README.md
In RobertMyles/flagfillr: Use Flags as Fills for ggplot2 Maps

flagfillr

flagfillr is a little package for R that makes it easier to use flags as fills (i.e. backgrounds) for ggplot2 maps.

You can install flagfillr from github with:

# install.packages("devtools")
devtools::install_github("RobertMyles/flag_fillr")

It's not on CRAN because it depends on development versions of some packages, and because the size of the 1000px flags renders it difficult for CRAN to accept. So it'll probably never be on CRAN, but hey, that's OK.

Important Note: flagfillr works with ggplot2's geom_sf(), which is currently only available in the current development version of ggplot2 (version 2.2.1.9000).

Well, I'm happy you asked. Imagine you saw the following image, from the Drunkneysian, taken from here:

It's an interesting subject, and a handy visual summary of the data. But...

...isn't this sooo much nicer?

(The section below shows how to make it.) Ok...it depends on some knowledge of flags, but look! They're so purty. And, I mean, just look at Africa...

That's pure unadulterated awesome-sauce, right there. (I know, I know. It's not data visualization in the case of the Africa plot. But still...) I would argue that it's easier to process the flag map in the above Brazilian case, especially for well-known flags. Anyway, I'm not slighting the Drunkneysian plot, very nice as it is. flagfillr merely offers a pretty alternative, and we all like pretty things in our lives, now don't we?

You can use flagfillr in two ways: you can supply your own data, and use the function flag_fillr_data() to make some maps, or you can make pretty pictures with flag_fillr_country(), flag_fillr_continent() and flag_fillr_state().

So with the latter option, you can do this:

flag_fillr_states("United States of America")

And this:

flag_fillr_continent("Asia")

And even this:

flag_fillr_country("Mexico")

Although I had to take out the 1000px resolution flags because of their size, so your Mexican flag won't look quite as amazing.

Be aware: some of these can take some time to plot, especially at higher resolutions and larger sizes.

Ok. The main reason I made this package is to use it with data, even though those 'picture' maps are totes awesome. To recreate something like the Brazilian economic-partners map above, you'll be using the flag_fillr_data() function, and you'll need the following:

a data.frame with a column for the base territory (where we'll map) and a column for the partners (the flags we'll put there). The simplest case is to just call these columns country (if you're plotting flags on entire countries) and partner. If you want to plot flags on states inside a country (like the Brazil example above), supply a state column. The country column is then optional. Note that the name of the country is always necessary, either supplied through country or country_col.
if you have data that you'd rather not rename, you can supply the 'partner' and 'country'/'state' columns, using partner_col, country_col and state_col. Here's how I made that map above (the code is long 'cos Brazil has lots of states...):

library(flagfillr)
library(rnaturalearth)
library(dplyr)
library(stringi)

br <- ne_states(country = "Brazil", returnclass = "sf")
trade <- tibble(
  country = "Brazil",
  state = br$name,
  partner = NA_character_) %>% 
  mutate(state = stri_trans_general(state, "Latin-ASCII"),
         partner = case_when(
          state == "Acre" ~ "Peru",
          state == "Alagoas" ~ "China",
          state == "Amapa" ~ "United States of America",
          state == "Amazonas" ~ "Argentina",
          state == "Bahia" ~ "China",
          state == "Ceara" ~ "United States of America",
          state == "Distrito Federal" ~ "China",
          state == "Espirito Santo" ~ "United States of America",
          state == "Goias" ~ "China",
          state == "Maranhao" ~ "Canada",
          state == "Mato Grosso" ~ "China",
          state == "Mato Grosso do Sul" ~ "China",
          state == "Minas Gerais" ~ "China",
          state == "Para" ~ "China",
          state == "Paraiba" ~ "United States of America",
          state == "Parana" ~ "China",
          state == "Pernambuco" ~ "Argentina",
          state == "Piaui" ~ "China",
          state == "Rio de Janeiro" ~ "China",
          state == "Rio Grande do Norte" ~ "United States of America",
          state == "Rio Grande do Sul" ~ "China",
          state == "Rondonia" ~ "Hong Kong",
          state == "Roraima" ~ "Venezuela",
          state == "Santa Catarina" ~ "United States of America",
          state == "Sao Paulo" ~ "United States of America",
          state == "Sergipe" ~ "Netherlands",
          TRUE ~ "China"
          ))

flag_fillr_data(trade, country = "Brazil", partner_col = trade$partner, 
                state_col = trade$state, type = "state", 
                resolution = "large", size = "250")

Don't be put off by all those state ==s, remember, you'll be supplying your own data. Here. I had to make it.

So there you go! In the (un)likely event you find yourself pining for flags in a ggplot2 map, flagfillr has got you covered.

Pull requests and issues are welcome. I particularly welcome any datasets of flags in png format! The plotting of state-level flags is still a bit messy, and removing islands and far-off territories could be much better. The flags are great, though (Argentina has some good ones).

I should mention that this isn't new: Paul Murrel shows how to do it with grid graphics here. And yes, ggplot2 is based on grid graphics. But I haven't seen a ggplot2 one, so... For images other than flags in plots other than maps, Giora Simchoni's ggwithimages package might be what you're looking for.

The main data wrangling function in this package is not painfully slow because the talented Daniel Falbel helped me out with purrr's map2. And I don't have distastrous 'outliers' (get it?) because of the help of the gifted Julio Trecenti. Valeu, gente!

Giora's package also reminded me of this project (I tried and failed about two years ago), so thanks Giora! And his blog post led me to this wonderful SO answer, which set me on my way. Thank you, jalapic and inscaven (I know those are not your real names).

The flags used in this repo come from Wikipedia. The US state flags come from Civil Services. Thanks to Wikipedia and the contributors of the above-linked projects for their work on making these flags available and easy to get!