subset

I have a netCDF file that I wish to extract a subset from defined by latitude/longitude boundaries (i.e. a lat/long defined box), using the ‘ncdf’ package in R. A summary of my netCDF file is below. It has two dimensions (latitude and longitude) and 1 variable (10U_GDS4_SFC). It is essentially a lat/long grid containing wind values: [1] "file example.nc has 2 dimensions:" [1] "lat_0 Size: 1280" [1] "lon_1 Size: 2560" [1] "------------------------" [1] "file example.nc has 1 variables:" [1] "float 10U_GDS4_SFC[lon_1,lat_0] Longname:10 metre U wind component Missval:1e+30" The latitude variable

I have a large data frame that consists of data that looks something like this: date w x y z region 1 2012 01 21 43 12 3 NORTH 2 2012 02 32 54 21 16 NORTH 3 2012 03 14 32 65 32 NORTH 4 2012 04 65 33 75 21 NORTH : : : : : : : : : : : : : : 12 2012 12 32 58 53 17 NORTH 13 2012 01 12 47 43 23 SOUTH 14 2012 02 87 43 21 76 SOUTH : : : : : : : 25 2012 01 12 46 84 29 EAST 26 2012 02 85 29 90 12 EAST : : : : : : : : : : : : : : I want to extract section of the data that have the same date value, for example to do this just for 2012 01 I would just create a subset of data data_1 <- subset(data, date ==

I've written the following function based on subset() , which I find handy: ss <- function (x, subset, ...) { r <- eval(substitute(subset), data.frame(.=x), parent.frame()) if (!is.logical(r)) stop("'subset' must be logical") x[r & !is.na(r)] } So, I can write: ss(myDataFrame$MyVariableName, 500 < . & . < 1500) instead of myDataFrame$MyVariableName[ 500 < myDataFrame$MyVariableName & myDataFrame$MyVariableName < 1500] This seems like something other people might have developed solutions for, though - including something in core R I might have missed. Anything already out there? I realize that

I have a field _keywords which is an array of strings. I want to get documents of which _keywords are super-set of the query array. For example: db.article.insert({'_keywords': ['foo', 'foo1', 'foo2']}) I want to retrive this record when I query subset of ['foo', 'foo1', 'foo2'], eg: ['foo'], ['foo1', 'foo2'] EDIT: something like: db.article.find({'_keywords': {$contains: array}}) Use the $all operator: db.article.find( { _keywords: { $all: [ 'foo1', 'foo2' ] } } ); Source: http://www.mongodb.org/display/DOCS/Advanced+Queries#AdvancedQueries-%24all In MongoDb, for array field: "$in:[...]"

How can I verify that one XSD schema is a subset of another XSD schema? We are creating a system-of-systems application using a collection of "blueprint" XSD schemas (which defines all possible inputs or outputs available to a subcomponent). Many subcomponents are being implemented, and these subcomponents pass data among themselves using XML files. Each subcomponent creates a subset of the relevant blueprint XSD schema (to indicate which of the possible inputs or output it has chosen to implement). Any XML datafile that validates against a subset XSD schema must also validate against the

I have a data frame with about 40 columns, the second column, data[2] contains the name of the company that the rest of the row data describes. However, the names of the companies are different depending on the year (trailing 09 for 2009 data, nothing for 2010). I would like to be able to subset the data such that I can pull in both years at once. Here is an example of what I'm trying to do... subset(data, data[2] == "Company Name 09" | "Company Name", drop = T) Essentially, I'm having difficulty using the OR operator within the subset function. However, I have tried other alternatives: subset