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Copy pathSpecialCollections_CatholicMapping.R
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SpecialCollections_CatholicMapping.R
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rm(list=ls(all=TRUE)) # clear memory
#test
packages<- c("foreign","ggmap") # list the packages that you'll need
lapply(packages, require, character.only=T) # load the packages, if they don't load you might need to install them first
setwd("E:\\GISWork_2\\Bohlman_CatholicsInAmerica")
seton.bibles <- read.csv("RawData\\SetonBibles_Subscription_Lists.csv", stringsAsFactors = F)
if (!file.exists("SetonBibles_freqTable.csv")){
seton.bibles.to.geocode <- data.frame(table(seton.bibles$SubscriberCity))
seton.bibles.to.geocode$SubscriberCity <- as.character(seton.bibles.to.geocode$Var1)
seton.bibles.to.geocode$city <- seton.bibles.to.geocode$SubscriberCity
seton.bibles.to.geocode$city[seton.bibles.to.geocode$SubscriberCity == "Washington City, George-Town, Fredericktown, &c."] <-"Washington DC"
seton.bibles.to.geocode <- seton.bibles.to.geocode[c(2:7),c(3,4,2)]
seton.bibles.geocoded<-cbind.data.frame(seton.bibles.to.geocode, geocode(seton.bibles.to.geocode$city))
write.csv(seton.bibles.geocoded, "SetonBibles_freqTable.csv",row.names =F)
}else{
seton.bibles.geocoded <- read.csv("SetonBibles_freqTable.csv", stringsAsFactors = F)
seton.bibles.all <- merge(seton.bibles, seton.bibles.geocoded[,c(1,4,5)],by="SubscriberCity")
write.csv(seton.bibles.all, "SetonBibles_all_city.csv",row.names =F)
}
baden.bibles <- read.csv("RawData\\BadenBibles_Subscription_Lists.csv", stringsAsFactors = F)
if (!file.exists("BadenBibles_freqTable.csv")){
baden.bibles.to.geocode <- data.frame(table(baden.bibles$SubscriberCity))
baden.bibles.to.geocode$SubscriberCity <- as.character(baden.bibles.to.geocode$Var1)
baden.bibles.to.geocode$city <- baden.bibles.to.geocode$SubscriberCity
baden.bibles.to.geocode$city[baden.bibles.to.geocode$SubscriberCity == "Washington City, George-Town, Fredericktown, &c."] <-"Washington DC"
baden.bibles.to.geocode <- baden.bibles.to.geocode[c(2:nrow(baden.bibles.to.geocode)),c(3,4,2)]
baden.bibles.geocoded<-cbind.data.frame(baden.bibles.to.geocode, geocode(baden.bibles.to.geocode$SubscriberCity))
write.csv(baden.bibles.geocoded, "BadenBibles_freqTable.csv",row.names =F)
}else{
baden.bibles.geocoded <- read.csv("BadenBibles_freqTable.csv", stringsAsFactors = F)
# baden.bible.freq2 <-
baden.bibles.all <- merge(baden.bibles, baden.bibles.geocoded[,c(1,4,5)],by="SubscriberCity")
write.csv(baden.bibles.all, "BadenBibles_all_city.csv",row.names =F)
}
sentinal <- read.csv("RawData\\Jesuit_Sentinel.csv", stringsAsFactors = F)
sentinal$DateStr <- as.character(as.Date(sentinal$Date.1, format = "%d-%m-%Y"))
sentinal$Date.1 <- NULL
sentinal$Dated <-as.Date(sentinal$DateStr,format = "%Y-%m-%d")
sentinal <- sentinal[sentinal$Subscriber.City != "",] #remove null cities
date.list <- c("1829-09-30","1829-12-31","1830-03-31","1830-06-30","1830-09-30")
sentinal.1829Sep <- sentinal[sentinal$Dated <= as.Date("1829-09-30", format = "%Y-%m-%d"),]
