CLASE-05

library(tidyverse)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.5.1     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.1
## ✔ purrr     1.0.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(sf)

## Linking to GEOS 3.11.0, GDAL 3.5.3, PROJ 9.1.0; sf_use_s2() is TRUE

partidos_amba <- st_read("data/partidos_amba/partidos_amba.shp")

## Reading layer `partidos_amba' from data source 
##   `/Users/angiescetta/Desktop/FEPP-DATOS-01/data/partidos_amba/partidos_amba.shp' 
##   using driver `ESRI Shapefile'
## Simple feature collection with 48 features and 3 fields
## Geometry type: MULTIPOLYGON
## Dimension:     XY
## Bounding box:  xmin: -59.3392 ymin: -35.23893 xmax: -57.70946 ymax: -34.23007
## Geodetic CRS:  WGS 84

ggplot()+
  geom_sf(data=partidos_amba, aes(fill=area_km2))+
  scale_fill_viridis_c(direction=-1)+
  labs(title="Partidos del AMBA")

ggplot()+
  geom_sf(data=partidos_amba, aes(fill=provincia))

ggplot()+
  geom_sf(data=partidos_amba, aes(fill=nombre), show.legend = FALSE)

datos_amba <- read.csv("data/amba_properati2021.csv",
                       encoding="latin1")

datos_amba_venta <- datos_amba %>%
  filter(operation_type=="Venta") %>%
  group_by(partido) %>%
  summarise(cantidad=n(),
            valor_m2=mean(price/surface_covered))

partidos_amba <- left_join(partidos_amba, datos_amba_venta, by=c("nombre"="partido"))

ggplot()+
  geom_sf(data=partidos_amba, aes(fill=valor_m2))+
  scale_fill_viridis_c(direction=-1)+
  labs(title="Partidos del AMBA")

ggplot()+
  geom_sf(data=partidos_amba, aes(fill=cantidad))+
  scale_fill_distiller(palette = "Spectral")+
  labs(title="Partidos del AMBA")

ggplot()+
  geom_sf(data=partidos_amba, aes(fill=cantidad/area_km2))+
  scale_fill_distiller(palette = "Spectral")+
  labs(title="Partidos del AMBA")

ggplot()+
  geom_sf(data=partidos_amba)+
  geom_sf(data=filter(partidos_amba, cantidad>=300), aes(fill=cantidad/area_km2))+
  scale_fill_distiller(palette = "Spectral")+
  labs(title="Partidos del AMBA")

A continuación…

ggplot()+
  geom_sf(data=filter(partidos_amba, provincia=="CABA"), aes(fill=cantidad/area_km2))+
  geom_sf_text(data=filter(partidos_amba, provincia=="CABA"), aes(label=nombre), size=1.5)+
  scale_fill_distiller(palette = "Spectral")+
  labs(title="Partidos del AMBA")

## Warning in st_point_on_surface.sfc(sf::st_zm(x)): st_point_on_surface may not
## give correct results for longitude/latitude data