Taller_ggmap2
Anahí Martín
25 de marzo de 2017
1. Bloque de inicializacion de librerias
ejecutar el siguiente código si no se dispone del paquete ggmap: devtools::install_github(“dkahle/ggmap”)
ejecutar el siguiente código si al ejecutar los comandos aparecen errores relacionados con el environment: devtools::install_github("hadley/ggplot2@v2.2.0")
library(ggmap)## Loading required package: ggplot2## Google Maps API Terms of Service: http://developers.google.com/maps/terms.## Please cite ggmap if you use it: see citation("ggmap") for details.2. Bloque de parametros iniciales
setwd("~/Desktop/Taller")3. Bloque de carga de informacion
Viviendas <- read.csv("listings.csv")7. Bloque de distancias
desde=c("El Arte de Medir, Calle Cundinamarca, Madrid")
hasta=c("Medialab-Prado, Calle de la Alameda, Madrid")
mapdist(desde, hasta, mode = "driving")## Source : https://maps.googleapis.com/maps/api/distancematrix/json?origins=El%20Arte%20de%20Medir%2C%20Calle%20Cundinamarca%2C%20Madrid&destinations=Medialab-Prado%2C%20Calle%20de%20la%20Alameda%2C%20Madrid&mode=driving&language=en-EN## from
## 1 El Arte de Medir, Calle Cundinamarca, Madrid
## to m km miles
## 1 Medialab-Prado, Calle de la Alameda, Madrid 17658 17.658 10.97268
## seconds minutes hours
## 1 1227 20.45 0.3408333mapdist(desde, hasta, mode = "bicycling")## Source : https://maps.googleapis.com/maps/api/distancematrix/json?origins=El%20Arte%20de%20Medir%2C%20Calle%20Cundinamarca%2C%20Madrid&destinations=Medialab-Prado%2C%20Calle%20de%20la%20Alameda%2C%20Madrid&mode=bicycling&language=en-EN## from
## 1 El Arte de Medir, Calle Cundinamarca, Madrid
## to m km miles
## 1 Medialab-Prado, Calle de la Alameda, Madrid 11742 11.742 7.296479
## seconds minutes hours
## 1 2610 43.5 0.725mapdist(desde, hasta, mode = "walking")## Source : https://maps.googleapis.com/maps/api/distancematrix/json?origins=El%20Arte%20de%20Medir%2C%20Calle%20Cundinamarca%2C%20Madrid&destinations=Medialab-Prado%2C%20Calle%20de%20la%20Alameda%2C%20Madrid&mode=walking&language=en-EN## from
## 1 El Arte de Medir, Calle Cundinamarca, Madrid
## to m km miles
## 1 Medialab-Prado, Calle de la Alameda, Madrid 10194 10.194 6.334552
## seconds minutes hours
## 1 7706 128.4333 2.140556EJERCICIO: Calcular la distancia entre Atocha y Chamartin en bicicleta, caminando y en coche
desde=c("Estación de Madrid Atocha, Plaza Emperador Carlos V, Madrid")
