Describe structure of Data Sets and Importers
The function codeplan() creates a data frame that
describes the structure of an item list (a data.set object or
an importer object), so that this structure can be stored and
and recovered. The resulting data frame has a particular print method
that delimits the output to one line per variable.
With setCodeplan an item list structure (as returned by codeplan())
can be applied to a data frame or data set. It is also possible to use an
assignment like codeplan(x) <- value to a similar effect.
codeplan(x) ## S4 method for signature 'item.list' codeplan(x) ## S4 method for signature 'item' codeplan(x) setCodeplan(x,value) ## S4 method for signature 'data.frame,codeplan' setCodeplan(x,value) ## S4 method for signature 'data.set,codeplan' setCodeplan(x,value) ## S4 method for signature 'data.set,NULL' setCodeplan(x,value) ## S4 method for signature 'item,codeplan' setCodeplan(x,value) ## S4 method for signature 'item,NULL' setCodeplan(x,value) ## S4 method for signature 'atomic,codeplan' setCodeplan(x,value) ## S4 method for signature 'atomic,NULL' setCodeplan(x,value) codeplan(x) <- value
x |
for |
value |
an object as it would be returned by |
If applicable, codeplan returns a data frame with
additional S3 class attribute "codeplan". For arguments for
which the relevant information does not exist, the function returns NULL.
Such a data frame has the following variables:
|
The name of the item/variable in the item list or data set. |
|
The description/variable label string of the item/variable. |
|
code to recreate the annotation attribute, |
|
code to recreate the value labels, |
|
code to recreate the value filter attribute (declaration of missing values, range of valid values, or an enumeration of valid values.) |
|
a character string that describes storage mode, such as |
|
a character string with the measurement level,
|
If codeplan(x)<-value or setCodeplan(x,value) is used
and value is NULL, all the special information about
annotation, labels, value filters, etc. is removed from the resulting
object, which then is usually a mere atomic vector or data frame.
Data1 <- data.set(
vote = sample(c(1,2,3,8,9,97,99),size=300,replace=TRUE),
region = sample(c(rep(1,3),rep(2,2),3,99),size=300,replace=TRUE),
income = exp(rnorm(300,sd=.7))*2000
)
Data1 <- within(Data1,{
description(vote) <- "Vote intention"
description(region) <- "Region of residence"
description(income) <- "Household income"
foreach(x=c(vote,region),{
measurement(x) <- "nominal"
})
measurement(income) <- "ratio"
labels(vote) <- c(
Conservatives = 1,
Labour = 2,
"Liberal Democrats" = 3,
"Don't know" = 8,
"Answer refused" = 9,
"Not applicable" = 97,
"Not asked in survey" = 99)
labels(region) <- c(
England = 1,
Scotland = 2,
Wales = 3,
"Not applicable" = 97,
"Not asked in survey" = 99)
foreach(x=c(vote,region,income),{
annotation(x)["Remark"] <- "This is not a real survey item, of course ..."
})
missing.values(vote) <- c(8,9,97,99)
missing.values(region) <- c(97,99)
})
cpData1 <- codeplan(Data1)
Data2 <- data.frame(
vote = sample(c(1,2,3,8,9,97,99),size=300,replace=TRUE),
region = sample(c(rep(1,3),rep(2,2),3,99),size=300,replace=TRUE),
income = exp(rnorm(300,sd=.7))*2000
)
codeplan(Data2) <- cpData1
codebook(Data2)
# Note the difference between 'as.data.frame' and setting
# the codeplan to NULL:
Data2df <- as.data.frame(Data2)
codeplan(Data2) <- NULL
str(Data2)
str(Data2df)
# Codeplans of survey items can also be inquired and manipulated:
vote <- Data1$vote
str(vote)
cp.vote <- codeplan(vote)
codeplan(vote) <- NULL
str(vote)
codeplan(vote) <- cp.vote
votePlease choose more modern alternatives, such as Google Chrome or Mozilla Firefox.