Mapas

apiKey<-"AIzaSyBPxhDW9_bUJ1juxXEGvY_QcNIZNJPUy7A" #la llave para que funcione la appi de google
library(ggplot2)

## Registered S3 methods overwritten by 'tibble':
##   method     from  
##   format.tbl pillar
##   print.tbl  pillar

#install.packages("ggmap")
library(ggmap)

## Warning: package 'ggmap' was built under R version 4.0.5

## Google's Terms of Service: https://cloud.google.com/maps-platform/terms/.

## Please cite ggmap if you use it! See citation("ggmap") for details.

register_google(apiKey) #me registro en google

qmap(c(-76.5,3.43),zoom=12,9, maptype="hybrid")

## Source : https://maps.googleapis.com/maps/api/staticmap?center=3.43,-76.5&zoom=12&size=640x640&scale=2&maptype=hybrid&language=en-EN&key=xxx

#Cargar base de datos
library(readr)

MIO_STOPS <- read_delim("MIO_STOPS.txt","\t", escape_double = FALSE, trim_ws = TRUE)

## Parsed with column specification:
## cols(
##   STOPID = col_double(),
##   PLANVERSIONID = col_double(),
##   SHORTNAME = col_character(),
##   LONGNAME = col_character(),
##   GPS_X = col_double(),
##   GPS_Y = col_double(),
##   DECIMALLONGITUDE = col_double(),
##   DECIMALLATITUDE = col_double(),
##   PASSANGERS_NUM = col_double(),
##   TYPE_BUS = col_double()
## )

#Adicionar una columna de agrupamiento

k<-7
nIter<-100

grupos<-kmeans(MIO_STOPS[,c(7,8)],k,iter.max = nIter,nstart = 1)

#pegar el cluster a la base de MIO_STOPS
MIO_STOPS$grupos<-grupos$cluster


#poligono
cluster<-subset(MIO_STOPS,MIO_STOPS$grupos==1)
indicesC1<-chull(cluster[,c(7,8)])
poligono<-MIO_STOPS[indicesC1,]


#mapa<-ggplot(MIO_STOPS, aes(DECIMALLONGITUDE, DECIMALLATITUDE))

city<-get_map(c(-76.5,3.43),zoom=12)

## Source : https://maps.googleapis.com/maps/api/staticmap?center=3.43,-76.5&zoom=12&size=640x640&scale=2&maptype=terrain&language=en-EN&key=xxx

mapa<-ggmap(city)
mapa<-mapa+geom_point(data=MIO_STOPS,aes(x=DECIMALLONGITUDE,y=DECIMALLATITUDE),
                      color=MIO_STOPS$grupos,size=MIO_STOPS$PASSANGERS_NUM*0.02 )

mapa

#Nota: El de polígono se queda pendiente.