version 1.0.3

DESCRIPTION

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+Package: countries
+Type: Package
+Title: Deal with Country Data in an Easy Way
+Version: 1.0.3
+Authors@R: 
+    person("Francesco Saverio", "Bellelli", , "fsabellelli@gmail.com", role = c("aut", "cre", "cph"),
+           comment = c(Website = "https://fbellelli.com/"))
+Description: Wrangle country data more effectively and quickly. 
+    This package contains functions to easily identify and convert country names,
+    download country information, merge country data from different sources, 
+    and make quick world maps.
+License: GPL-3
+Encoding: UTF-8
+RoxygenNote: 7.2.3
+Imports: stringdist, tidyr, stringr, dplyr, knitr, fastmatch,
+        lubridate, utils, methods, stats, httr, jsonlite, ggplot2,
+        viridis, grDevices
+Suggests: data.table, rmarkdown, testthat
+Depends: R (>= 2.10)
+VignetteBuilder: knitr
+URL: https://fbellelli.github.io/countries/,
+        https://github.com/fbellelli/countries
+BugReports: https://github.com/fbellelli/countries/issues
+Config/testthat/edition: 3
+LazyData: true
+NeedsCompilation: no
+Packaged: 2023-09-01 13:31:41 UTC; FSB
+Author: Francesco Saverio Bellelli [aut, cre, cph] (https://fbellelli.com/)
+Maintainer: Francesco Saverio Bellelli <fsabellelli@gmail.com>
+Repository: CRAN
+Date/Publication: 2023-09-01 15:50:02 UTC

