R: How to get a dataset with spaces in its name

Question

How can I get an R dataset with spaces in its name, for example, “BJsales.lead (BJsales)” in “dataset” packages?

pkg = "datasets" cat( "Summary of all the datasets in package", pkg, "--\n" ) d = data( package=pkg ) $results # "Package" "LibPath" "Item" "Title" names = d[ , "Item" ] titles = d[ , "Title" ] # sum( duplicated( names )) ?? for( j in 1:len(names) ){ name = names[[j]] cat( name, ":\n" ) data( list=name ) x = get( name ) # <-- Error if blank in name m = paste( dim( as.matrix( x )), collapse=" " ) # grr cat( class(x), m, " freq", frequency(x), "\n" ) } # -> Error in get(name) : object 'BJsales.lead (BJsales)' not found 

OK, get can only search for the correct names, which is reasonable.
But what to do - how can I get the data for "BJsales.lead (BJsales)"?

R version 3.1.3 (2015-03-09)
Platform: x86_64-apple-darwin10.8.0 (64-bit)
Running under: OS X 10.8.3 (Mountain Lion)

Answer 1

In fact, get() may look for invalid names:

 `xy` <- 3; get('x y'); ## [1] 3 

The problem is that the Item column of the results matrix returned by data() does not always contain the exact name of the data set; in some cases it has a suffix in brackets, although I have no idea why.

You can disable it with gsub() and then download via get() .

In addition, you do not need a data(list=name) call data(list=name) .

Also, there is no len() (unfortunately); I think you mean length() .

Consequently:

