sasxport.get {Hmisc} | R Documentation |
Uses the read.xport
and lookup.xport
functions in the
foreign
library to import SAS datasets. SAS date, time, and
date/time variables are converted to the appropriate POSIX objects in R,
variable names are converted to lower case, SAS labels are associated
with variables, and (by default) integer-valued variables are converted
from storage mode double
to integer
. If the user ran
PROC FORMAT CNTLOUT=
in SAS and included the resulting dataset in
the SAS version 5 transport file, variables having customized formats
that do not include any ranges (i.e., variables having standard
PROC FORMAT; VALUE
label formats) will have their format labels looked
up, and these variables are converted to S factor
s.
SASdsLabels
reads a file containing PROC CONTENTS
printed output to parse dataset labels, assuming that PROC
CONTENTS
was run on an entire library.
sasxport.get(file, force.single = TRUE) sasdsLabels(file)
file |
name of a file containing the SAS transport file.
file may be a URL beginning with http:// . For
sasdsLabels , file is the name of a file containing a
PROC CONTENTS output listing.
|
force.single |
set to FALSE to keep integer-valued
variables not exceeding 2^31-1 in value from being converted to
integer storage mode |
See contents.list
for a way to print the
directory of SAS datasets when more than one was imported.
If there is more than one dataset in the transport file other than the
PROC FORMAT
file, the result is a list of data frames
containing all the non-PROC FORMAT
datasets. Otherwise the
result is the single data frame. sasdsLabels
returns a named
vector of dataset labels, with names equal to the dataset names.
Frank E Harrell Jr
read.xport
,label
,sas.get
,
DateTimeClasses
,lookup.xport
,
contents
,describe
## Don't run: # SAS code to generate test dataset: # libname y SASV5XPT "test2.xpt"; # # PROC FORMAT; VALUE race 1=green 2=blue 3=purple; RUN; # PROC FORMAT CNTLOUT=format;RUN; * Name, e.g. 'format', unimportant; # data test; # LENGTH race 3 age 4; # age=30; label age="Age at Beginning of Study"; # race=2; # d1='3mar2002'd ; # dt1='3mar2002 9:31:02'dt; # t1='11:13:45't; # output; # # age=31; # race=4; # d1='3jun2002'd ; # dt1='3jun2002 9:42:07'dt; # t1='11:14:13't; # output; # format d1 mmddyy10. dt1 datetime. t1 time. race race.; # run; # data z; LENGTH x3 3 x4 4 x5 5 x6 6 x7 7 x8 8; # DO i=1 TO 100; # x3=ranuni(3); # x4=ranuni(5); # x5=ranuni(7); # x6=ranuni(9); # x7=ranuni(11); # x8=ranuni(13); # output; # END; # DROP i; # RUN; # PROC MEANS; RUN; # PROC COPY IN=work OUT=y;SELECT test format z;RUN; *Creates test2.xpt; w <- sasxport.get('test2.xpt') # To use an existing copy of test2.xpt available on the web: w <- sasxport.get('http://hesweb1.med.virginia.edu/biostat/s/data/sas/test2.xpt') describe(w$test) # see labels, format names for dataset test # Note: if only one dataset (other than format) had been exported, # just do describe(w) as sasxport.get would not create a list for that lapply(w, describe)# see descriptive stats for both datasets contents(w$test) # another way to see variable attributes lapply(w, contents)# show contents of both datasets options(digits=7) # compare the following matrix with PROC MEANS output t(sapply(w$z, function(x) c(Mean=mean(x),SD=sqrt(var(x)),Min=min(x),Max=max(x)))) ## End Don't run