MD5

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+b947eb5cdb99f4e362d6b6b5a1ca8b4e *DESCRIPTION
+a95ab0a827028110692a7dae2aa99101 *NAMESPACE
+0e6122e6aa53c9d8e83c9c47e1bbc3ae *NEWS.md
+44d2cae832bf363be8ac99818104adc8 *R/auto_melt.R
+3438b2c41e9c5a049d9b31e0714995d3 *R/auto_merge.R
+b263764e99818915c3af9f626a0bc694 *R/check_wide_format.R
+d19385c957b0aebccd98e06d0a002099 *R/country_info.R
+e7af7478b451016330354b213dab11e5 *R/country_name.R
+9d42485df3c3364640c7884eae4f95e5 *R/data_long.R
+988b9c53e5c74cbcc7e34f576383c778 *R/data_wide.R
+d68c0805e97fddf25e5845f6e0acfa2f *R/data_world.R
+a48310b1e0ab29b8d167c09cd2c0f3e6 *R/find_countrycol.R
+63f5b06dd9bfd99b659dc9ed76f5cbfb *R/find_keycol.R
+341fdd3989356adaafec9f49047ba9a4 *R/find_timecol.R
+b2350fbae252c2e2b469fefe2a211e0a *R/has.invalid.multibyte.string.R
+71e679eb2e99de151bcc99379a221851 *R/is.yearcol.R
+e9377c4e7fec1342928925b45985c09d *R/is_country.R
+7462073eb90f69ca8c86a8574c3a58b6 *R/is_date.R
+9b1fa35aec228a0511cd32ddf57674c0 *R/is_keycol.R
+ef073b1907f50c76632b62e95c098bf3 *R/list_fields.R
+b7c879f029d3c13a69879f5b16aa3626 *R/map_palettes_and_themes.R
+903deb275bbbe443a65c0f6db06b8904 *R/match_table.R
+2f85ce9471994478ff99642ee385f953 *R/mode.R
+99f98f0605b128410f1bb9139b9d018e *R/parse.by.order.R
+5a37546d74ead984da1179870df4876c *R/quick_map.R
+97cb01db7d9786585a3ae48dbcebed68 *R/sysdata.rda
+8aa6f00a0f289c0cb7a690d701708e6f *R/which_min-max-mode.R
+a7bdc2e35aef141bb473fb4719f4fe6f *README.md
+e2f048aeb1ff5b9f5ad7f33c914ad454 *build/vignette.rds
+1e375b313bfda9eb653a05ffd9924cda *data/country_reference_list.rda
+0cf365f67f04b8a449ae14008f43f268 *data/country_reference_list_long.rda
+1f0663373d69793da7b98914a2a9ed16 *data/world.rda
+71b16632b064c42439c8c869a1f639e3 *inst/doc/auto_merge.R
+c5cfe6ac0e8888634d23da4f1dfec0be *inst/doc/auto_merge.Rmd
+1048f4c99ba33ecd0f55bdac05ff0a9f *inst/doc/auto_merge.html
+dc91c637da076712507555f7d80a32c3 *inst/doc/data_structure.R
+d876d0ec1d539156ca867838b51583ed *inst/doc/data_structure.Rmd
+6247c039b19eb7f8dd1ae76f35599d38 *inst/doc/data_structure.html
+ee51f9ba307b28bb2acaf315a81a06cb *inst/doc/dealing_with_names.R
+0088a25ad588b8d95628009bd1e63555 *inst/doc/dealing_with_names.Rmd
+820e1a3ba367d48dad727f95169b0afe *inst/doc/dealing_with_names.html
+7356195d829dfe56994b6b58b3e46d92 *inst/doc/quick_map.R
+19e68c3cc34e35e63a7d46c4ff215d6e *inst/doc/quick_map.Rmd
+e1e8493cee4063f1868b6e726c35f05f *inst/doc/quick_map.html
+0c1d510e5c29173f65fd62d049283568 *man/Mode.Rd
+a733f14d4c729e69d74ce50312799e02 *man/auto_melt.Rd
+b35bafe1f838b98969a0be6c59e3541e *man/auto_merge.Rd
+260f8778a234d1cac6e8299e242da865 *man/check_wide_format.Rd
+6b71ecb50bc5d274c7b337626450b041 *man/country_info.Rd
+898bd98ac226fb73346b92e4f06ad9ef *man/country_name.Rd
+5e57f2c0290c218a1240048c240aacdd *man/country_reference_list.Rd
+f02da7d9aea610e9ccda0635a01966fb *man/country_reference_list_long.Rd
+424a813073100dd310c469f68479c26b *man/figures/hexagon_sticker.png
+b5f9fc0a848db6df188fdc5105b17da4 *man/figures/hexagon_sticker_medium.png
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+45b6157deed9af890cc51e0ab543d912 *man/figures/logo.ico
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+56b0845cc9b76c81dbf0a11a3ba815d5 *man/find_countrycol.Rd
+5f3b9a15883654298e1cbba40836379a *man/find_keycol.Rd
+5db241def4048d2c74a1efc01b659a62 *man/find_timecol.Rd
+0c794ac131b6be7559b8b61a1591e1af *man/is_country.Rd
+3ecf8ab63ced7b4571ca8f1783767860 *man/is_date.Rd
+ced0bb9411b00bc0afce4b890f4d770b *man/is_keycol.Rd
+6ff85ebe41a3f090d64a7558a8436b2d *man/list_fields.Rd
+1a055bcc57e9650f6c69039c43e6ba04 *man/match_table.Rd
+f2a1108aba0a4c616b2d8e6ec166afa3 *man/palettes_countries.Rd
+e8da43942f05cb2a582d09439cf0f3ee *man/quick_map.Rd
+6c86f0a89214839bb4b6939a84f00eb6 *man/which_min.Rd
+8d0533094c347962433a572f9c95d329 *man/world.Rd
+5250cf6b34d84721cdb2683b313e85ad *tests/testthat.R
+2d3a8fcf9094d36f345bdc195a5007f1 *tests/testthat/test_function_output.R
+c5cfe6ac0e8888634d23da4f1dfec0be *vignettes/auto_merge.Rmd
+d876d0ec1d539156ca867838b51583ed *vignettes/data_structure.Rmd
+0088a25ad588b8d95628009bd1e63555 *vignettes/dealing_with_names.Rmd
+19e68c3cc34e35e63a7d46c4ff215d6e *vignettes/quick_map.Rmd