 pkg <- 'datasets'; cat('Summary of all the datasets in package',pkg,'--\n'); d <- data(package=pkg)$results; # 'Package' 'LibPath' 'Item' 'Title' names <- d[,'Item']; titles <- d[,'Title']; for (j in 1:length(names)) { name <- names[j]; cat(name,':\n'); x <- get(gsub('\\s.*','',name)); m <- paste(dim(as.matrix(x)),collapse=' '); cat(class(x),m,' freq',frequency(x),'\n'); }; ## Summary of all the datasets in package datasets -- ## AirPassengers : ## ts 144 1 freq 12 ## BJsales : ## ts 150 1 freq 1 ## BJsales.lead (BJsales) : ## ts 150 1 freq 1 ## BOD : ## data.frame 6 2 freq 1 ## CO2 : ## nfnGroupedData nfGroupedData groupedData data.frame 84 5 freq 1 ## ChickWeight : ## nfnGroupedData nfGroupedData groupedData data.frame 578 4 freq 1 ## DNase : ## nfnGroupedData nfGroupedData groupedData data.frame 176 3 freq 1 ## EuStockMarkets : ## mts ts matrix 1860 4 freq 260 ## Formaldehyde : ## data.frame 6 2 freq 1 ## HairEyeColor : ## table 32 1 freq 1 ## Harman23.cor : ## list 3 1 freq 1 ## Harman74.cor : ## list 3 1 freq 1 ## Indometh : ## nfnGroupedData nfGroupedData groupedData data.frame 66 3 freq 1 ## InsectSprays : ## data.frame 72 2 freq 1 ## JohnsonJohnson : ## ts 84 1 freq 4 ## LakeHuron : ## ts 98 1 freq 1 ## LifeCycleSavings : ## data.frame 50 5 freq 1 ## Loblolly : ## nfnGroupedData nfGroupedData groupedData data.frame 84 3 freq 1 ## Nile : ## ts 100 1 freq 1 ## Orange : ## nfnGroupedData nfGroupedData groupedData data.frame 35 3 freq 1 ## OrchardSprays : ## data.frame 64 4 freq 1 ## PlantGrowth : ## data.frame 30 2 freq 1 ## Puromycin : ## data.frame 23 3 freq 1 ## Seatbelts : ## mts ts 192 8 freq 12 ## Theoph : ## nfnGroupedData nfGroupedData groupedData data.frame 132 5 freq 1 ## Titanic : ## table 32 1 freq 1 ## ToothGrowth : ## data.frame 60 3 freq 1 ## UCBAdmissions : ## table 24 1 freq 1 ## UKDriverDeaths : ## ts 192 1 freq 12 ## UKgas : ## ts 108 1 freq 4 ## USAccDeaths : ## ts 72 1 freq 12 ## USArrests : ## data.frame 50 4 freq 1 ## USJudgeRatings : ## data.frame 43 12 freq 1 ## USPersonalExpenditure : ## matrix 5 5 freq 1 ## VADeaths : ## matrix 5 4 freq 1 ## WWWusage : ## ts 100 1 freq 1 ## WorldPhones : ## matrix 7 7 freq 1 ## ability.cov : ## list 3 1 freq 1 ## airmiles : ## ts 24 1 freq 1 ## airquality : ## data.frame 153 6 freq 1 ## anscombe : ## data.frame 11 8 freq 1 ## attenu : ## data.frame 182 5 freq 1 ## attitude : ## data.frame 30 7 freq 1 ## austres : ## ts 89 1 freq 4 ## beaver1 (beavers) : ## data.frame 114 4 freq 1 ## beaver2 (beavers) : ## data.frame 100 4 freq 1 ## cars : ## data.frame 50 2 freq 1 ## chickwts : ## data.frame 71 2 freq 1 ## co2 : ## ts 468 1 freq 12 ## crimtab : ## table 42 22 freq 1 ## discoveries : ## ts 100 1 freq 1 ## esoph : ## data.frame 88 5 freq 1 ## euro : ## numeric 11 1 freq 1 ## euro.cross (euro) : ## matrix 11 11 freq 1 ## eurodist : ## dist 21 21 freq 1 ## faithful : ## data.frame 272 2 freq 1 ## fdeaths (UKLungDeaths) : ## ts 72 1 freq 12 ## freeny : ## data.frame 39 5 freq 1 ## freeny.x (freeny) : ## matrix 39 4 freq 1 ## freeny.y (freeny) : ## ts 39 1 freq 4 ## infert : ## data.frame 248 8 freq 1 ## iris : ## data.frame 150 5 freq 1 ## iris3 : ## array 600 1 freq 1 ## islands : ## numeric 48 1 freq 1 ## ldeaths (UKLungDeaths) : ## ts 72 1 freq 12 ## lh : ## ts 48 1 freq 1 ## longley : ## data.frame 16 7 freq 1 ## lynx : ## ts 114 1 freq 1 ## mdeaths (UKLungDeaths) : ## ts 72 1 freq 12 ## morley : ## data.frame 100 3 freq 1 ## mtcars : ## data.frame 32 11 freq 1 ## nhtemp : ## ts 60 1 freq 1 ## nottem : ## ts 240 1 freq 12 ## npk : ## data.frame 24 5 freq 1 ## occupationalStatus : ## table 8 8 freq 1 ## precip : ## numeric 70 1 freq 1 ## presidents : ## ts 120 1 freq 4 ## pressure : ## data.frame 19 2 freq 1 ## quakes : ## data.frame 1000 5 freq 1 ## randu : ## data.frame 400 3 freq 1 ## rivers : ## numeric 141 1 freq 1 ## rock : ## data.frame 48 4 freq 1 ## sleep : ## data.frame 20 3 freq 1 ## stack.loss (stackloss) : ## numeric 21 1 freq 1 ## stack.x (stackloss) : ## matrix 21 3 freq 1 ## stackloss : ## data.frame 21 4 freq 1 ## state.abb (state) : ## character 50 1 freq 1 ## state.area (state) : ## numeric 50 1 freq 1 ## state.center (state) : ## list 2 1 freq 1 ## state.division (state) : ## factor 50 1 freq 1 ## state.name (state) : ## character 50 1 freq 1 ## state.region (state) : ## factor 50 1 freq 1 ## state.x77 (state) : ## matrix 50 8 freq 1 ## sunspot.month : ## ts 3177 1 freq 12 ## sunspot.year : ## ts 289 1 freq 1 ## sunspots : ## ts 2820 1 freq 12 ## swiss : ## data.frame 47 6 freq 1 ## treering : ## ts 7980 1 freq 1 ## trees : ## data.frame 31 3 freq 1 ## uspop : ## ts 19 1 freq 0.1 ## volcano : ## matrix 87 61 freq 1 ## warpbreaks : ## data.frame 54 3 freq 1 ## women : ## data.frame 15 2 freq 1