June 2026 splash

Author: Gonçalo Marques

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: lissyrtools
 Title: Tools for LISSY Jobs
-Version: 0.2.3
+Version: 0.2.4
 Authors@R: c(
     person("Gonçalo", "Marques", , "marques@lisdatacenter.org", role = c("aut", "cre")),
     person("Josep", "Espasa Reig" , ,"jespasareig@gmail.com", role = c("aut"))

NEWS.md

@@ -1,5 +1,19 @@
 # lissyrtools
 
+# lissyrtools 0.2.4 (2026-06-15)
+
+## New functions
+## Major changes
+
+- Added a new character argument `pattern` to `variable_labels()`.
+
+## Minor changes
+
+- Bug fix in the body of  `structure_to_plot()`.
+- The complementary table `lissyrtools::missing_or_zero_vars_all` is now created in a more efficient way and includes a `cname` column.
+- Output of `variable_has_note()` and `variable_exists()` now displays country names and not their iso2 codes. 
+
+
 # lissyrtools 0.2.3 (2026-03-15)
 
 ## New functions

R/countries_and_years.R

@@ -13,7 +13,7 @@ get_countries_lis <- function() {
     dplyr::select(cname, iso2) %>%
     tibble::deframe()
 
-  attributes(output)[1] <- NULL
+  #attributes(output)[1] <- NULL
 
   return(output)
 }
@@ -34,7 +34,7 @@ get_countries_lws <- function() {
     dplyr::select(cname, iso2) %>%
     tibble::deframe()
 
-  attributes(output)[1] <- NULL
+  #attributes(output)[1] <- NULL
 
   return(output)
 }
@@ -81,7 +81,7 @@ get_years_lis <- function(iso2) {
       dplyr::arrange(year) %>%
       dplyr::pull()
 
-    attributes(years_to_output)[1] <- NULL
+    #attributes(years_to_output)[1] <- NULL
 
     return(years_to_output)
   }
@@ -134,7 +134,7 @@ get_years_lws <- function(iso2) {
       dplyr::arrange(year) %>%
       dplyr::pull()
 
-    attributes(years_to_output)[1] <- NULL
+    #attributes(years_to_output)[1] <- NULL
 
     return(years_to_output)
   }

R/data.R

@@ -44,7 +44,7 @@
 #'
 #' A data frame that identifies whether a variable consists only of zeros or missing values for a given country and year.
 #'
-#' @format A data frame with 6 variables:
+#' @format A data frame with 7 variables:
 "missing_or_zero_vars_all"
 
 

R/get_labels_notes_surveys.R

@@ -1,25 +1,31 @@
 #' Inspect the Labels of LIS and LWS variables
 #'
 #' @param vars A character vector containing LIS/LWS variables or the output list from lissyuse.
+#' @param pattern A character.  
 #'
-#' @return A character vector with the corresponding labels for the selected variables.
+#' @return A character vector with the corresponding labels for the selected variables, or where the pattern was detected in its label. 
 #' @export
 #'
 #' @examples
+#' \dontrun{
 #' # 1) Without any argument:
 #' variable_labels()
 #' 
-#' \dontrun{
+
 #' # 2) Using with the outputed list from lissyuse:
 #' lis_datasets <- lissyuse(data = c("uk"), vars = c("hpub_i","hpub_u", "hi42", "hi421", "hi422", "hi43"), from = 2016)
 #' variable_labels(vars = lis_datasets)
-#' }
+
 #' 
 #' # 3) Using a character vector with LIS/LWS variables:
 #' variable_labels(vars = c("fyft", "basb", "hxremit", "bafi1_c", "pasodc"))
-variable_labels <- function(vars = NULL) {
-  
-  if (is.null(vars)) {
+#' 
+#' # 4) Using pattern argument: 
+#' variable_labels(pattern = "occupa")
+#' variable_labels(pattern = "capital")
+#' }
+variable_labels <- function(vars = NULL, pattern = NULL) {
+  if (is.null(vars) & is.null(pattern)) {
     output <- tibble::deframe(lissyrtools::data_vars_labels)
     return(output)
   } else if (!(is.null(vars))) {
@@ -58,6 +64,22 @@ variable_labels <- function(vars = NULL) {
         return(output)
       }
     }
+  } else if (!(is.null(pattern))) {
+    if (!is.character(pattern)) {
+      stop(glue::glue(
+        "Argument `pattern` only accepts characters."
+      ))
+    } else {
+      output <- lissyrtools::data_vars_labels[
+        stringr::str_detect(
+          lissyrtools::data_vars_labels$label,
+          pattern = pattern
+        ),
+      ] %>%
+        tibble::deframe()
+
+      return(output)
+    }
   }
 }
 
