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# In this part, I scaped the address information about New Haven real estate proporties from website.
# Setting Working Directory in my Mac
setwd("/Users/tianjiachen/Desktop/case studies/Y15_W1/newdata")
# Set three variables in the data frame
all_html <- 1:27307
pid=rep(0, length(all_html))
location=rep(0, length(all_html))
totval=rep(0, length(all_html))
# Get the pid, location and totval from all the webpages
for (i in all_html) {
url <- paste(i, ".html", sep="")
try(x <- scan(url, what="", sep="\n"))
x <- gsub("<[^<>]*>", "", x)
x <- gsub("\t", "", x, fixed=TRUE)
x <- gsub(" ", "", x, fixed=TRUE) # Taking out unnecessary blanks while keeping the blanks in the location
pos_Location <- grep("Location", x) # Get position of key word "Location"
pos_PID <- grep("PID", x)
pos_Appraisal <- grep("Appraisal", x)
pid[i] <- as.numeric(x[pos_PID+2])
location[i] <- x[pos_Location+2]
totval[i] <- as.numeric(gsub(",", "", substr(x[pos_Appraisal[1]+2],2,nchar(x[pos_Appraisal[1]+2])), fixed=TRUE))
# Put the result into data frame
result <- data.frame(pid=pid,
result <- unique(result)
# Write data to .csv
write.csv(result, "newhavendata.csv", row.names=FALSE)
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