> On Oct 15, 2017, at 3:35 PM, Miluji Sb <miluj...@gmail.com> wrote:
>
> Dear David,
>
> This is amazing, thank you so much. If I may ask another question:
>
> The output looks like the following:
>
> ###
> dput(head(x,15))
> c("Metadata for Requested Time Series:", "",
> "prod_name=GLDAS_NOAH025_3H_v2.0",
> "param_short_name=Tair_f_inst", "param_name=Near surface air temperature",
> "unit=K", "begin_time=1970-01-01T00", "end_time=1979-12-31T21",
> "lat= 42.36", "lon=-71.06", "Request_time=2017-10-15 22:20:03 GMT",
> "", "Date&Time Data", "1970-01-01T00:00:00\t267.769",
> "1970-01-01T03:00:00\t264.595")
> ###
>
> Thus I need to drop the first 13 rows and do the following to add identifying
> information:
Are you having difficulty reading in the data from disk? The `read.table`
function has a "skip" parameter.
>
> ###
> mydata <- data.frame(year = substr(x,1,4),
That would not appear to do anything useful with x. The `x` object is not a
long string. The items you want are in separate elements of x.
substr(x,1,4) # now returns
[1] "Meta" "" "prod" "para" "para" "unit" "begi" "end_" "lat=" "lon="
"Requ" "" "Date"
[14] "1970" "1970"
You need to learn basic R indexing. The year might be extracted from the 7th
element of x x via code like this:
year <- substr( x[7], 1,4)
> month = substr(x, 6,7),
> day = substr(x, 9, 10),
> hour = substr(x, 12, 13),
> temp = substr(x, 21, 27))
The time and temp items would naturally be read in with read.table (or in the
case of tab-delimited data with read.delim) after skipping the first 14 lines.
>
> mydata$city <- rep(cities[1,1], nrow(mydata))
There's no need to use `rep` with data.frame. If one argument to data.frame is
length n then all single elelment arguments will be "recycled" to fill in the
needed number of rows. Please take the time to work through all the pages of
"Introduction to R" (shipped with all distributions of R) or pick another
introductory text. We cannot provide tutoring to all students. You need to put
in the needed self-study first.
--
David.
> mydata$state <- rep(cities[1,2], nrow(mydata))
> mydata$lon <- rep(cities[1,3], nrow(mydata))
> mydata$lat <- rep(cities[1,4], nrow(mydata))
> ###
>
> Is it possible to incorporate these into your code so the data looks like
> this:
>
> dput(droplevels(head(mydata)))
> structure(list(year = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = "1970",
> class = "factor"),
> month = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = "01", class =
> "factor"),
> day = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = "01", class =
> "factor"),
> hour = structure(1:6, .Label = c("00", "03", "06", "09",
> "12", "15"), class = "factor"), temp = structure(c(6L, 4L,
> 2L, 1L, 3L, 5L), .Label = c("261.559", "262.525", "262.648",
> "264.595", "265.812", "267.769"), class = "factor"), city =
> structure(c(1L,
> 1L, 1L, 1L, 1L, 1L), .Label = "Boston", class = "factor"),
> state = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = " MA ", class =
> "factor"),
> lon = c(-71.06, -71.06, -71.06, -71.06, -71.06, -71.06),
> lat = c(42.36, 42.36, 42.36, 42.36, 42.36, 42.36)), .Names = c("year",
> "month", "day", "hour", "temp", "city", "state", "lon", "lat"
> ), row.names = c(NA, 6L), class = "data.frame")
>
> Apologies for asking repeated questions and thank you again!
Of course it's possible. I don't understand where the difficulty lies.
>
> Sincerely,
>
> Milu
>
> On Sun, Oct 15, 2017 at 11:45 PM, David Winsemius <dwinsem...@comcast.net>
> wrote:
>
> > On Oct 15, 2017, at 2:02 PM, Miluji Sb <miluj...@gmail.com> wrote:
> >
> > Dear all,
> >
> > i am trying to download time-series climatic data from GES DISC (NASA)
> > Hydrology Data Rods web-service. Unfortunately, no wget method is
> > available.