@@ -73,20 +95,23 @@ variable_labels <- function(vars = NULL) {
 #' @examples
 #' variable_has_note(variable = "area_c", iso2 = "br")
 #' variable_has_note(variable = "basb", iso2 = c("fr", "de", "us", "uk"), lws = TRUE)
+#' 
+#' To check the notes on METIS go to: https://www.lisdatacenter.org/frontend#/home, and select a database and a given country:.
+#' Afterwards, head to 'RESULTS' > 'Dataset information' > 'Code Books'.
 variable_has_note <- function(variable, iso2, lws = FALSE) {
 
   # Ensure that argument 'variable' only accepts one character
-
+  
   if (length(variable) > 1) {
     stop(
       glue::glue(
         "Argument `variable` accepts no more than one character."
       )
     )
   }
-
+  
   # Ensure the validity of the variable
-
+  
   if (lws) {
     invalid_var <- variable[!variable %in% lissyrtools::lws_variables]
     if (length(invalid_var) > 0) {
@@ -102,17 +127,17 @@ variable_has_note <- function(variable, iso2, lws = FALSE) {
       ))
     }
   }
-
+  
   # Ensure the validity of the iso2 codes
-
+  
   valid_iso2 <- if (lws) {
     lissyrtools::get_countries_lws()
   } else {
     lissyrtools::get_countries_lis()
   }
-
+  
   invalid_iso2 <- iso2[!iso2 %in% valid_iso2]
-
+  
   if (length(invalid_iso2) == length(iso2)) {
     # If no valid iso2 codes, stop with an error
     stop(
@@ -130,7 +155,7 @@ variable_has_note <- function(variable, iso2, lws = FALSE) {
       )
     )
   }
-
+  
   # body of the function
   process_country <- function(i) {
     db <- if (lws) "LWS" else "LIS"
@@ -139,23 +164,40 @@ variable_has_note <- function(variable, iso2, lws = FALSE) {
     } else {
       lissyrtools::get_years_lis
     }
-
+    
     years <- get_years_function(i)[[1]]
-
+    
     existing_years <- lissyrtools::data_with_warnings %>%
       dplyr::filter(database == db, iso2 == i, var_name == variable) %>%
       dplyr::pull(year)
-
+    
     year_status <- ifelse(years %in% existing_years, "Yes", "No")
     names(year_status) <- years
     return(year_status)
   }
-
+  
   to_be_used_iso2 <- iso2[iso2 %in% valid_iso2]
   result <- purrr::map(to_be_used_iso2, process_country)
-  names(result) <- to_be_used_iso2
-
+  
+  
+  # Naming the list 
+  naming_funct <- function(x) {
+    
+    vector_out <- c()
+    
+    for (i  in to_be_used_iso2) {
+      country_idx <- lissyrtools::metis_countries_df %>% dplyr::filter(iso2 == i)  %>% dplyr::select(name)  %>% dplyr::pull()
+      vector_out[i] <- country_idx
+    }
+    vector_out <- unname(vector_out)
+    
+    return(vector_out)
+  }
+  
+  names(result) <- naming_funct(to_be_used_iso2) 
+  
   return(result)
+  
 }
 
 

R/variable_exists.R

@@ -17,17 +17,17 @@
 variable_exists <- function(variable, iso2, lws = FALSE, share = FALSE) {
 
