Rafael H M Pereira rafapereirabr

This gist shows in two steps how to tilt and stack maps using ggplot2 in order to create an image like this one: [![enter image description here][1]][1]

Let's load the necessary libraries and data to use a reproducible example:

# load libraries
  library(rgeos)
  library(UScensus2000tract)
  library(ggplot2)

This is the fastest way I've found so far to calculate the distances between pairs of lat long coordinates. The method takes advantage of distGeo{geosphere} and the crazy fast := operator of data.table.

Load libraries and data for Reproducible example

# load libraries
  library(data.table)
  library(dplyr)
  library(sp)
  library(rgeos)
  library(UScensus2000tract)

This gist shows how to create an animated world map of life expectancy using R. The data comes the UN World Population Prospects, 2015 Revision, and it brings life expectancy data from 1950 untill 2015 and projeceted data up to 2100. Thanks Topi Tjukanov, who reminded me of the UN DESA data portal, where you can find this dataset and many others

The idea is to use open data to create a GIF, much like the ones created by Aron Strandberg but his maps look much nicer. The output of this script is a map like this one:

[![enter image description here][1]][1]

Now diving into the code. First, let's load the necessary libraries and get the data. As of this writing, the current version of gganimate has a bug that messes the aesthetics of the .gif file. As a temporary solution, I've intalled an older version of the package, [as recommended by the author of the gganimate, David Ro

	## This gist shows how to create Flow Maps in R using ggplot2.
	## source: This is based on different bits of code from other with amazing R skills:

	@ceng_l : http://web.stanford.edu/~cengel/cgi-bin/anthrospace/great-circles-on-a-recentered-worldmap-in-ggplot
	@3wen : http://egallic.fr/maps-with-r/
	@spatialanalysis : http://spatialanalysis.co.uk/2012/06/mapping-worlds-biggest-airlines/
	@freakonometrics : http://freakonometrics.hypotheses.org/48184


	# Libraries

	library(data.table)
	library(ggmap)

	# load data. Obs: The file used in this example does not allow to create flow maps
	df <- fread("your_data.csv)

	# Get Map background
	map <- get_map(location = c(lon = -43.45967, lat = -22.92728),
	zoom = 10, source = "stamen", maptype = "toner-background")

	library(stringr)
	library(stringi)
	library(ggplot2)
	library(viridis)
	library(data.table)
	library(BAMMtools) # fast calculation of jenks natural breaks
	library(ggt)

	# load data
	data("iris")

	library(stringr)
	library(spdep)
	library(rgdal)
	library(magrittr)
	library(ggplot2)
	library(sf)



	#======================================================

	library(tidyverse)
	library(maps)

	temp <- maps::world.cities %>%
	ggplot() +
	geom_point(aes(x=long, y=lat, size=pop, fill=pop, color=pop), alpha=.1, show.legend = FALSE) +
	theme_void() +
	coord_equal()

	ggsave( temp, file="pop.png", dpi = 300, width = 20, height = 10)

	// Use Gists to store code you would like to remember later on
	console.log(window); // log the "window" object to the console