DDIwR (version 0.20)

getCodebook: Extract metadata information

Description

Extract a list containing the variable labels, value labels and any available information about missing values.

Usage

getCodebook(from = NULL, encoding = "auto", ignore = NULL, ...)

Value

An R list roughly equivalent to a DDI Codebook, containing all variables, their corresponding variable labels and value labels, and (if applicable) missing values if imported and found.

Arguments

from

A path to a file, or a data frame object

encoding

The character encoding used to read a file

ignore

Character, ignore DDI elements when reading from an XML file

...

Additional arguments for this function (internal use only)

Author

Adrian Dusa

Details

This function extracts the metadata from an R dataset, or alternatively it can read an XML file containing a DDI Codebook version 1.2.2, 2.5 or 2.6, or an SPSS or Stata file and returns a list containing the variable labels, value labels and information about the missing values.

If the input is a dataset, it will extract the variable level metadata (labels, missing values etc.). From a DDI XML file, it will import all metadata elements, the most expensive being the data description.

It additionally attempts to automatically detect a type for each variable:

cat:	categorical variable using numeric values
catchar:	categorical variable using character values
catnum:	categorical variable for which numerical summaries
	can be calculated (ex. a 0...10 Likert response scale)
num:	numerical
numcat:	numerical variable with few enough values (ex. number of children)
	for which a table of frequencies is possible in addition to frequencies

Apart from utf8, other encodings might be necessary when reading from SPSS or DDI XML files, for instance latin1 or windows-1252, and it also accepts bytes for multi-byte encodings. To use the one specified in the file, set encoding = NULL. The default is encoding = "auto", which tries to detect the encoding automatically.

For the moment, only DDI Codebook is supported, but DDI Lifecycle is planned to be implemented.

Examples

x <- data.frame(
    A = declared(
        c(1:5, -92),
        labels = c(Good = 1, Bad = 5, NR = -92),
        na_values = -92
    ),
    C = declared(
        c(1, -91, 3:5, -92),
        labels = c(DK = -91, NR = -92),
        na_values = c(-91, -92)
    )
)

getCodebook(from = x)