   # Ensure that argument 'variable' only accepts one character
-
+  
   if (length(variable) > 1) {
     stop(
       glue::glue(
         "Argument `variable` accepts no more than one character."
       )
     )
   }
-
+  
   # ensure the validity of the variable
-
+  
   if (lws) {
     invalid_var <- variable[!variable %in% lissyrtools::lws_variables]
     if (length(invalid_var) > 0) {
@@ -43,17 +43,17 @@ variable_exists <- function(variable, iso2, lws = FALSE, share = FALSE) {
       ))
     }
   }
-
+  
   # ensure the validity of the iso2 codes
-
+  
   valid_iso2 <- if (lws) {
     lissyrtools::get_countries_lws()
   } else {
     lissyrtools::get_countries_lis()
   }
-
+  
   invalid_iso2 <- iso2[!iso2 %in% valid_iso2]
-
+  
   if (length(invalid_iso2) == length(iso2)) {
     # If no valid iso2 codes, stop with an error
     stop(
@@ -71,7 +71,7 @@ variable_exists <- function(variable, iso2, lws = FALSE, share = FALSE) {
       )
     )
   }
-
+  
   # body of the function
   if (share == FALSE) {
     process_country <- function(i) {
@@ -81,49 +81,69 @@ variable_exists <- function(variable, iso2, lws = FALSE, share = FALSE) {
       } else {
         lissyrtools::get_years_lis
       }
-
+      
       years <- get_years_function(i)[[1]]
-
+      
       existing_var_years <- lissyrtools::missing_or_zero_vars_all %>%
         dplyr::filter(
           database == db &
             iso2 == i &
             variable == {{ variable }} &
-            status == FALSE
+            missing_status == FALSE
         ) %>%
         dplyr::pull(year)
-
+      
       year_status <- ifelse(years %in% existing_var_years, "Yes", "No")
       names(year_status) <- years
       return(year_status)
     }
-
+    
     to_be_used_iso2 <- iso2[iso2 %in% valid_iso2]
     result <- purrr::map(to_be_used_iso2, process_country)
-    names(result) <- to_be_used_iso2
-
+    
+    # Naming the list 
+    naming_funct <- function(x) {
+      
+      vector_out <- c()
+      
+      for (i  in to_be_used_iso2) {
+        country_idx <- lissyrtools::metis_countries_df %>% dplyr::filter(iso2 == i)  %>% dplyr::select(name)  %>% dplyr::pull()
+        vector_out[i] <- country_idx
+      }
+      vector_out <- unname(vector_out)
+      
+      return(vector_out)
+    }
+    
+    names(result) <- naming_funct(to_be_used_iso2)
+    
     return(result)
+    
   } else if (share == TRUE) {
+    
     db <- if (lws) "LWS" else "LIS"
+    
     to_be_used_iso2 <- iso2[iso2 %in% valid_iso2]
-
+    
     share_to_output <- lissyrtools::missing_or_zero_vars_all %>%
       dplyr::filter(
         database == db,
         iso2 %in% to_be_used_iso2,
         variable == {{ variable }}
       ) %>%
-      dplyr::group_by(iso2, {{ variable }}) %>%
+      dplyr::group_by(cname, {{ variable }}) %>%
       dplyr::summarise(
-        share = 100 - (sum(status) / dplyr::n() * 100),
+        share = 100 - (sum(missing_status) / dplyr::n() * 100),
         .groups = "drop"
       ) %>%
-      dplyr::select(iso2, share) %>%
+      dplyr::select(cname, share) %>%
       dplyr::mutate(share = round(share, digits = 1)) %>%
       tibble::deframe()
-
+    
     result <- list()
+    
     result[[1]] <- share_to_output
+    
     names(result) <- paste0(
       "Share of years across the series in ",
       dplyr::if_else(lws, "LWS", "LIS"),
@@ -132,5 +152,6 @@ variable_exists <- function(variable, iso2, lws = FALSE, share = FALSE) {
       " has values other than zeros and missings."
     )
     return(result)
+    
   }
-}
+}

data-raw/LWS_income_reference_year_adjustment_data.R

@@ -28,6 +28,12 @@ data_inc_ref_year <- tibble::tribble(
   "cl17",                  2017L,
   "cl21",                  2021L,
   "cl24",                  2024L,
+  "cz21",                  2020L,
+  "fi87",                  1987L,
+  "fi88",                  1988L,
+  "fi94",                  1994L, 
+  "fi98",                  1998L,
+  "fi04",                  2004L, 
   "fi09",                  2009L,
   "fi13",                  2013L,
   "fi16",                  2016L,