**Freakonometrics » R-english**, and kindly contributed to R-bloggers)

This week, I mentioned a series of maps, on Twitter,

```
```some minimalist maps http://t.co/YCNPf3AR9n (poke @visionscarto) pic.twitter.com/Ip9Tylsbkv

— Arthur Charpentier (@freakonometrics) 2 Septembre 2015

Friday evening, just before leaving the office to pick-up the kids after their first week back in class, Matthew Champion (aka **@matthewchampion**) sent me an email, asking for more details. He wanted to know if I did produce those graphs, and if he could mention then, in a post. The truth is, I have no idea who produced those graphs, but I told him one can easily reproduce them. For instance, for the **cities**, in R, use

> library(maps) > data("world.cities") > plot(world.cities$lon,world.cities$lat, + pch=19,cex=.7,axes=FALSE,xlab="",ylab="")

It is possible to get a more minimalist one by plotting only cities with more than 100,000 unhabitants, e.g.,

> world.cities2 = world.cities[ + world.cities$pop>100000,] > plot(world.cities2$lon,world.cities2$lat, + pch=19,cex=.7,axes=FALSE,xlab="",ylab="")

For the **airports**, it was slightly more complex since on http://openflights.org/data.html#airport, 6,977 airports are mentioned. But on http://www.naturalearthdata.com/, I found another dataset with only 891 airports.

> library(maptools) > shape <- readShapePoints( + "~/data/airport/ne_10m_airports.shp") > plot(shape,pch=19,cex=.7)

On the same website, one can find a dataset for **ports**,

> shape <- readShapePoints( + "~/data/airport/ne_10m_ports.shp") > plot(shape,pch=19,cex=.7)

This is for graphs based on points. For those based on lines, for instance **rivers**, shapefiles can be downloaded from https://github.com/jjrom/hydre/tree/, and then, use

> require(maptools) > shape <- readShapeLines( + "./data/river/GRDC_687_rivers.shp") > plot(shape,col="blue")

For **roads**, the shapefile can be downloaded from http://www.naturalearthdata.com/

> shape <- readShapeLines( + "./data/roads/ne_10m_roads.shp") > plot(shape,lwd=.5)

Last, but not least, for lakes, we need the polygons,

> shape <- readShapePoly( + "./data/lake/ne_10m_lakes.shp") > plot(shape,col="blue",border="blue",lwd=2)

Nice, isn’t it? See *See the world differently with these minimalist maps* for Matthew Champion‘s post.

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