hasta=c("Chamartín, Madrid")
mapdist(desde, hasta, mode = "driving")## Source : https://maps.googleapis.com/maps/api/distancematrix/json?origins=Estaci%C3%B3n%20de%20Madrid%20Atocha%2C%20Plaza%20Emperador%20Carlos%20V%2C%20Madrid&destinations=Chamart%C3%ADn%2C%20Madrid&mode=driving&language=en-EN## from
## 1 Estación de Madrid Atocha, Plaza Emperador Carlos V, Madrid
## to m km miles seconds minutes hours
## 1 Chamartín, Madrid 11356 11.356 7.056618 1073 17.88333 0.2980556mapdist(desde, hasta, mode = "bicycling")## Source : https://maps.googleapis.com/maps/api/distancematrix/json?origins=Estaci%C3%B3n%20de%20Madrid%20Atocha%2C%20Plaza%20Emperador%20Carlos%20V%2C%20Madrid&destinations=Chamart%C3%ADn%2C%20Madrid&mode=bicycling&language=en-EN## from
## 1 Estación de Madrid Atocha, Plaza Emperador Carlos V, Madrid
## to m km miles seconds minutes hours
## 1 Chamartín, Madrid 6888 6.888 4.280203 1590 26.5 0.4416667mapdist(desde, hasta, mode = "walking")## Source : https://maps.googleapis.com/maps/api/distancematrix/json?origins=Estaci%C3%B3n%20de%20Madrid%20Atocha%2C%20Plaza%20Emperador%20Carlos%20V%2C%20Madrid&destinations=Chamart%C3%ADn%2C%20Madrid&mode=walking&language=en-EN## from
## 1 Estación de Madrid Atocha, Plaza Emperador Carlos V, Madrid
## to m km miles seconds minutes hours
## 1 Chamartín, Madrid 6362 6.362 3.953347 5081 84.68333 1.411389- Bloque de posicionamiento de objetos
ArtedeMedir <- geocode("El Arte de Medir, Calle Cundinamarca, Madrid",source = "google")## Source : https://maps.googleapis.com/maps/api/geocode/json?address=El%20Arte%20de%20Medir%2C%20Calle%20Cundinamarca%2C%20Madridmap.ArtedeMedir <- get_map(location = as.numeric(ArtedeMedir),zoom = 18,maptype = "roadmap")## Source : https://maps.googleapis.com/maps/api/staticmap?center=40.470838,-3.631555&zoom=18&size=640x640&scale=2&maptype=roadmap&language=en-ENstr(ArtedeMedir)## 'data.frame': 1 obs. of 2 variables:
## $ lon: num -3.63
## $ lat: num 40.5ggmap(map.ArtedeMedir) + geom_point(aes(x = lon, y = lat),
data = ArtedeMedir, colour = 'red',
size = 4)
str(Viviendas)## 'data.frame': 7446 obs. of 16 variables:
