## ----include = FALSE------------------------------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----setup----------------------------------------------------------------------------------------
library(eatGADS)
db_path <- system.file("extdata", "pisa.db", package = "eatGADS")
db_path

## ----structure------------------------------------------------------------------------------------
nam <- namesGADS(db_path)
nam

## ----extractMeta----------------------------------------------------------------------------------
# Meta data for one variable
extractMeta(db_path, "age")

## ----extractMeta all------------------------------------------------------------------------------
extractMeta(db_path, nam$PVs)

## ----extractMeta description----------------------------------------------------------------------
# Meta data for manually chosen multiple variables
extractMeta(db_path, c("idstud", "schtype"))

## ----getGADS--------------------------------------------------------------------------------------
gads1 <- getGADS(filePath = db_path, vSelect = c("idstud", "schtype", "gender"))
class(gads1)
extractMeta(gads1)

## ----extractdata----------------------------------------------------------------------------------
## leave all labeled variables as numeric, convert missings to NA
dat1 <- extractData2(gads1)
head(dat1)

## convert selected labeled variable(s) to character, convert missings to NA
dat2 <- extractData2(gads1, labels2character = c("schtype"))
head(dat2)

## convert all labeled variables to character, convert missings to NA
dat3 <- extractData2(gads1, labels2character = namesGADS(gads1))
head(dat3)


## ----noImp hierarchy levels-----------------------------------------------------------------------
gads1 <- getGADS(db_path, vSelect = c("schtype", "g8g9"))
dat1 <- extractData2(gads1)
dim(dat1)
head(dat1)

## ----PVs hierarchy levels-------------------------------------------------------------------------
gads2 <- getGADS(db_path, vSelect = c("schtype", "value"))
dat2 <- extractData2(gads2)
dim(dat2)
head(dat2)

## ----trendPaths-----------------------------------------------------------------------------------
trend_path1 <- system.file("extdata", "trend_gads_2020.db", package = "eatGADS")
trend_path2 <- system.file("extdata", "trend_gads_2015.db", package = "eatGADS")
trend_path3 <- system.file("extdata", "trend_gads_2010.db", package = "eatGADS")

## ----getTrendGADS---------------------------------------------------------------------------------
gads_trend <- getTrendGADS(filePaths = c(trend_path1, trend_path2, trend_path3), 
                           vSelect = c("idstud", "dimension", "score"), 
                           years = c(2020, 2015, 2010), fast = FALSE)
dat_trend <- extractData2(gads_trend)
head(dat_trend)