library(cbsodataR)
library(tidyverse)
library(sf)
# https://www.cbs.nl/en-gb/onze-diensten/open-data/statline-as-open-data/cartography
# https://simplemaps.com/data/nl-cities
#----
<- cbs_get_data("83765NED",
data_house select=c("WijkenEnBuurten",
"Appartement_48",
"ScholenBinnen3Km_98")) %>%
mutate(WijkenEnBuurten = str_trim(WijkenEnBuurten),#boroughs
houses = Appartement_48,
schools=ScholenBinnen3Km_98)
# Retrieve data with municipal boundaries from PDOK
<- st_read("https://geodata.nationaalgeoregister.nl/cbsgebiedsindelingen/wfs?request=GetFeature&service=WFS&version=2.0.0&typeName=cbs_gemeente_2017_gegeneraliseerd&outputFormat=json")
municipalBoundaries
# obtain the coordinates
as.data.frame(st_coordinates(municipalBoundaries$geometry))
<- municipalBoundaries$statnaam
df <- as.data.frame(df)
df
<- municipalBoundaries%>%
df_xy select(statnaam,geometry) %>%
st_centroid()%>%
st_coordinates()
<- cbind(df,df_xy)%>%
state filter(df%in%c("Amsterdam","The Hague",
"Utrecht","Rotterdam",
"Eindhoven",
"Groningen","Breda",
"Apeldoorn"))
library(showtext)
library(extrafont)
#fonts()
#loadfonts()
font_add_google("Roboto Condensed","RobotoCondensed")
showtext_opts(dpi = 320)
showtext_auto(enable = T)
# Link data from Statistics Netherlands to geodata
<-
data_house %>%
municipalBoundaries left_join(data_house, by=c(statcode="WijkenEnBuurten"))
# Create a thematic map
<- data_house %>%
plot ggplot() +
geom_sf(aes(fill = schools)) +
geom_text(data=state,aes(x=X,y=Y,label=df),
color="gold",fontface="bold",family="RobotoCondensed")+
scale_fill_gradient(low="#c97d2c",high = "darkblue")+
labs(title = "The Netherlands: Hurban and Rural",
subtitle="Schools near by...",
caption="Datasource: cbs.nl opendata - #30DayMapChallenge\nGraphics: Federica Gazzelloni\n",
fill = "Schools") +
coord_sf()+
theme_void()+
theme(text = element_text(color="gold",face="bold",family="RobotoCondensed"),
plot.background = element_rect(color = "grey20",fill="grey60",size=2),
legend.position = c(0.1,0.08),
plot.caption = element_text(hjust=0.5,size=11),
plot.caption.position = "panel",
plot.title = element_text(size=25,hjust=0.2,vjust=-1.5),
plot.subtitle = element_text(size=18,hjust=0.06,vjust=-1))
library(cowplot)
<- cowplot::ggdraw(plot)+
final draw_label("The Hague",x=0.4,y=0.5,color="gold",
fontface = "bold",fontfamily="RobotoCondensed")
Overview
This is The Netherlands: Hurban and Rural
and Schools near by...
, data is from cbs.nl
opendata.
Save the final plot
::agg_png(here::here("R_general_resources/30DayMapChallenge/day15_urban_rural/urban_rural.png"),
raggres = 320, width = 12, height = 8, units = "in")
finaldev.off()
More about data for Holland capitals.
library(readr)
<- read_csv("R_general_resources/30DayMapChallenge/day15_urban_rural/nl.csv")
nl
%>%count(city,population)%>%arrange(-population)
nl
%>%
nlfilter(!lat<20)%>%
ggplot(aes(x=lng,y=lat))+
geom_point()+
::geom_text_repel(aes(label=capital)) ggrepel