I am trying to map my data on a world map according to the number of times the country has been listed.
Let's say I have this dataset
company country ...
A Germany
B China
C Argentina
D United States of America
E Germany
.....
According to how often in the df the country is listed I want a bigger or smaller bubble to "rank" that.
I found a way to plot it with ggplot2 but coordinates were necessary for that and since this is concerning the entire country I was wondering if there is an easier way to plot this without needing to add and search for long & lat:
mdat <- map_data('world')
str(mdat)
ggplot() + geom_polygon(dat=mdat, aes(long, lat, group=group), fill="grey50") + geom_point(data=un_all_years, aes(x=Lat, y=Lon, map_id=Location), col="red") mapBubbles(dF=un_all_years, nameZColour="Location",oceanCol="lightblue", landCol="wheat", addLegend=FALSE)
A further advanced question on this behalf is also: If I have an extra information in my data set that I would like to also include in my world map like industry sector, how could I differentiate that (let's say the bubbles will take the according colour to sector still differing in size!)
company country industry sector ...
A Germany a
B China a
C Argentina b
D USA c
E Germany d
.....
It would be nice if the result would look something like this in a simplified way:
