| upData {Hmisc} | R Documentation |
cleanup.import will correct errors and shrink
the size of data frames created by the S-Plus File ... Import
dialog or by other methods such as scan and read.table. By
default, double precision numeric variables are changed to single
precision (S-Plus only) or to integer when they contain no fractional
components.
Infinite values or values greater than 1e20 in absolute value are set
to NA. This solves problems of importing Excel spreadsheets that
contain occasional character values for numeric columns, as S-Plus
converts these to Inf without warning. There is also an option to
convert variable names to lower case and to add labels to variables.
The latter can be made easier by importing a CNTLOUT dataset created
by SAS PROC FORMAT and using the sasdict option as shown in the
example below. cleanup.import can also transform character or
factor variables to dates.
upData is a function facilitating the updating of a data frame
without attaching it in search position one. New variables can be
added, old variables can be modified, variables can be removed or renamed, and
"labels" and "units" attributes can be provided. Various checks
are made for errors and inconsistencies, with warnings issued to help
the user. Levels of factor variables
can be replaced, especially using the list notation of the standard
merge.levels function. Unless force.single is set to FALSE,
upData also converts double precision vectors to single precision
(if not under R), or to integer if no fractional values are present in
a vector.
Both cleanup.import and upData will fix a problem with
data frames created under S-Plus before version 5 that are used in S-Plus 5 or
later. The problem was caused by use of the label function
to set a variable's class to "labelled". These classes are
removed as the S version 4 language does not support multiple
inheritance. Failure to run data frames through one of the two
functions when these conditions apply will result in simple numeric
variables being set to factor in some cases. Extraneous "AsIs"
classes are also removed.
For S-Plus, a function exportDataStripped is provided that allows
exporting of data to other systems
by removing attributes label, imputed, format, units, and
comment. It calls exportData after stripping these
attributes. Otherwise exportData will fail.
cleanup.import(obj, labels, lowernames=FALSE,
force.single=TRUE, force.numeric=TRUE, rmnames=TRUE,
big=1e20, sasdict, pr, datevars=NULL, dateformat='%F',
fixdates=c('none','year'))
upData(object, ...,
rename, drop, labels, units, levels,
force.single=TRUE, lowernames=FALSE, moveUnits=FALSE)
exportDataStripped(data, ...)
obj |
a data frame or list |
object |
a data frame or list |
data |
a data frame |
force.single |
By default, double precision variables are converted to single precision
(in S-Plus only) unless force.single=FALSE.
force.single=TRUE will also convert vectors having only integer
values to have a storage mode of integer, in R or S-Plus.
|
force.numeric |
Sometimes importing will cause a numeric variable to be
changed to a factor vector. By default, cleanup.import will check
each factor variable to see if the levels contain only numeric values
and "". In that case, the variable will be converted to numeric,
with "" converted to NA. Set force.numeric=FALSE to prevent
this behavior.
|
rmnames |
set to `F' to not have `cleanup.import' remove `names' or `.Names' attributes from variables |
labels |
a character vector the same length as the number of variables in
obj. These character values are taken to be variable labels in the
same order of variables in obj.
For upData, labels is a named list or named vector with variables
in no specific order.
|
lowernames |
set this to TRUE to change variable names to lower case.
upData does this before applying any other changes, so variable
names given inside arguments to upData need to be lower case if
lowernames==TRUE.
|
big |
a value such that values larger than this in absolute value are set to
missing by cleanup.import
|
sasdict |
the name of a data frame containing a raw imported SAS PROC CONTENTS CNTLOUT= dataset. This is used to define variable names and to add attributes to the new data frame specifying the original SAS dataset name and label. |
pr |
set to TRUE or FALSE to force or prevent printing of the current
variable number being processed. By default, such messages are printed if the
product of the number of variables and number of observations in obj
exceeds 500,000.
|
datevars |
character vector of names (after lowernames is
applied) of variables to consider as a factor or character vector
containing dates in a format matching dateformat. The
default is "%F" which uses the yyyy-mm-dd format. |
dateformat |
for cleanup.import is the input format (see
strptime) |
fixdates |
for any of the variables listed in datevars
that have a dateformat that cleanup.import understands,
specifying fixdates allows corrections of certain formatting
inconsistencies before the fields are attempted to be converted to
dates (the default is to assume that the dateformat is followed
for all observation for datevars). Currently
fixdates='year' is implemented, which will cause 2-digit or
4-digit years to be shifted to the alternate number of digits when
dateform is the default "%F" or is "%y-%m-%d",
"%m/%d/%y", or "%m/%d/%Y". Two-digits years are padded with 20
on the left. Set dateformat to the desired format, not the
exceptional format.
|
... |
for upData, one or more expressions of the form
variable=expression, to derive new variables or change old ones.
For exportDataStripped, optional arguments that are passed to
exportData.
|
rename |
list or named vector specifying old and new names for variables. Variables are
renamed before any other operations are done. For example, to rename
variables age and sex to respectively Age and
gender, specify rename=list(age="Age", sex="gender") or
rename=c(age=...).
|
drop |
a vector of variable names to remove from the data frame |
units |
a named vector or list defining "units" attributes of variables, in no
specific order
|
levels |
a named list defining "levels" attributes for factor variables, in
no specific order. The values in this list may be character vectors
redefining levels (in order) or another list (see
merge.levels if using S-Plus).
|
moveUnits |
set to TRUE to look for units of measurements in variable
labels and move them to a "units" attribute. If an expression
in a label is enclosed in parentheses or brackets it is assumed to be
units if moveUnits=TRUE.
|
a new data frame
Frank Harrell, Vanderbilt University
sas.get, data.frame, describe,
label, read.csv, strptime,
POSIXct,Date
## Not run:
dat <- read.table('myfile.asc')
dat <- cleanup.import(dat)
## End(Not run)
dat <- data.frame(a=1:3, d=c('01/02/2004',' 1/3/04',''))
cleanup.import(dat, datevars='d', dateformat='%m/%d/%y', fixdates='year')
dat <- data.frame(a=(1:3)/7, y=c('a','b1','b2'), z=1:3)
dat2 <- upData(dat, x=x^2, x=x-5, m=x/10,
rename=c(a='x'), drop='z',
labels=c(x='X', y='test'),
levels=list(y=list(a='a',b=c('b1','b2'))))
dat2
describe(dat2)
dat <- dat2 # copy to original name and delete dat2 if OK
rm(dat2)
# If you import a SAS dataset created by PROC CONTENTS CNTLOUT=x.datadict,
# the LABELs from this dataset can be added to the data. Let's also
# convert names to lower case for the main data file
## Not run:
mydata2 <- cleanup.import(mydata2, lowernames=TRUE, sasdict=datadict)
## End(Not run)