#geobr and #censob by @UrbanDemog are terrific #rstats packages! Saw a fun vignette and thought I try making it 3D because why not? Gratuitous, possibly. Pretty, I think so.

Here's the proportion of households in Brasil connected to a sewage network in 2010.

O setor censitário de uma reserva indígena rodeada de plantação de soja.

Essa terra é da etnia Ofayé, e pode ser baixada do #geobr com 3 linhas de codigo no #rstats

t <- geobr::read_indigenous_land()
t2 <- subset(t, etnia_nome == "Ofayé")
mapview::mapview(t2)
---
RT @esquinadobrasil
Municipio: Brasilândia - MS
Setor censitário: 500230805000010
População: 58
Área (Km2): 5.02
Densidade (hab/Km2): 11.54
Zona: rural
🗺 http://maps.g…
https://twitter.com/esquinadobrasil/status/1630900143393234945

RT @UrbanDemog@twitter.com

@Demografia_CSIC@twitter.com @ipeaonline@twitter.com @CSchmert@twitter.com Data update. The #geobr package now includes the shapes of risk areas prone to landslides and floods in Brazil (source: IBGE/Cemaden). Download the data with a line of code:

d <- read_disaster_risk_area(year=2010)

more info at: https://github.com/ipeaGIT/geobr

🐦🔗: https://twitter.com/UrbanDemog/status/1176985754972696576

RT @UrbanDemog@twitter.com

The #geobr package in #rstats is probably the easiest and fastest way to download shapefiles and official spatial data sets of Brazil.
👉 https://github.com/ipeaGIT/geobr

This thread will periodically bring news with updates of the package. RT or Like it to stay tuned!

🐦🔗: https://twitter.com/UrbanDemog/status/1145694001837875201