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 Date
or
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.
For those users having access to SAS, method='csv'
is preferred
when importing several SAS datasets.
Run SAS macro exportlib.sas
available from
http://biostat.mc.vanderbilt.edu/twiki/pub/Main/Hmisc/exportlib.sas
to convert all SAS datasets in a SAS data library (from any engine
supported by your system) into CSV
files. If any customized
formats are used, it is assumed that the PROC FORMAT CNTLOUT=
dataset is in the data library as a regular SAS dataset, as above.
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, method=c('read.xport','dataload','csv'), formats=NULL, allow=NULL) 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. For method='csv' ,
file is the name of the directory containing all the CSV
files created by running the exportlib SAS macro.
|
force.single |
set to FALSE to keep integer-valued
variables not exceeding 2^31-1 in value from being converted to
integer storage mode |
method |
set to "dataload" if you have the dataload
executable installed and want to use it instead of
read.xport . This seems to correct some errors in which
rarely some factor variables are always missing when read by
read.xport when in fact they have some non-missing values. |
formats |
a data frame or list (like that created by
read.xport ) containing PROC FORMAT
output, if such output is not stored in the main transport file. |
allow |
a vector of characters allowed by R that should not be converted to periods in variable names. By default, underscores in variable names are converted to periods as with R before version 1.9. |
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
## Not 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(Not run)