Mongo Loves Data - Using the map-region.py code to create a map

map-region.R

library( reticulate)
library(ggplot2)
library( dplyr )

# As in the call-python.R script  the structure remains unchanged
# A) load the python file
# B) use the function to return a data.frame
#    i)  name is the neighborhood name
#    ii) restaurants
#    iii) region_lng and region_at
#    iv) long and lat for the restaurant markers: R and python don't play nicely enough together to make it worth the effort to extract this from data$restaurant['address']
# 
use_python('/usr/local/bin/python3')
source_python( 'map-region.py')
data <- get_data('Middle Village')

LONG = median( data$long )
LAT = median( data$lat )

# Build the basic graph
m <- leaflet() %>%
  addTiles() %>%
  setView(LONG, LAT, zoom = 13)

#add polygon and individual markers
m %>% addPolygons( lng= data$region_lng, lat = data$region_lat, fillColor='yellow', color='red', stroke=TRUE,  opacity=0.5, label="Middle Village", ) %>% 
  addMarkers(d, lng=data$long, lat = data$lat, popup = data$restaurants['name'] )