## $ id : int 7328003 6289024 3778195 7056183 6847125 3453225 336869 5876946 316712 6584180 ...
## $ name : Factor w/ 7251 levels " Habitacion silenciosa ",..: 1779 5377 6958 5412 4151 4291 2858 5912 50 3977 ...
## $ host_id : int 9205789 3305388 10940437 19558259 21039137 1528801 1713524 16859206 162701 34212673 ...
## $ host_name : Factor w/ 1821 levels "","(email hidden)",..: 64 504 64 1001 349 500 1378 1718 1304 1208 ...
## $ neighbourhood_group : Factor w/ 21 levels "Arganzuela","Barajas",..: 4 4 4 4 4 4 4 4 4 4 ...
## $ neighbourhood : Factor w/ 126 levels "Abrantes","Acacias",..: 83 83 83 83 83 83 83 83 83 83 ...
## $ latitude : num 40.4 40.4 40.4 40.4 40.4 ...
## $ longitude : num -3.71 -3.72 -3.71 -3.71 -3.71 ...
## $ room_type : Factor w/ 3 levels "Entire home/apt",..: 1 2 3 2 2 2 2 2 2 2 ...
## $ price : int 60 25 22 45 37 19 55 95 25 25 ...
## $ minimum_nights : int 1 1 1 1 2 3 2 1 2 1 ...
## $ number_of_reviews : int 3 1 12 0 3 0 75 2 60 3 ...
## $ last_review : Factor w/ 420 levels "","2011-11-26",..: 409 350 401 1 338 1 415 332 406 373 ...
## $ reviews_per_month : num 3 0.42 0.91 NA 1 NA 1.81 0.44 1.38 0.77 ...
## $ calculated_host_listings_count: int 2 1 11 1 1 12 2 6 1 5 ...
## $ availability_365 : int 343 330 347 335 0 26 318 302 327 295 ...Madrid=c(-3.6883432,40.453054)
map.Madrid <- get_map(location = Madrid)## Source : https://maps.googleapis.com/maps/api/staticmap?center=40.453054,-3.688343&zoom=10&size=640x640&scale=2&maptype=terrain&language=en-ENggmap(map.Madrid)+ geom_point(aes(x = longitude, y = latitude),
data = Viviendas, colour = 'red', alpha=1)
9. Bloque de consulta de consumo de API
geocodeQueryCheck()## 2499 geocoding queries remaining.10. Bloque de representacion de variables categoricas
Viviendas <- read.csv("listings.csv")
str(Viviendas)## 'data.frame': 7446 obs. of 16 variables:
## $ id : int 7328003 6289024 3778195 7056183 6847125 3453225 336869 5876946 316712 6584180 ...
## $ name : Factor w/ 7251 levels " Habitacion silenciosa ",..: 1779 5377 6958 5412 4151 4291 2858 5912 50 3977 ...
## $ host_id : int 9205789 3305388 10940437 19558259 21039137 1528801 1713524 16859206 162701 34212673 ...
## $ host_name : Factor w/ 1821 levels "","(email hidden)",..: 64 504 64 1001 349 500 1378 1718 1304 1208 ...
## $ neighbourhood_group : Factor w/ 21 levels "Arganzuela","Barajas",..: 4 4 4 4 4 4 4 4 4 4 ...
## $ neighbourhood : Factor w/ 126 levels "Abrantes","Acacias",..: 83 83 83 83 83 83 83 83 83 83 ...
## $ latitude : num 40.4 40.4 40.4 40.4 40.4 ...
## $ longitude : num -3.71 -3.72 -3.71 -3.71 -3.71 ...
## $ room_type : Factor w/ 3 levels "Entire home/apt",..: 1 2 3 2 2 2 2 2 2 2 ...
## $ price : int 60 25 22 45 37 19 55 95 25 25 ...
## $ minimum_nights : int 1 1 1 1 2 3 2 1 2 1 ...
## $ number_of_reviews : int 3 1 12 0 3 0 75 2 60 3 ...
## $ last_review : Factor w/ 420 levels "","2011-11-26",..: 409 350 401 1 338 1 415 332 406 373 ...
## $ reviews_per_month : num 3 0.42 0.91 NA 1 NA 1.81 0.44 1.38 0.77 ...
## $ calculated_host_listings_count: int 2 1 11 1 1 12 2 6 1 5 ...
## $ availability_365 : int 343 330 347 335 0 26 318 302 327 295 ...table(Viviendas$room_type)##
## Entire home/apt Private room Shared room
## 4580 2760 106Madrid=c(-3.6883432,40.453054)
map.Madrid <- get_map(location = Madrid,zoom=12,maptype = "satellite")## Source : https://maps.googleapis.com/maps/api/staticmap?center=40.453054,-3.688343&zoom=12&size=640x640&scale=2&maptype=satellite&language=en-ENggmap(map.Madrid)+ geom_point(aes(x = longitude, y = latitude),
data = Viviendas, colour = 4+as.numeric(Viviendas$room_type))## Warning: Removed 74 rows containing missing values (geom_point).
Bernabeu=c(-3.7083759,40.4169335)
map.Bernabeu <- get_map(location = Bernabeu,zoom = 16,maptype = "satellite")## Source : https://maps.googleapis.com/maps/api/staticmap?center=40.416933,-3.708376&zoom=16&size=640x640&scale=2&maptype=satellite&language=en-ENggmap(map.Bernabeu) + geom_point(aes(x = longitude, y = latitude),
data = Viviendas, colour =4+as.numeric(Viviendas$room_type))## Warning: Removed 6149 rows containing missing values (geom_point).
