Extracting EOD Data from NSE
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My prime interest being the Indian financial markets, the first step would be to get the data to play around. NSE India provides EOD of data as bhavcopies. The same are stored as zipped files at their servers. Downloading them one by one for a larger time frame will be very tedious, hence I will attempt to automate the process.
There is a great tool for statistical computing called R. It is open-source with a lot of development being done across various packages. This interests me a lot because of it simplicity and power. I would make my attempt of automating bhavcopy downloads using this software. If you want to try the same, you can visit the downloads section of R-Project and get the latest version
Objective: Download Bhavcopy (Equity) from http://www.nseindia.com and save only relevant columns Date, Symbol, Open, High, Low, Close, Last and Volume.
To download the Bhavcopy (Equity) from http://www.bseindia.com refer to this post.
Here is the R Code for the same
#Define Working Directory, where files would be saved
setwd('D:/')
#Define start and end dates, and convert them into date format
startDate = as.Date("2010-12-25", order="ymd")
endDate = as.Date("2011-01-05", order="ymd")
#work with date, month, year for which data has to be extracted
myDate = startDate
zippedFile <- tempfile()
while (myDate <= endDate){
filenameDate = paste(as.character(myDate, "%y%m%d"), ".csv", sep = "")
monthfilename=paste(as.character(myDate, "%y%m"),".csv", sep = "")
downloadfilename=paste("cm", toupper(as.character(myDate, "%d%b%Y")), "bhav.csv", sep = "")
temp =""
#Generate URL
myURL = paste("http://nseindia.com/content/historical/EQUITIES/", as.character(myDate, "%Y"), "/", toupper(as.character(myDate, "%b")), "/", downloadfilename, ".zip", sep = "")
#retrieve Zipped file
tryCatch({
#Download Zipped File
download.file(myURL,zippedFile, quiet=TRUE, mode="wb")
#Unzip file and save it in temp
temp <- read.csv(unzip(zippedFile), sep = ",")
#Rename Columns Volume and Date
colnames(temp)[9] <- "VOLUME"
colnames(temp)[11] <- "DATE"
#Define Date format
temp$DATE <- as.Date(temp$DATE, format="%d-%b-%Y")
#Reorder Columns and Select relevant columns
temp<-subset(temp,select=c("DATE","SYMBOL","OPEN","HIGH","LOW","CLOSE","LAST","VOLUME"))
#Write the BHAVCOPY csv - datewise
write.csv(temp,file=filenameDate,row.names = FALSE)
#Write the csv in Monthly file
if (file.exists(monthfilename))
{
write.table(temp,file=monthfilename,sep=",", eol="\n", row.names = FALSE, col.names = FALSE, append=TRUE)
}else
{
write.table(temp,file=monthfilename,sep=",", eol="\n", row.names = FALSE, col.names = TRUE, append=FALSE)
}
#Write the file Symbol wise
#Print Progress
#print(paste (myDate, "-Done!", endDate-myDate, "left"))
}, error=function(err){
#print(paste(myDate, "-No Record"))
}
)
myDate <- myDate+1
#print(paste(myDate, "Next Record"))
}
#Delete temp file - Bhavcopy
junk <- dir(pattern="cm")
file.remove(junk)
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