![]() ![]() Weather Underground is owned by The Weather Company, a subsidiary of IBM. ![]() The site is available in many languages, and customers can access an ad-free version of the site with additional features for an annual fee. Its information comes from the National Weather Service (NWS), and over 250,000 personal weather stations (PWS). Weather Underground provides weather reports for most major cities around the world on its Web site, as well as local weather reports for newspapers and third-party sites. Myfile <- paste("NewportWeather",i,".csv")ĭownload.file(url = myurl, file.Weather Underground is a commercial weather service providing real-time weather information over the Internet. ![]() The code finished as this: start_date <- as.POSIXct("",tz="gmt") I also had to chance length(my_dates) to nrow(my_dates) in the for loop. myfile <- paste("NewportWeather",i,".csv") You will need to change the folder the file is downloaded into to run the code.Īs pointed out, i needed to incorporate i into the filename which I found can be done like this. Is anyone able to help me download all data for the entire date range in either separate files, or all appended onto the same file. When running this, only data for one day is downloaded in the correct file location, not all of them in the date range. Myfile <- paste("NewportWeather",rownames(my_dates),".csv")ĭownload.file(url = myurl, file.path(folder, myfile, fsep = "\\" )) My_dates<-as.integer(unlist(strsplit(as.character(dates),"-"))) Where i is a date between the start and end.Įnd_date <- as.POSIXct(Sys.Date(),tz="gmt")ĭates <- seq.POSIXt(start_date,end_date,by="day") I am running a for loop for the url: myurl <- paste("",station,"&day=",my_dates$day,"&month=",my_dates$month,"&year=",my_dates$year,"&graphspan=day&format=1", sep = "") In order to speed up the run time I am running the code from the 1st of September 2019 to today's date (I will actually need to run for a period of a few years). ![]() I am trying to download historical data from weather underground into csv format by running a for loop with iterations for each date. ![]()
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