Gmaps API Location Search for City Names in California

Gmaps_API.r

# Example Script for GMAPS API Search
library(anonymizer)
library(readr)
library(dplyr)
library(stringr)
library(RPostgreSQL)
library(data.table)
library(tidyr)
library(chron)
library(lettercase)
library(stringi)
#library(googleway) #Won't use this one as the resuts are parsed out as a list that must be processed to return key values
library(placement)
#Check City List for real city names using Google Geocoder
key <- 'Use Your Key 1'
gmaps_geocode_key <- 'Use Your Key 2'

'%ni%' <- Negate('%in%')

ClipperAccounts <- read_csv("Documents/Data/Clipper/MTC_RegUsers.csv")

#Fix String Case for selected fields
ClipperAccounts$CITY <- stri_trans_general(ClipperAccounts$CITY, id="Title")
ClipperAccounts$FIRST_NAME <- stri_trans_general(ClipperAccounts$FIRST_NAME, id="Title")
ClipperAccounts$LAST_NAME <- stri_trans_general(ClipperAccounts$LAST_NAME, id="Title")
#ClipperAccounts$STATE <- stri_trans_general(ClipperAccounts$STATE, id="Title")
ClipperAccounts$STATUS <- stri_trans_general(ClipperAccounts$STATUS, id="Title")
ClipperAccounts$CARD_TYPE <- stri_trans_general(ClipperAccounts$CARD_TYPE, id="Title")

#Filter Records for Subset that match minimum criteria for matching
# Need to evaluate record counts for this table for all key fields listed below
# Show a count of unique values in key fields
# This would be useful in a table or som eother form of visual to explain which records we will be dropping from the set.
ClipperAccounts %>%
  select(CONTACT_ID,FIRST_NAME,LAST_NAME,CITY,STATE,CARD_SERIAL_NUMBER,CARD_TYPE, STATUS) %>%
  filter(!is.na(CONTACT_ID) & 
           !is.na(LAST_NAME) & 
           !is.na(CITY) &
           !is.na(STATE) &
           !is.na(CARD_SERIAL_NUMBER) &
           !is.na(CARD_TYPE) &
           !is.na(STATUS) & STATE == "CA" &
           STATUS %in% c("Blocked","Active","blocked") &
           CARD_TYPE %ni% c("Failed","Initialized", "Adult - Obsolete")
  ) -> ClipperGood

#Turn City List into Data Frame
CityList <- data.frame(CityName=unique(ClipperGood$CITY))

# Append California to all City Name Values as these locations should all only be California Records
CityList$Location <- paste0(CityList$CityName, ", California")

CityList %>% top_n(3407) -> CityList

CityList <- as.character(CityList$Location)

# This Method uses the placement library
#https://www.r-bloggers.com/placement-an-r-package-to-access-the-google-maps-api/
MatchedCities <- geocode_url(CityList, auth="standard_api", privkey=key,
                             clean=TRUE, add_date='today', verbose=TRUE)





#Merge return cities locations from google to main dataframe based upon Cityname value
#This will be used to decide whether city values are accurate.