Merge pull request #34 from antaldaniel/master

roxygen and tidyselect changes

Author: antaldaniel

DESCRIPTION

@@ -1,25 +1,19 @@
 Type: Package
 Package: retroharmonize
 Title: Ex Post Survey Data Harmonization
-Version: 0.2.5.002
-Date: 2022-09-24
+Version: 0.2.5.003
+Date: 2023-12-01
 Authors@R: c(
-    person("Daniel", "Antal", , "[email protected]", role = c("aut", "cre"),
+    person(given = "Daniel", 
+           family = "Antal", 
+           email = "[email protected]",
+           role = c("aut", "cre"),
            comment = c(ORCID = "0000-0001-7513-6760")),
       person(given = "Marta",
-           family = "Kolczynska",
-           role = c("ctb"),
-           email = "[email protected]",
-           comment = c(ORCID = "0000-0003-4981-0437")), 
-      person(given = "Pyry",
-             family = "Kantanen", 
-             role = "ctb", 
-             comment = c(ORCID = "0000-0003-2853-2765")),
-      person(given = "Leo", 
-             family = " Lahti", 
-             role = "ctb", 
-             comment = c(ORCID = "0000-0001-5537-637X")
-             )
+             family = "Kolczynska",
+             role = c("ctb"),
+             email = "[email protected]",
+             comment = c(ORCID = "0000-0003-4981-0437"))
       )
 Maintainer: Daniel Antal <[email protected]>
 Description: Assist in reproducible retrospective (ex-post) harmonization
@@ -69,6 +63,6 @@ Config/testthat/edition: 3
 Encoding: UTF-8
 Language: en-US
 LazyData: true
-RoxygenNote: 7.2.1
+RoxygenNote: 7.2.3
 X-schema.org-isPartOf: http://ropengov.org/
 X-schema.org-keywords: ropengov

R/collect_val_labels.R

@@ -1,4 +1,4 @@
-#' Collect labels from metadata file
+#' @title Collect labels from metadata file
 #' 
 #' @param metadata A metadata data frame created by 
 #' \code{\link{metadata_create}}.

R/create_codebook.R

@@ -83,32 +83,32 @@ create_codebook <- function ( metadata = NULL,
   if ( n_labelled_numeric  > 0 ) {
     # These area cases when the labels are of class numeric
     valid_labelled_numeric <-  metadata_labelled_numeric %>%
-      filter ( grepl( "labelled", .data$class_orig )) %>%
+      filter ( grepl( "labelled", class_orig )) %>%
       select ( all_of(c("entry", "id", "filename", "var_name_orig", "var_label_orig", "valid_labels")))   %>%
-      unnest_longer( .data$valid_labels) %>%
+      unnest_longer( valid_labels) %>%
       rlang::set_names ( c("entry", "id", "filename", "var_name_orig","var_label_orig",  "val_code_orig", "val_label_orig")) %>%
       mutate ( 
         # This is the valid observation range
         label_range = "valid", 
-        val_code_orig = as.character(.data$val_code_orig))  
+        val_code_orig = as.character(val_code_orig))  
 
     na_labelled_numeric <-  metadata[num_labels ,] %>%
-      filter ( grepl( "labelled", .data$class_orig )) %>%
+      filter ( grepl( "labelled", class_orig )) %>%
       select ( all_of(c("entry", "id", "filename", "var_name_orig", "var_label_orig",  "na_labels"))) %>%
-      unnest_longer( .data$na_labels) %>%
+      unnest_longer( na_labels) %>%
       purrr::set_names ( c("entry", "id", "filename", "var_name_orig", "var_label_orig",  "val_code_orig", "val_label_orig")) %>%
       mutate ( 
         # This is the missing observation range
         label_range = "missing") %>%
-      filter ( !is.na(.data$val_code_orig) ) %>%
-      mutate ( val_code_orig = as.character(.data$val_code_orig) )
+      filter ( !is.na(val_code_orig) ) %>%
+      mutate ( val_code_orig = as.character(val_code_orig) )
 