NAMESPACE

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+# Generated by roxygen2: do not edit by hand
+
+export(Mode)
+export(auto_melt)
+export(auto_merge)
+export(check_wide_format)
+export(country_info)
+export(country_name)
+export(find_countrycol)
+export(find_keycol)
+export(find_timecol)
+export(is_country)
+export(is_date)
+export(is_keycol)
+export(list_fields)
+export(match_table)
+export(palettes_countries)
+export(quick_map)
+export(which_max)
+export(which_min)
+export(which_mode)
+import(ggplot2)
+importFrom(fastmatch,"%fin%")
+importFrom(stats,na.omit)
+importFrom(stats,quantile)

NEWS.md

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+# countries 1.0.3
+* Fixed hyperlinks in for resubmission
+* Eliminated references to unexported objects in documentation
+
+# countries 1.0
+* First CRAN submission
+
+# countries 0.3
+
+* Added function *country_info()* to download information about countries (e.g. capital city, currency, neighbouring countries, etc.)
+* Added function *list_fields()* returning a list of accepted fields for *country_info()*
+* Added function *auto_merge()* to quickly join multiple dataset and automatically deal with country names and time columns
+* Added function *auto_melt()* to automatically pivot tables containing country names and years in their headers
+* Added function *quick_map()* to easily plot coloured country maps
+* Added function *palettes_countries()* providing access to the package's colour themes
+* Added vignette on plotting chloropleth maps with *quick_map* and merging country data with *auto_merge()* 
+* Bug fixes
+
+# countries 0.2
+
+* Added function *is_country()* to test whether a string is a country name or related to list of countries names
+* Added function *is_date()* to test whether values are dates
+* Added function *is_keycol()* to test whether a set of columns could be the keys of a table
+* Added function *find_countrycol()* to automate search of columns containing country names in data frames
+* Added function *find_timecol()* to automate search of date and/or year columns in data frames
+* Added function *find_keycol()* to automate search of table keys in data frames
+* Added functions *which_min()*, *which_max()* and *which_mode()* returning all the positions of vector's minimum, maximum and mode values.
+* Speed improvements for the functions *country_name()* and *match_table()*
+* Bug fixes
+* Added vignette on data structure
+
+
+
+# countries 0.1
+
+* Function *country_name()* for converting and translating country names based on a fuzzy matching approach
+* Function *match_table()* to easily construct conversion tables with the help of fuzzy matching algorithm
+* Function *Mode()* returns the statistical mode of a vectors (most frequent observation)
+* Dataset *country_reference_list* containing a country names in different languages and naming conventions
+* Added vignettes and documentation
+* Created website for the package

