ggmap

Is there a way to implement gg_animate in R to produce a gif. I already have my ggmaps created and saved as PDFs. I would like to create an animation which scrolls through those maps maybe holding on each image for 1 or 2 seconds. Is there a way to do this in R or should I use some sort of gif creator - if so any suggestions? Thanks much Update Jul2018 : gganimate() has undergone a rewrite and is now much improved . The previous API is only available through the archived version and should not be expected to work with the new version. With the new version: library(gapminder) library(gganimate)

I want to visualize a dataframe with R and the ggmap package. df: | lon | lat | |-----------|-----------| | 6.585863 | 51.09021 | | 8.682.127 | 50.11092 | | 7.460.367 | 5.152.755 | I created a map with mapImageData <- get_googlemap( + "Germany", + zoom=15 + ) And then wanted to add the geocodes: ggmap(mapImageData) + + geom_point(aes(x=lon, y=lat), data=df, colour="red", size=5) But I get the error: Error: geom_point requires the following missing aesthetics: x, y What am I doing wrong? You have three problems: More than one deicmal point in some values & decimal points probably not at the

I need to plot spatial data in a non-square map. I have been using ggmap, and supposedly you can get non squared maps giving low-west-corner and upper-right-corner coordinates. However, actually it seems it doesn't work (reported here and here ). Anyone knows how to get rectangular maps in R/ggmap? If you can live without Google Maps, there are easy, immediate alternatives (I'd've included CloudMade but I don't have an enterprise account): library(ggmap) loc <- c(-96, 29.4, -94, 30.2) # gmaps tx_map_gmaps <- get_map(location=loc, source="google", maptype="terrain") gg <- ggmap(tx_map_gmaps) gg

I am generating a few maps and I would like show the borders of counties on top of a ggmap roadmap. Here is an example using part of Texas. library(ggmap) map = get_map(location = c(-95.31619, 28.42460), zoom = 6, source = "google", maptype="roadmap") map.plot = ggmap(map) # get texas counties counties <- map_data("county") tx_county <- subset(counties, region == 'texas') map.plot + theme_nothing() + geom_polygon(data = tx_county, aes(x=long, y=lat), fill = NA, color = "red") However, the resulting figure has lines crossing counties instead of just the borders. Any thoughts on what I am doing

I am trying to use ggmap to create a map of the protected areas I am working in with a satellite image from google earth underneath. I can make a very satisfactory image except that it lacks a north arrow and scale bar: I'm aware that there are very long winded ways to add these elements (e.g. here ) but there must surely be a more parsimonious way to do it! I've tried using map.scale and north.arrow but these both give me: Error in polygon(xb + arrow.x * s, yb + arrow.y * s, ...) : plot.new has not been called yet I can get both map.scale and north.arrow to work in base R using plot but then

I have been trying to make a different this lovely flowing data visualization for some time this week but keep hitting a snag in the final implementation. Here is the data set I'm using. I have melded it into a frame with the three key bits of information I want to display: startinglatlong, endinglatlong, and number of trips. I got closest using the idea posted here , but two hit a snag on two items: 1) making the size of the line change based on the number of trips 2) getting the google api to allow me to call this many rows (I have 55,704 in my data set). counts is the name of my full df,

I have been stuck with this for hours. When I run this : library(ggmap) set.seed(1) n=100 df <- data.frame(x=rnorm(n, 0, 1), y=rnorm(n, 0, 1)) TestData <- ggplot (data = df) + stat_density2d(aes(x = x, y = y,fill = as.factor(..level..)),bins=4, geom = "polygon",) + geom_point(aes(x = x, y = y)) + scale_fill_manual(values = c("yellow","red","green","royalblue", "black")) I get this error message : Error: Unknown parameters: bins Does anyone know why? Okay, adding this one as a second answer because I think the descriptions and comments in the first answer are useful and I don't feel like