> >
> > Five parameters are needed for data retrieval: variable, location,
> > startDate, endDate, and type. For example:
> >
> > ###
> > https://hydro1.gesdisc.eosdis.nasa.gov/daac-bin/access/timeseries.cgi?variable=GLDAS2:GLDAS_NOAH025_3H_v2.0:Tair_f_inst&startDate=1970-01-01T00&endDate=1979-12-31T00&location=GEOM:POINT(-71.06,%2042.36)&type=asc2
> > ###
> >
> > In this case, variable: Tair_f_inst (temperature), location: (-71.06,
> > 42.36), startDate: 01 January 1970; endDate: 31 December 1979; type: asc2
> > (output 2-column ASCII).
> >
> > I am trying to download data for 100 US cities, data for which I have in
> > the following data.frame:
> >
> > ###
> > cities <- dput(droplevels(head(cities, 5)))
> > structure(list(city = structure(1:5, .Label = c("Boston", "Bridgeport",
> > "Cambridge", "Fall River", "Hartford"), class = "factor"), state =
> > structure(c(2L,
> > 1L, 2L, 2L, 1L), .Label = c(" CT ", " MA "), class = "factor"),
> > lon = c(-71.06, -73.19, -71.11, -71.16, -72.67), lat = c(42.36,
> > 41.18, 42.37, 41.7, 41.77)), .Names = c("city", "state",
> > "lon", "lat"), row.names = c(NA, 5L), class = "data.frame")
> > ###
> >
> > Is it possible to download the data for the multiple locations
> > automatically (e.g. RCurl) and save them as csv? Essentially, reading
> > coordinates from the data.frame and entering it in the URL.
> >
> > I would also like to add identifying information to each of the data files
> > from the cities data.frame. I have been doing the following for a single
> > file:
>
> Didn't seem that difficult:
>
> library(downloader) # makes things easier for Macs, perhaps not needed
> # if not used will need to use download.file
>
> for( i in 1:5) {
> target1 <-
> paste0("https://hydro1.gesdisc.eosdis.nasa.gov/daac-bin/access/timeseries.cgi?variable=GLDAS2:GLDAS_NOAH025_3H_v2.0:Tair_f_inst&startDate=1970-01-01T00&endDate=1979-12-31T00&location=GEOM:POINT(",
> cities[i, "lon"],
> ",%20", cities[i,"lat"],
> ")&type=asc2")
> target2 <- paste0("~/", # change for whatever destination directory you
> may prefer.
> cities[i,"city"],
> cities[i,"state"], ".asc")
> download(url=target1, destfile=target2)
> }
>
> Now I have 5 named files with extensions ".asc" in my user directory (since
> I'm on a Mac). It is a slow website so patience is needed.
>
> --
> David
>
>
> >
> > ###
> > x <- readLines(con=url("
> > https://hydro1.gesdisc.eosdis.nasa.gov/daac-bin/access/timeseries.cgi?variable=GLDAS2:GLDAS_NOAH025_3H_v2.0:Tair_f_inst&startDate=1970-01-01T00&endDate=1979-12-31T00&location=GEOM:POINT(-71.06,%2042.36)&type=asc2
> > "))
> > x <- x[-(1:13)]
> >
> > mydata <- data.frame(year = substr(x,1,4),
> > month = substr(x, 6,7),
> > day = substr(x, 9, 10),
> > hour = substr(x, 12, 13),
> > temp = substr(x, 21, 27))
> >
> > mydata$city <- rep(cities[1,1], nrow(mydata))
> > mydata$state <- rep(cities[1,2], nrow(mydata))
> > mydata$lon <- rep(cities[1,3], nrow(mydata))
> > mydata$lat <- rep(cities[1,4], nrow(mydata))
> > ###
> >
> > Help and advice would be greatly appreciated. Thank you!
> >
> > Sincerely,
> >
> > Milu
> >
> > [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
>
> David Winsemius
> Alameda, CA, USA
>
> 'Any technology distinguishable from magic is insufficiently advanced.'
> -Gehm's Corollary to Clarke's Third Law
>
>
>
>
>
>
David Winsemius
Alameda, CA, USA
'Any technology distinguishable from magic is insufficiently advanced.'
-Gehm's Corollary to Clarke's Third Law
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
