top.places <- names(rev(sort(table(df$publication.place)))[1:10])
library(dplyr)
mapdata <- df %>%
filter(publication.place %in% top.places) %>%
group_by(publication.place, latitude, longitude) %>%
tally() %>%
filter(!is.na(latitude) & !is.na(longitude))
region <- "UK"
mymap <- get_map(location=geobox(region), source="google", maptype="terrain")
p <- ggmap(mymap) + theme(legend.position="none")
# Pick the investigated period (sliding window)
# Sum up the years within this sliding window for each element
dfw <- mapdata %>%
group_by(publication.place, latitude, longitude) %>%
summarize(n = sum(n))
p <- p + geom_point(data = dfw,
aes(x = longitude, y = latitude,
size = log10(1+n)),
color = "blue", alpha = 0.8) +
scale_size(range = c(5,30))
png("figure/UK1.png")
print(p)
dev.off()
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