EJERCICIO: Representar en un mapa tipo satellite las viviendas cercanas a Sol con Zoom 18
Sol=c(-3.6883432,40.453054)
map.Sol <- get_map(location = Sol,zoom = 18,maptype = "satellite")## Source : https://maps.googleapis.com/maps/api/staticmap?center=40.453054,-3.688343&zoom=18&size=640x640&scale=2&maptype=satellite&language=en-ENggmap(map.Sol) + geom_point(aes(x = longitude, y = latitude),
data = Viviendas, colour = 4+as.numeric(Viviendas$room_type))## Warning: Removed 7445 rows containing missing values (geom_point).
11. Bloque de representacion de variables continuas
str(Viviendas)## 'data.frame': 7446 obs. of 16 variables:
## $ id : int 7328003 6289024 3778195 7056183 6847125 3453225 336869 5876946 316712 6584180 ...
## $ name : Factor w/ 7251 levels " Habitacion silenciosa ",..: 1779 5377 6958 5412 4151 4291 2858 5912 50 3977 ...
## $ host_id : int 9205789 3305388 10940437 19558259 21039137 1528801 1713524 16859206 162701 34212673 ...
## $ host_name : Factor w/ 1821 levels "","(email hidden)",..: 64 504 64 1001 349 500 1378 1718 1304 1208 ...
## $ neighbourhood_group : Factor w/ 21 levels "Arganzuela","Barajas",..: 4 4 4 4 4 4 4 4 4 4 ...
## $ neighbourhood : Factor w/ 126 levels "Abrantes","Acacias",..: 83 83 83 83 83 83 83 83 83 83 ...
## $ latitude : num 40.4 40.4 40.4 40.4 40.4 ...
## $ longitude : num -3.71 -3.72 -3.71 -3.71 -3.71 ...
## $ room_type : Factor w/ 3 levels "Entire home/apt",..: 1 2 3 2 2 2 2 2 2 2 ...
## $ price : int 60 25 22 45 37 19 55 95 25 25 ...
## $ minimum_nights : int 1 1 1 1 2 3 2 1 2 1 ...
## $ number_of_reviews : int 3 1 12 0 3 0 75 2 60 3 ...
## $ last_review : Factor w/ 420 levels "","2011-11-26",..: 409 350 401 1 338 1 415 332 406 373 ...
## $ reviews_per_month : num 3 0.42 0.91 NA 1 NA 1.81 0.44 1.38 0.77 ...
## $ calculated_host_listings_count: int 2 1 11 1 1 12 2 6 1 5 ...
## $ availability_365 : int 343 330 347 335 0 26 318 302 327 295 ...hist(Viviendas$price)
hist(log(Viviendas$price))
Madrid=c(-3.6883432,40.453054)
map.Madrid <- get_map(location = Madrid,zoom=12,maptype = "satellite")## Source : https://maps.googleapis.com/maps/api/staticmap?center=40.453054,-3.688343&zoom=12&size=640x640&scale=2&maptype=satellite&language=en-ENggmap(map.Madrid)+ geom_point(aes(x = longitude, y = latitude,col = room_type,size=price) ,
data = Viviendas)## Warning: Removed 74 rows containing missing values (geom_point).
Bernabeu=c(-3.6883432,40.453054)
map.Bernabeu <- get_map(location = Bernabeu,zoom = 16,maptype = "satellite")## Source : https://maps.googleapis.com/maps/api/staticmap?center=40.453054,-3.688343&zoom=16&size=640x640&scale=2&maptype=satellite&language=en-ENggmap(map.Bernabeu) + geom_point(aes(x = longitude, y = latitude,col = room_type,size=price) ,data = Viviendas)## Warning: Removed 7409 rows containing missing values (geom_point).
ggmap(map.Bernabeu) + geom_point(aes(x = longitude, y = latitude,col = room_type,size=price) ,data = Viviendas,shape=8)## Warning: Removed 7409 rows containing missing values (geom_point).