pnds_labeller {PNDSIBGE}

Label categorical variables from PNDS microdata

Description

This function labels categorical variables from PNDS microdata.

Usage

pnds_labeller(data_pnds, dictionary.file)

Arguments

data_pnds

A tibble of PNDS microdata read with read_pnds function.

dictionary.file

The dictionary file for selected survey available on official website: (select the dictionary and input zip file, according to the appropriated year, microdata folder and then, inside, documentation) - ‘⁠https://ftp.ibge.gov.br/PNDS/⁠’.

Value

A tibble with the data provided from PNDS survey and its categorical variables as factors with related labels.

Note

For more information, visit the survey official website <https://www.ibge.gov.br/estatisticas/sociais/saude/9160-pesquisa-nacional-de-demografia-e-saude.html?=&t=o-que-e> and consult the other functions of this package, described below.

See Also

get_pnds for downloading, labeling, deflating and creating survey design object for PNDS microdata.
read_pnds for reading PNDS microdata.
pnds_deflator for adding deflator variables to PNDS microdata.
pnds_design for creating PNDS survey design object.
pnds_example for getting the path of the PNDS toy example files.

Examples

# Using data read from disk
input_path <- pnds_example(path="input_example.txt")
data_path <- pnds_example(path="exampledata.txt")
dictionary.path <- pnds_example(path="dictionaryexample.xls")
pnds.df <- read_pnds(microdata=data_path, input_txt=input_path, vars=c("J007","J009"))
pnds.df <- pnds.df[(pnds.df$M001 == "1" & !is.na(pnds.df$M001)),]
pnds.df <- pnds.df[,!(names(pnds.df) %in% c("V0029", "V00291", "V00292", "V00293"))]
pnds.df <- pnds_labeller(data_pnds=pnds.df, dictionary.file=dictionary.path)

# Downloading data
pnds.df2 <- get_pnds(year=2023, section="Female", vars=c("J007","J009"),
                       labels=FALSE, deflator=FALSE, design=FALSE,
                       reload=TRUE, curlopts=list(), savedir=tempdir())
dictionary.path2 <- pnds_example(path="dictionaryexample.xls")
pnds.df2 <- pnds_labeller(data_pnds=pnds.df2, dictionary.file=dictionary.path2)