Geocode & Web Scraping

library(dplyr)
library(tidygeocoder)
library(OpenStreetMap)
library(ggplot2)
library(ggrepel)
library(osmar)
library(rvest)

#URL for scrapping
url <- "https://locations.wendys.com/united-states/pa/pittsburgh"
wendys_url <- read_html("https://locations.wendys.com/united-states/pa/pittsburgh")

#clean wendys data
#==============================================================
#scrap the address from the wendys website
#make sure to add . before selector class name
selector_name<-".c-AddressRow"

fnames<-html_nodes(wendys_url, css = selector_name) %>%
  html_text()

df <- as.data.frame(fnames)%>%
  filter(fnames != "US")

#convert to matrix 
wendys_df <- as.data.frame(matrix(df$fnames, ncol = 2, byrow = TRUE))
  
#create full address column
wendys_df$location <- paste0(wendys_df$V1,",",wendys_df$V2)

#create long and lat via geocode
wendys_coordinates <- wendys_df%>%
geocode(location, method = "arcgis" )
#==============================================================

#make a map of pgh using coordinates from openstreetmap.org
#applies coordinates to the openmap function
# # The openmap function downloads a street map and 
# the openproj function projects it onto a latitude and longitude 
# coordinate system so that we can overlay the coordinates
pgh_map <- openmap( c(40.6151,-79.8241),c(40.2476,-80.1841))
pgh_map.latlng <- openproj(pgh_map)

#plot wendys locations on map
autoplot.OpenStreetMap(pgh_map.latlng) +
  theme_minimal() +
  theme(      axis.text.y=element_blank(),
              axis.title=element_blank(),
              axis.text.x=element_blank(),
              plot.margin = unit(c(0, 0, 0, 0), "cm")
  ) +
  geom_point(data=wendys_coordinates, aes(x=long, y=lat), color="navy", size=4, alpha=1)+
  labs(
    title = "Wendy's Pittsburgh Locations (using geocoding and webscraping)"
  )