 
     num_labels <- valid_labelled_numeric  %>% 
       dplyr::bind_rows (
         na_labelled_numeric 
       ) %>%
-      dplyr::arrange( .data$entry, .data$val_code_orig ) %>%
+      dplyr::arrange( entry, val_code_orig ) %>%
       left_join ( metadata %>% select ( any_of(c("entry", "id", "filename", "na_range", 
                                                  "n_labels", "n_valid_labels", "n_na_labels", 
                                                  user_vars))), 
@@ -126,34 +126,34 @@ create_codebook <- function ( metadata = NULL,
   if ( n_labelled_character > 0) {
     # These area cases when the na_labels are of class character
     valid_labelled_character  <-   metadata_labelled_character %>%
-      filter ( grepl( "labelled", .data$class_orig )) %>%
+      filter ( grepl( "labelled", class_orig )) %>%
       select ( all_of(c("entry", "id", "filename", "var_name_orig", "var_label_orig", "valid_labels")))   %>%
-      unnest_longer( .data$valid_labels) %>%
+      unnest_longer( valid_labels) %>%
       rlang::set_names ( c("entry", "id", "filename", "var_name_orig","var_label_orig",  "val_code_orig", "val_label_orig")) %>%
       mutate ( 
         # This is the valid observation range
         label_range = "valid")  %>%
-      mutate ( val_code_orig = as.character(.data$val_code_orig) )
+      mutate ( val_code_orig = as.character(val_code_orig) )
 
 
     na_labelled_character <-  metadata[char_labels ,] %>%
-      filter ( grepl( "labelled", .data$class_orig )) %>%
+      filter ( grepl( "labelled", class_orig )) %>%
       select ( all_of(c("entry", "id", "filename", "var_name_orig", "var_label_orig",  "na_labels"))) %>%
-      unnest_longer( .data$na_labels) %>%
+      unnest_longer( na_labels) %>%
       purrr::set_names ( c("entry", "id", "filename", "var_name_orig", "var_label_orig",  
                            "val_code_orig", "val_label_orig")) %>%
       mutate ( 
         # This is the missing observation range
         label_range = "missing") %>%
-      filter ( !is.na(.data$val_code_orig)) %>%
-      mutate ( val_code_orig = as.character(.data$val_code_orig) )
+      filter ( !is.na(val_code_orig)) %>%
+      mutate ( val_code_orig = as.character(val_code_orig) )
 
 
     char_labels <- valid_labelled_character %>% 
       dplyr::bind_rows (
         na_labelled_character 
       ) %>%
-      dplyr::arrange( .data$entry, .data$val_code_orig ) %>%
+      dplyr::arrange( entry, val_code_orig ) %>%
       left_join ( metadata %>% select ( any_of(c("entry", "id", "filename", "na_range", 
                                                  "n_labels", "n_valid_labels", "n_na_labels", 
                                                  user_vars))), 
@@ -178,14 +178,14 @@ create_codebook <- function ( metadata = NULL,
       left_join ( user_data[0,], by = "entry" )
   } else if ( n_labelled_character == 0 ) {
     num_labels %>%
-      dplyr::arrange (.data$entry)
+      dplyr::arrange (entry)
   } else if ( n_labelled_numeric == 0  ) {
     char_labels %>%
-      dplyr::arrange (.data$entry)
+      dplyr::arrange (entry)
   } else {
    num_labels %>%
       bind_rows ( char_labels) %>%
-      dplyr::arrange (.data$entry)
+      dplyr::arrange (entry)
   }
 }
 

R/crosswalk.R

@@ -25,7 +25,6 @@
 #' data frames, where the variable names, and optionally the variable labels, and the missing 
 #' value range is harmonized (the same names, labels, codes are used.)
 #' @importFrom dplyr filter select mutate distinct_all relocate across everything
-#' @importFrom rlang .data
 #' @importFrom assertthat assert_that
 #' @family harmonization functions
 #' @examples 
@@ -90,7 +89,7 @@ crosswalk_surveys <- function(crosswalk_table,
                 msg = "selection must have rows")
 
     select_to_harmonize <- selection %>%
-      filter ( !is.na(.data$val_label_orig) )
+      filter ( !is.na(val_label_orig) )
 
     vars_to_harmonize <- unique(select_to_harmonize$var_name_target) 
 