sentinal.1829Dec <- sentinal[sentinal$Dated <= as.Date("1829-12-31", format = "%Y-%m-%d"),]
sentinal.1830Mar <- sentinal[sentinal$Dated <= as.Date("1830-03-31", format = "%Y-%m-%d"),]
sentinal.1830Jun <- sentinal[sentinal$Dated <= as.Date("1830-06-30", format = "%Y-%m-%d"),]
sentinal.1830Sep <- sentinal[sentinal$Dated <= as.Date("1830-09-30", format = "%Y-%m-%d"),]
if (!file.exists("sentinal_freqTable.csv")){
sentinal$code <- paste(sentinal$Subscriber.City,sentinal$Date,sentinal$Year, sep="-")
sentinal <- sentinal[!(sentinal$Subscriber.City == ""),]
sentinal.to.geocode <- data.frame(table(sentinal$Subscriber.City))
sentinal.to.geocode$Subscriber.City <- as.character(sentinal.to.geocode$Var1)
sentinal.to.geocode <- sentinal.to.geocode[c(2:nrow(sentinal.to.geocode)),c(3,2)]
sentinal.geocoded <-cbind.data.frame(sentinal.to.geocode, geocode(sentinal.to.geocode$Subscriber.City))
write.csv(sentinal.geocoded, "sentinal_freqTable.csv",row.names =F)
}else{
sentinal.geocoded <- read.table("sentinal_freqTable2.csv", stringsAsFactors = F, header = T,sep="\t")
sentinal.all <- merge(sentinal, sentinal.geocoded,by="Subscriber.City")
write.csv(sentinal.all, "sentinal_all_city.csv",row.names =F)
sentinal.time.base <- unique(sentinal.all[,c(1,16:22)])
write.csv(sentinal.time.base, "sentinal_time2.csv",row.names = F)
}
#Sentinal Time spots
rm(list=ls(all=TRUE)) # clear memory
packages<- c("foreign","ggmap") # list the packages that you'll need
lapply(packages, require, character.only=T) # load the packages, if they don't load you might need to install them first
setwd("E:\\GISWork_2\\Bohlman_CatholicsInAmerica")
sentinal <- read.csv("RawData\\Jesuit_Sentinel.csv", stringsAsFactors = F)
sentinal$DateStr <- as.character(as.Date(sentinal$Date.1, format = "%d-%m-%Y"))
sentinal$Dated <-as.Date(sentinal$DateStr,format = "%Y-%m-%d")
sentinal <- sentinal[,c("Subscriber.City","Dated")]
sentinal <- sentinal[sentinal$Subscriber.City != "",] #remove null cities
date.list <- c("1830-09-30","1830-06-30","1830-03-31","1829-12-31", "1829-09-30")
first <-TRUE
for (each.date in date.list){
sentinal.setDate <- sentinal[sentinal$Dated <= as.Date(each.date, format = "%Y-%m-%d"),]
sentinal.table <- data.frame(table(sentinal.setDate$Subscriber.City))
sentinal.table$Subscriber.City <- as.character(sentinal.table$Var1)
sentinal.table <- sentinal.table[,c(3,2)]
names(sentinal.table)<-c("SubscriberCity",paste("d",each.date,sep=""))
if (first){
sentinal.total <- sentinal.table
first <- FALSE
}else{
sentinal.total <- merge(sentinal.total,sentinal.table,by = "SubscriberCity", all = T)
}
}
remove(sentinal.setDate,sentinal.table)
#Redoing the geocoding
sentinal.geocoded <-cbind.data.frame(sentinal.total, geocode(sentinal.total$SubscriberCity))
sentinal.geocoded[is.na(sentinal.geocoded)] <- 0
write.csv(sentinal.geocoded, "sentinal_TimeTable.csv",row.names =F)
library(reshape2)
looper <- melt(sentinal.geocoded, id.vars=c("SubscriberCity", "lon", "lat"))
looper$date <- (substr(as.character(looper$variable),2,11))
looper$freq <- looper$value
looper <- looper[,c(1,2,3,6,7)]
write.csv(looper,"Sentinal_TimeAware.csv")