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Dear Rusers, I am trying to feed my database with data from a file. But since my file (2010101000.txt) there`s no headers I am facing problem because the result data.frame is not separated my columns. How could I set variables names for each columns in *dbWriteTable*? I have tried the command below but I don`t know how to fill the *field.type*option. dbWriteTable(con, "b20101010",

Dear R-users, I would like to know how could I read a file with different lines lengths. I need read this file and create an output to feed my database. So after reading I'll need create an output like this "INSERT INTO TEMP (DATA,STATION,VAR1,VAR2) VALUES (20100910,837460, 39,390)" I mean, each line should be read. But I don`t how to do this when these lines have different

Hello everybody, I am a new R & Grass user. I am interested in doing a kriging of the Temperature in a basin, based on pixel elevation (DTM). I use Grass 6.2.1 and R 2.5.1 and have installed the spgrass6 package. The DTM is called "DTM_trentino_100m" and is like this: north:5158000.0 south:5058500.0 east:1729700.0 west:1611600.0 rows:995 cols:1181 -9999.0 -9999.0 -9999.0

Dear all, I am attempting to convert 10 NetCDF files into a single NetCDF file, due to the data input requirements of a model I hope to use. I am using the ncdf package, version 1.6. The data are global-scale water values, on a monthly basis for 10 years (ie. 120 months of data in total; at present the data are separated by year, with 12 months of data in each file - mrunoff_1986 through to

Dear all, I am attempting to convert 10 NetCDF files into a single NetCDF file, due to the data input requirements of a model I hope to use. I am using the ncdf package, version 1.6. The data are global-scale water values, on a monthly basis for 10 years (ie. 120 months of data in total; at present the data are separated by year, with 12 months of data in each file - mrunoff_1986 through to

...based on my experience, for use in all non-certified enterprise operations (large and small) on general-purpose computers. RHEL is, of course, the better alternative when you require the upstream vendor's certified platform, certified and tested integrated solutions, industry-leading support, or customized solutions. Their offerings are a bargain when you consider the benefits they provide