Data science art

# Variables to input
  google_key <- "YOUR_GOOGLE_API_KEY"
  # bounding box limits for map
  top_lat <- 47.565
  bottom_lat <- 47.54
  left_lng <- 7.57
  right_lng <- 7.61
  zoom_level=13 # resolution of map
  # steps for grid
  steps = 20
  # thing to search for
  type=bar
  # see link for full list
  # https://developers.google.com/places/supported_types
{% endhighlight %}

## Functions

### Pull nearest amenity

This function will take the location frame you give it, make a grid (the number of points defined by `steps`) and get the closest type of place you are looking for.

{% highlight r %}
jb_pullnearby <- function(
  GOOGLE_API_KEY = google_key,
  # Map corners
  lat_NW = 47.56232,
  lng_NW = 7.57373,
  lat_SE = 47.54263,
  lng_SE = 7.60274,
  steps=100,
  type="restaurant"
){
  library(jsonlite)
  library(dplyr)

  # 100 steps left and 100 down
  lat_incr = (lat_SE-lat_NW)/steps
  lng_incr = (lng_SE-lng_NW)/steps
  # Start in the northwest and iterate to the southeast
  lat_curr = lat_NW
  lng_curr = lng_NW

  # clear output
  data_output <- NULL

  # Open loop

  for(i_lat in 1:steps){
    for(i_lng in 1:steps){
      # current location
      curr_location = paste0(lat_curr,",",lng_curr)
      # url to call api
      url <- paste0('https://maps.googleapis.com/maps/api/place/nearbysearch/json?location=',
                    curr_location,
                    '&key=',
                    GOOGLE_API_KEY,
                    '&rankby=distance&types=',
                    type)
      response <- fromJSON(txt=url)$results
      if(!is.null(nrow(response))){
      temp_location <- response$geometry$location
      temp_info <- response %>%
        select(place_id,icon,name,vicinity)
      temp_data <- cbind(temp_location,temp_info)
      # Make line of data from response
        # note rankby means sorted by proxomity!
      temp_data <- temp_data %>%
        mutate(
          n = 1:n(),
          loc_lat = lat,
          loc_lng = lng,
          lat = lat_curr,
          lng = lng_curr,
          i_lat = i_lat,
          i_lng = i_lng
        )
      # add data
      data_output <- rbind(data_output,temp_data)
      }
      # Move along one lng increment
      lng_curr <- lng_curr+lng_incr
    } # longitiude loop
    # reset longitude
    lng_curr = lng_NW
    # Move along one lat increment
    lat_curr <- lat_curr+lat_incr
  } # latitude loop
  return(data_output)
} # close function

jb_googledist <- function(
  origin=paste0(lat,",",lng),
  destination=paste0(lat,",",lng),
  GOOGLE_API_KEY=google_key){
  library(XML)
  library(RCurl)
  xml.url <- paste0(
    'https://maps.googleapis.com/maps/api/distancematrix/xml?origins=',
    origin,'&destinations=',
    destination,
    '&mode=walking&key=',
    GOOGLE_API_KEY,
    '&sensor=false')
  xmlfile <- xmlParse(getURL(xml.url))
  time <- xmlValue(xmlChildren(xpathApply(xmlfile,"//duration")[[1]])$value)
  time <- round(as.numeric(time)/60,1)
  dist <- xmlValue(xmlChildren(xpathApply(xmlfile,"//distance")[[1]])$value)
  distance <- as.numeric(dist)
  output <- data.frame(time=time,distance=distance)
  return(output)
}

# Get the nearest
data_locations <- jb_pullnearby(
  GOOGLE_API_KEY = google_key,
  # Map corners
  lat_NW = top_lat,
  lng_NW = left_lng,
  lat_SE = bottom_lat,
  lng_SE = right_lng,
  steps=steps,
  type=type
)

  # Drop to closest restaurant
  dataset <- data_locations %>%
    filter(n==1)

# Get google distance
  # empty results df
  dataset_distances <- NULL
  # start loop over data
  for(i in 1:nrow(dataset)){
    # current iteration
    i_origin = paste0(dataset$lat[i],",",dataset$lng[i])
    i_destination = paste0(dataset$loc_lat[i],",",dataset$loc_lng[i])
    # get distances
    i_distance <- jb_googledist(
      origin=i_origin,
      destination=i_destination,
      GOOGLE_API_KEY = google_key)
    # load into data
    dataset_distances <- rbind(dataset_distances,i_distance)
  }
  # add to data
  dataset <- cbind(dataset,dataset_distances)

# map it
library(ggmap)
  ## get the map from stamen
  basemap <- get_stamenmap(
    bbox = c(left = left_lng,
             bottom = bottom_lat,
             right = right_lng,
             top = top_lat),
    zoom=zoom_level, source='stamen',crop = TRUE,
    maptype="terrain-lines", color="bw")

  # Order points high to low
  dataset <- dataset[order(-dataset$distance),]

# Plot - pubs
  ggmap(basemap,extent = 'device') +
    geom_segment(
      aes(x=lng, xend=loc_lng,
          y=lat, yend=loc_lat,
          colour=distance,
          alpha=0.5),
      size=2, data=dataset) +
    scale_colour_gradient(limits=c(0, 2500),
                          low="blue", high="red")+
    geom_point(aes(x=dataset$loc_lng,
                   y=dataset$loc_lat),size=3)

  ggsave("map.svg", width=10, height=10)