@@ -102,7 +101,7 @@ crosswalk_surveys <- function(crosswalk_table,
     for ( this_var in vars_to_harmonize ) {
 
       correspondence_table <- select_to_harmonize %>%
-        filter ( .data$var_name_target == this_var ) 
+        filter ( var_name_target == this_var ) 
 
       assert_that(is.numeric(correspondence_table$val_numeric_target), 
                   msg = "Error in relabel_survey: 'val_numeric_target' must be a numeric vector")
@@ -138,15 +137,15 @@ crosswalk_surveys <- function(crosswalk_table,
   subset_survey <- function(this_survey) {
 
     survey_id <- attr(this_survey, "id")
-    assertthat::assert_that(length(survey_id)>0, 
-                            msg = "Error in subset_survey(): survey_id has 0 length.")
+    assert_that(length(survey_id)>0, 
+                msg = "Error in subset_survey(): survey_id has 0 length.")
 
     tmp <- this_survey %>% 
       mutate ( id = survey_id ) %>%
-      relocate ( .data$id, .before = everything())
+      relocate ( id, .before = everything())
 
     selection <- crosswalk_table %>% 
-      filter ( .data$id == survey_id ) %>%
+      filter ( id == survey_id ) %>%
       distinct_all()
 
 
@@ -322,8 +321,8 @@ crosswalk_table_create <- function(metadata) {
   if (nrow(metadata)==1) {
     fn_labels(x=metadata[1,])
   } else {
-    ctable_list <- lapply ( 1:nrow(metadata), function(x) fn_labels(metadata[x,])  )
-    ctable <- suppressMessages(purrr::reduce ( ctable_list, full_join ))
+    ctable_list <- lapply (1:nrow(metadata), function(x) fn_labels(metadata[x,]))
+    ctable <- suppressMessages(purrr::reduce(ctable_list, full_join))
     ctable
   }
 }
@@ -332,7 +331,6 @@ crosswalk_table_create <- function(metadata) {
 #' @rdname crosswalk_table_create 
 #' @param ctable A table to validate if it is a crosswalk table.
 #' @importFrom dplyr tally group_by across filter
-#' @importFrom rlang .data
 #' @family metadata functions
 #' @export
 
@@ -351,8 +349,8 @@ is.crosswalk_table <- function(ctable) {
     distinct_all() %>%
     group_by ( across(c("var_name_target", "id"))) %>%
     tally() %>%
-    filter ( .data$n>1) %>%
-    select (.data$var_name_target ) %>%
+    filter ( n>1) %>%
+    select (var_name_target ) %>%
     unlist()
 
   error_msg <- paste(unique(duplicates), collapse = ', ')

R/document_survey_item.R

@@ -72,8 +72,8 @@ document_survey_item <- function(x) {
   tbl_length <- nrow(coding)
 
   list (
-    code_table = dplyr::bind_cols(coding, labelling) %>%
-      mutate ( missing = ifelse (.data$values %in% attr(x, "na_values"), 
+    code_table = bind_cols(coding, labelling) %>%
+      mutate ( missing = ifelse (values %in% attr(x, "na_values"), 
                                  TRUE, FALSE)), 
     history_var_name = c(
       c("name" = original_x_name ), 

R/harmonize_survey_variables.R

@@ -65,15 +65,15 @@ harmonize_survey_variables <- function( crosswalk_table,
     new_names <- tibble( var_name_orig = names(this_survey)) %>%
       left_join (
         crosswalk_table %>% 
-          filter (.data$id == survey_id) %>% 
-          select ( .data$var_name_orig, .data$var_name_target ) %>%
+          filter (id == survey_id) %>% 
+          select ( var_name_orig, var_name_target ) %>%
           distinct_all(), 
         by = "var_name_orig",
       ) %>% 
-      mutate ( var_name_target = ifelse (.data$var_name_orig == "rowid", 
+      mutate ( var_name_target = ifelse (var_name_orig == "rowid", 
                                          yes = "rowid", 
-                                         no = .data$var_name_target)) %>% 
-      select ( .data$var_name_target ) %>% unlist() %>% as.character()
+                                         no = var_name_target)) %>% 
+      select ( var_name_target ) %>% unlist() %>% as.character()
 
     rlang::set_names(this_survey, nm = new_names )
 
