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codeplan

Describe structure of Data Sets and Importers


Description

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.

Usage

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

Arguments

x

for codeplan(x) an object that inherits from class "item.list", i.e. can be a "data.set" object or an "importer" object, it can also be an object that inherits from class "item"

value

an object as it would be returned by codeplan(x) or NULL.

Value

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:

name

The name of the item/variable in the item list or data set.

description

The description/variable label string of the item/variable.

annotation

code to recreate the annotation attribute,

labels

code to recreate the value labels,

value.filter

code to recreate the value filter attribute (declaration of missing values, range of valid values, or an enumeration of valid values.)

mode

a character string that describes storage mode, such as "character", "integer", or "numeric".

measurement

a character string with the measurement level, "nominal", "ordinal", "interval", or "ratio".

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.

Examples

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
vote

memisc

Management of Survey Data and Presentation of Analysis Results

v0.99.27.3
GPL-2
Authors
Martin Elff (with contributions from Christopher N. Lawrence, Dave Atkins, Jason W. Morgan, Achim Zeileis)
Initial release
2020-11-18

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