Author: YJ Choi
Date: 2019-05-25

1. Data access

Download Google map my data. Save it in your working directory. See this for how to extract map data: https://webapps.stackexchange.com/questions/16177/is-there-a-way-to-export-my-starred-locations-from-google-maps

setwd("C:/Users/YoonJoung Choi/Dropbox/0 Project/Map")
dir()

## [1] "Added dishes, products, activities.json"
## [2] "Labeled places.json"                    
## [3] "MapTopia.html"                          
## [4] "MapTopia.rmd"                           
## [5] "Reviews.json"                           
## [6] "rsconnect"                              
## [7] "Saved Places.json"

2. Data wranling part I

Inspect data, gather only relevant information, and put them into a dataframe.

suppressPackageStartupMessages(library(jsonlite))
myjson<-fromJSON("Saved places.json")
jsondta<-as.data.frame(myjson)

dim(jsondta)
names(jsondta)
head(jsondta)

geometry<-jsondta[ , 2]
#str(geometry)

properties<-jsondta[ , 3]
#str(properties)

location<-properties[ , 2]
#str(location)
head(location)

geo<-location[ , 6]
#str(geo)
head(geo)

    location<-location[ , 1:5]
    url<-as.data.frame(properties[ , 1])
        colnames(url)[1] <- "url"
    title<-as.data.frame(properties[ , 4])
        colnames(title)[1] <- "title"
    str(location)
    str(title)    
    str(url)    
    str(geo)
    #confirm there is no nested dataframes
    
suppressPackageStartupMessages(library(dplyr))
dtaset<-bind_cols(location, url, title, geo)

3. Data wranling part II

Clean data, including selecting a specific area based on latitute and longitude. The area selection can be done with country name, in theory, but it is often missing for names of city/town, etc (see below).

#check what you have
colnames(dtaset)<-tolower(names(dtaset))
head(dtaset)

   latitude  longitude                                       address
1 -0.954457 -90.964147                                          <NA>
2      <NA>       <NA>              Puerto Baquerizo Moreno, Ecuador
3      <NA>       <NA> Carlos Mora, Puerto Baquerizo Moreno, Ecuador
4 -0.743292 -90.315689                                          <NA>
5      <NA>       <NA>                                       Ecuador
6 -1.053483 -77.548439                                          <NA>
               business name country code
1                       <NA>         <NA>
2 Airport Isla San Cristobal           EC
3               Hostal Gosén           EC
4                       <NA>         <NA>
5          GAIA Amazon Lodge           EC
6                       <NA>         <NA>
                                                                                            url
1 http://maps.google.com/?q=Puerto+Villamil,+Ecuador&ftid=0x9aabeb96e0ec8dbb:0x64746d53fc14dc0f
2                                              http://maps.google.com/?cid=17614056007148402264
3                                               http://maps.google.com/?cid=3726830005299073107
4    http://maps.google.com/?q=Puerto+Ayora,+Ecuador&ftid=0x9aaa5d43fb94bf6b:0x9841fa352c866135
5                                               http://maps.google.com/?cid=7746604468468777656
6          http://maps.google.com/?q=Ahuano,+Ecuador&ftid=0x91d6c83d6d0de0bb:0x48bdf34f4f103803
                       title  latitude1  longitude1
1   Puerto Villamil, Ecuador       <NA>        <NA>
2 Airport Isla San Cristobal -0.9086996 -89.6162348
3               Hostal Gosén -0.9003580 -89.6087425
4      Puerto Ayora, Ecuador       <NA>        <NA>
5          GAIA Amazon Lodge -1.0308977 -77.5269610
6            Ahuano, Ecuador       <NA>        <NA>

#clean
suppressPackageStartupMessages(library(Hmisc))
dta<- dtaset %>% 
    rename(country = 'country code') %>% 
    rename(business = 'business name') %>% 
    mutate(
        latitude = ifelse(is.na(latitude)==TRUE, latitude1, latitude) , 
        longitude = ifelse(is.na(longitude)==TRUE, longitude1, longitude) ,
        latitude = as.numeric(as.character(latitude)),
        longitude = as.numeric(as.character(longitude))
        ) %>% 
    select( -latitude1, -longitude1) %>% 
    filter( latitude<10 & longitude<0 ) %>% 
    filter( country=="PE" | country=="EC" | is.na(country)==TRUE)

#Now, check cleaned data. 
head(dta)

    latitude longitude                                       address
1 -0.9544570 -90.96415                                          <NA>
2 -0.9086996 -89.61623              Puerto Baquerizo Moreno, Ecuador
3 -0.9003580 -89.60874 Carlos Mora, Puerto Baquerizo Moreno, Ecuador
4 -0.7432920 -90.31569                                          <NA>
5 -1.0308977 -77.52696                                       Ecuador
6 -1.0534830 -77.54844                                          <NA>
                    business country
1                       <NA>    <NA>
2 Airport Isla San Cristobal      EC
3               Hostal Gosén      EC
4                       <NA>    <NA>
5          GAIA Amazon Lodge      EC
6                       <NA>    <NA>
                                                                                            url
1 http://maps.google.com/?q=Puerto+Villamil,+Ecuador&ftid=0x9aabeb96e0ec8dbb:0x64746d53fc14dc0f
2                                              http://maps.google.com/?cid=17614056007148402264
3                                               http://maps.google.com/?cid=3726830005299073107
4    http://maps.google.com/?q=Puerto+Ayora,+Ecuador&ftid=0x9aaa5d43fb94bf6b:0x9841fa352c866135
5                                               http://maps.google.com/?cid=7746604468468777656
6          http://maps.google.com/?q=Ahuano,+Ecuador&ftid=0x91d6c83d6d0de0bb:0x48bdf34f4f103803
                       title
1   Puerto Villamil, Ecuador
2 Airport Isla San Cristobal
3               Hostal Gosén
4      Puerto Ayora, Ecuador
5          GAIA Amazon Lodge
6            Ahuano, Ecuador

table(dta$country)


EC PE 
 5 17

#check data without country. They also do not have business. These are all names of city/town. These can be dropped.  
check<- dta %>% filter( is.na(country)==TRUE)  
check

4. Putting them on a map

Using leaflet! Popup content can be customized. Refine the map as needed!

google<- "http://mt0.google.com/vt/lyrs=m&hl=en&x={x}&y={y}&z={z}&s=Ga"

df <- data.frame(latitude = dta$latitude, 
                 longitude = dta$longitude, 
                 popup = dta$title)

suppressPackageStartupMessages(library(leaflet))
df %>% 
  leaflet() %>%
  addTiles(urlTemplate = google) %>%
  addMarkers(popup=df$popup)

Sharing My Google Map Data for Travel with Friends

1. Data access

2. Data wranling part I

3. Data wranling part II

4. Putting them on a map