var_to_merge: General function to choose variables to merge, limiting the...

In InseeFrLab/rtauargus: Using Tau-Argus from R

General function to choose variables to merge, limiting the number of generated tables while ensuring not to generate tables that are too large.

Description

General function to choose variables to merge, limiting the number of generated tables while ensuring not to generate tables that are too large.

Usage

var_to_merge(
  dfs,
  totcode,
  hrcfiles = NULL,
  nb_var = 4,
  nb_tab_option = "min",
  limit = 150
)

Arguments

dfs	data.frame
totcode	named vector of totals for categorical variables
hrcfiles	named vector of hrc files for categorical variables
nb_var	number of variables to merge
nb_tab_option	strategy to follow for choosing variables automatically: 'min': minimize the number of tables; 'max': maximize the number of tables; 'smart': minimize the number of tables under the constraint of their row count.
limit	maximum allowed row count in the 'smart' case

Value

A list of vectors representing the chosen variables to merge

Examples

library(dplyr)
data <- expand.grid(
  ACT = c("Total", "A", "B", "A1", "A2", "B1", "B2"),
  GEO = c("Total", "GA", "GB", "GA1", "GA2"),
  SEX = c("Total", "F", "M"),
  AGE = c("Total", "AGE1", "AGE2"),
  stringsAsFactors = FALSE,
  KEEP.OUT.ATTRS = FALSE
) %>%
  as.data.frame()

data <- data %>% mutate(VALUE = 1:n())

hrc_act <- "hrc_ACT.hrc"
sdcHierarchies::hier_create(root = "Total", nodes = c("A","B")) %>%
  sdcHierarchies::hier_add(root = "A", nodes = c("A1","A2")) %>%
  sdcHierarchies::hier_add(root = "B", nodes = c("B1","B2")) %>%
  sdcHierarchies::hier_convert(as = "argus") %>%
  slice(-1) %>%
  mutate(levels = substring(paste0(level,name),3)) %>%
  select(levels) %>%
  write.table(file = hrc_act, row.names = FALSE, col.names = FALSE, quote = FALSE)

hrc_geo <- "hrc_GEO.hrc"
sdcHierarchies::hier_create(root = "Total", nodes = c("GA","GB")) %>%
  sdcHierarchies::hier_add(root = "GA", nodes = c("GA1","GA2")) %>%
  sdcHierarchies::hier_convert(as = "argus") %>%
  slice(-1) %>%
  mutate(levels = substring(paste0(level,name),3)) %>%
  select(levels) %>%
  write.table(file = hrc_geo, row.names = FALSE, col.names = FALSE, quote = FALSE)

totcode <- c(SEX="Total",AGE="Total", GEO="Total", ACT="Total")

hrcfiles <- c(ACT = hrc_act, GEO = hrc_geo)

# Consistent: choose two hierarchical variables
res1 <- var_to_merge(dfs = data,
                                        totcode = totcode,
                                        hrcfiles = hrcfiles,
                                        nb_var = 2,
                                        nb_tab_option = 'max')
res1
max(unlist(length_tabs(dfs = data,
                       hrcfiles = hrcfiles,
                       totcode = totcode,
                       v1 = res1$vars[1], v2 = res1$vars[2])))

# Consistent: choose two non-hierarchical variables
res2 <- var_to_merge(dfs = data,
                                totcode = totcode,
                                hrcfiles = hrcfiles,
                                nb_var = 2,
                                nb_tab_option = 'min')
res2
max(unlist(length_tabs(dfs = data,
                       hrcfiles = hrcfiles,
                       totcode = totcode,
                       v1 = res2$vars[1], v2 = res2$vars[2])))

res3 <- var_to_merge(dfs = data,
                                totcode = totcode,
                                hrcfiles = hrcfiles,
                                limit = 200,
                                nb_var = 2,
                                nb_tab_option = 'smart')
res3
max(unlist(length_tabs(dfs = data,
                       hrcfiles = hrcfiles,
                       totcode = totcode,
                       v1 = res3$vars[1], v2 = res3$vars[2])))

# Obtains 147, which is well below 200

res4 <- var_to_merge(dfs = data,
                                totcode = totcode,
                                hrcfiles = hrcfiles,
                                limit = 5,
                                nb_var = 2,
                                nb_tab_option = 'smart')
res4
max(unlist(length_tabs(dfs = data,
                       hrcfiles = hrcfiles,
                       totcode = totcode,
                       v1 = res4$vars[1], v2 = res4$vars[2])))

# Receives a warning: unable to reach the announced value
# There are 63 rows (equivalent to the max
# -> this is what reduces the table size)
# And the warning announces 63 rows, which is consistent with the output

InseeFrLab/rtauargus documentation built on Feb. 25, 2025, 6:32 a.m.