))

census_regions <- read_csv("https://raw.githubusercontent.com/cphalpert/census-regions/master/us%20census%20bureau%20regions%20and%20divisions.csv")

combined_frame <- income %>% inner_join(census_regions, by=c('state' = 'State'))

visualization_frame <- 
	combined_frame %>%
		group_by(year, Region, income_level) %>%
		summarise(percent_of_total = mean(percent_of_total)) %>%
		ungroup()

mylist <- 
	visualization_frame %>%
		mutate(year2 = year, Region = as_factor(Region)) %>%
		nest(-year) %>%
		pull(data)

tween.df <- tween_states(mylist
						,tweenlength = 1
						,statelength = 2
						,ease = 'cubic-in-out'
						,nframes=121)

myplot<-function(i){  
	g <- 
		ggplot(data = filter(tween.df, i==.frame)
				, aes(x = income_level, y = percent_of_total, fill = Region)
				) +
			geom_bar(stat="identity", position="stack") +
			theme_minimal() +
			theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
			ggtitle("Distribution by Income Level", "by % of total state population") +
			xlab("") +
			ylab("% of Population")

	return(g)
}

oopt = ani.options(interval = 0.1)
saveGIF({for (i in seq_along(unique(tween.df$.frame))) {
  g <- myplot(i)
  print(g)
  print(i)
  ani.pause()
}
}, movie.name="incomedata_tween.gif", ani.width = 600, ani.height = 600)