@@ -96,15 +96,15 @@ harmonize_survey_variables <- function( crosswalk_table,
     new_names <- tibble( var_name_orig = names(this_survey)) %>%
       left_join (
         crosswalk_table %>% 
-          filter (.data$id == survey_id) %>% 
-          select ( .data$var_name_orig, .data$var_name_target ) %>%
+          filter (id == survey_id) %>% 
+          select ( var_name_orig, var_name_target ) %>%
           distinct_all(), 
         by = "var_name_orig",
       ) %>%
-      mutate ( var_name_target = ifelse (.data$var_name_orig == "rowid", 
+      mutate ( var_name_target = ifelse (var_name_orig == "rowid", 
                                          yes = "rowid", 
-                                         no = .data$var_name_target)) %>% 
-      select ( .data$var_name_target ) %>% unlist() %>% as.character()
+                                         no = var_name_target)) %>% 
+      select ( var_name_target ) %>% unlist() %>% as.character()
 
     this_survey <- rlang::set_names(this_survey, nm = new_names )
     saveRDS(this_survey, file = file.path(export_path, x), version = 2 )

R/metadata_create.R

@@ -90,7 +90,6 @@ metadata_waves_create <- function(survey_list) {
 #' @importFrom labelled na_values na_range val_labels var_label
 #' @importFrom purrr map
 #' @importFrom assertthat assert_that
-#' @importFrom rlang .data
 #' @family metadata functions
 #' @return A nested data frame with metadata and the range of 
 #' labels, na_values and the na_range itself.
@@ -219,14 +218,14 @@ metadata_survey_create <- function(survey) {
 
   return_df <- metadata %>%
     left_join (  range_df %>% 
-                   group_by ( .data$var_name_orig ) %>%
+                   group_by ( var_name_orig ) %>%
                    tidyr::nest(), 
                 by = "var_name_orig") %>%
     tidyr::unnest ( cols = "data" )  %>%
     ungroup() %>%
-    mutate ( n_na_labels = as.numeric(.data$n_na_labels), 
-             n_valid_labels = as.numeric(.data$n_valid_labels), 
-             n_labels = as.numeric(.data$n_labels)) %>%
+    mutate ( n_na_labels = as.numeric(n_na_labels), 
+             n_valid_labels = as.numeric(n_valid_labels), 
+             n_labels = as.numeric(n_labels)) %>%
     as.data.frame()
 
   change_label_to_empty <- function() {
@@ -247,7 +246,7 @@ metadata_survey_create <- function(survey) {
                                 no =  return_df$na_labels )
 
   return_df %>%
-    select ( -.data$label_type )
+    select ( -label_type )
 }
 
 

R/pull_survey.R

@@ -1,6 +1,6 @@
-#' Pull a survey from a survey list
+#' @title Pull a survey from a survey list
 #' 
-#' Pull a survey by survey code or id.
+#' @description Pull a survey by survey code or id.
 #' 
 #' @param survey_list A list of surveys
 #' @param id The id of the requested survey. If \code{NULL} use 

R/read_spss.R

@@ -18,6 +18,7 @@
 #' \code{tibble::\link[tibble:as_tibble]{as_tibble}} for details.
 #' @inheritParams read_rds
 #' @importFrom haven read_spss read_sav write_sav is.labelled
+#' @importFrom assertthat assert_that
 #' @importFrom tibble rowid_to_column as_tibble
 #' @importFrom fs path_ext_remove path_file is_file
 #' @importFrom labelled var_label
@@ -58,7 +59,7 @@ read_spss <- function(file,
 
   source_file_info <- valid_file_info(file)
 
-  safely_read_haven_spss <- purrr::safely(.f = haven::read_spss)
+  safely_read_haven_spss <- safely(.f = haven::read_spss)
 
   tmp <- safely_read_haven_spss (file = file, 
                                  user_na = user_na, 
@@ -78,13 +79,13 @@ read_spss <- function(file,
 
   all_vars <- names(tmp)
 
-  assertthat::assert_that(length(all_vars)>0, 
-                          msg = "The SPSS file has no names.")
+  assert_that(length(all_vars)>0, 
+              msg = "The SPSS file has no names.")
 
-  filename <- fs::path_file(file)
+  filename <- path_file(file)
 
   if ( is.null(id) ) {
-    id <- fs::path_ext_remove ( filename )
+    id <- path_ext_remove(filename)
   }
 
   if ( is.null(doi)) {
@@ -161,7 +162,7 @@ read_spss <- function(file,
   return_survey <- survey (return_df, id=id, filename=filename, doi=doi)
 
   object_size <- as.numeric(object.size(as_tibble(return_df)))
-  attr(return_survey, "object_size") <- object_size
+  attr(return_survey, "object_size")      <- object_size
   attr(return_survey, "source_file_size") <- source_file_info$size
 
   return_survey