R/auto_melt.R

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+#' @title Automatic pivoting of country and year columns to a long format
+#'
+#' @description
+#' When at least 3 country names or years are found in the column names, the function will automatically transform the table from a wide to a long format by pivoting the country/year columns.
+#' This is equivalent to applying \code{tidyr::pivot_longer()} or \code{data.table::melt()} on the columns with years or countries as names.
+#' The function is able to detect years also when they are preceded by a prefix.
+#'
+#' @param x A data.frame object to check and pivot country or year columns.
+#' @param names_to String indicating how the column holding the name of the pivoted columns should be called in the output table. Default is \code{"pivoted_colnames"}
+#' @param values_to String indicating how the column containing the values of the pivoted columns should be called in the output table. Default is \code{"pivoted_data"}
+#' @param verbose Logical value. If set to \code{TRUE} (the default), a message will be displayed on the console indicating which columns are being pivoted. If set to \code{FALSE}, the messages are turned off.
+#' @param pivoting_info Logical value indicating whether to return the list of names of the column that have been pivoted. Default is \code{FALSE}. If set to \code{TRUE}, the output will be a list instead of simple data.frame. Teh list will contain 1) the pivoted table, 2) the list of pivoted columns.
+#' @returns A table transformed into a "long" format by pivoting country or year columns. If year columns are found, a numeric column called \code{"year_pivoted_colnames"} is added isolating the years extracted from the table header's.
+#' @seealso \link[countries]{auto_merge}, \link[countries]{find_countrycol},\link[countries]{find_timecol}
+#' @export
+#' @examples
+#' # example data
+#' example <- data.frame(Date = c("01.01.2019", "01.02.2019", "01.03.2019"),
+#'                       Japan = 1:3,
+#'                       Norway = 2:4,
+#'                       Germany = 3:5,
+#'                       US = 4:6)
+#' example2 <- data.frame(Sector = c("Agriculture", "Mining", "Forestry"),
+#'                        X2000 = 1:3,
+#'                        X2001 = 2:4,
+#'                        X2002 = 3:5,
+#'                        X2003 = 4:6)
+#'
+#' # examples pivotting countries and years from column names
+#' auto_melt(example)
+#' auto_melt(example2)
+auto_melt <- function(
+    x,
+    names_to = "pivoted_colnames",
+    values_to = "pivoted_data",
+    verbose = TRUE,
+    pivoting_info = FALSE
+){
+
+  # check inputs
+  if(!is.data.frame(as.data.frame(x))|is.null(x)){stop("Argument - x - needs to be a dataframe")}
+  if (is.na(names_to)|is.null(names_to)) stop("The argument - names_to - cannot be NA or NULL. It needs to be a string.")
+  if (is.na(values_to)|is.null(values_to)) stop("The argument - values_to - cannot be NA or NULL. It needs to be a logical value")
+  if (is.na(verbose)|is.null(verbose)) stop("The argument - verbose - cannot be NA or NULL. It needs to be a logical value")
+  if (is.na(pivoting_info)|is.null(pivoting_info)) stop("The argument - pivoting_info - cannot be NA or NULL. It needs to be a string.")
+  if (!is.character(names_to)|length(names_to)!=1)stop("The argument - names_to - is invalid. It needs to be a string.")
+  if (!is.character(values_to)|length(values_to)!=1)stop("The argument - values_to - is invalid. It needs to be a string.")
+  if (!is.logical(verbose) | length(verbose)!=1) stop("Function argument - verbose - needs to be a logical statement (TRUE/FALSE)")
+  if (!is.logical(pivoting_info) | length(pivoting_info)!=1) stop("Function argument - pivoting_info - needs to be a logical statement (TRUE/FALSE)")
+
+  # convert input to data.frame
+  data <- as.data.frame(x)
+
+  #check column names for countries/years
+  temp <- check_wide_format(data)
+
+  # proceed if there is any column to pivot
+  if (!is.null(temp)){
+
+    # pivot table if countries or years were found and adjust name
+    data <- as.data.frame(tidyr::pivot_longer(data, dplyr::all_of(temp$col_name), names_to = names_to, values_to = values_to))
+
+    # move pivoted keys to front of table
+    data <- data[, c(names_to, colnames(data)[colnames(data) != names_to])]
+
+    # convert year to numeric if possible, otherwise add numeric column with detected year in string
+    if (colnames(temp)[1] == "year"){
+      if (all(grepl('^(?=.)([+-]?([0-9]*)(\\.([0-9]+))?)$', temp$col_name, perl = TRUE))){
+        data[, names_to] <- as.numeric(data[, names_to])
+      } else {
+        data[,"year_pivoted_colnames"] <- temp[fastmatch::fmatch(data[, names_to], temp$col_name), 1]
+      }
+    }
+
+    # save name of pivoted columns
+    pivoted_cols <- as.vector(temp$col_name)
+
+    # issue message to console
+    if (verbose) cat(paste0(colnames(temp)[1], " detected in column names, pivoting columns: ", paste(temp$col_name[1:3], collapse=", ", sep = ""), if (nrow(temp)>3){paste0(", ..., ", temp$col_name[nrow(temp)])}, "\n"))
+  } else {
+
+    pivoted_cols <- NULL
+
+    if (verbose) cat("No column was pivoted\n")
+  }
+
+  # final output
+  if (pivoting_info){
+    return(list(output = data,
+           pivoted_cols = pivoted_cols))
+  } else {
+    return(data)
+  }
+
+}