v1.5.4

.Rbuildignore

@@ -8,3 +8,4 @@
 ^cran-comments\.md$
 ^lintr\.R$
 ^.github$
+^CRAN-SUBMISSION$

CRAN-SUBMISSION

@@ -0,0 +1,3 @@
+Version: 1.5.4
+Date: 2022-10-28 13:00:25 UTC
+SHA: 8b6f7806f6cad942907166ec76ea256667f1e23f

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: cleaner
 Title: Fast and Easy Data Cleaning
-Version: 1.5.3.9003
-Date: 2022-10-24
+Version: 1.5.4
+Date: 2022-10-28
 Authors@R: 
   person(
     given = c("Matthijs", "S."),
@@ -27,7 +27,7 @@ Suggests:
   ggplot2,
   rmarkdown,
   testthat (>= 1.0.2)
-URL: https://github.com/msberends/cleaner
+URL: https://msberends.github.io/cleaner/, https://github.com/msberends/cleaner
 BugReports: https://github.com/msberends/cleaner/issues
 License: GPL-2
 Encoding: UTF-8

NEWS.md

@@ -1,7 +1,10 @@
-# cleaner 1.5.3.9xxx
+# cleaner 1.5.4
 
-* Fix for `digits` in `format()`
 * For `clean_Date()` and `clean_POSIXct()`: allow argument `max_date` to be the same length as `x`
+* Fix for `digits` in `format()`
+* Fix for currency symbols
+* Fix CRAN check error
+
 
 # cleaner 1.5.3
 
@@ -23,6 +26,7 @@
 * `freq()` now contains a `wt` argument to set the weights. The default (`NULL`) yields the old behaviour.
 * Fixed a bug in `clean_POSIXct()` that led to the warning `Incompatible methods ("Ops.POSIXt", "Ops.Date") for ">"`
 
+
 # cleaner 1.5.1
 
 * New function `format_p_value()` to format raw p values according to the APA guideline
@@ -34,6 +38,7 @@
 * Currency now prints and formats without symbols as default, use `as_symbol = TRUE` to print/format with currency symbols
 * Support for older versions of R (v3.2)
 
+
 # cleaner 1.5.0
 
 * New function `format_names()` to quickly and easily change names of `data.frame` columns, `list`s or `character` vectors.
@@ -66,6 +71,7 @@
   ```
 * Support for the upcoming R 4.1.0
 
+
 # cleaner 1.4.0
 
 * New function `rdate()` to generate random dates (in analogy to e.g. `runif()`)
@@ -100,18 +106,21 @@
   ```
 * Cleaned all code using the `lintr` package
 
+
 # cleaner 1.3.1
 
 * Fixed a bug when using a `percentage` class into the `percentage()` function, i.e. `percentage(as.percentage(1))` would fail
 * Fixed extremely small percentages, like `as.percentage(2.5e-14)`
 
+
 # cleaner 1.3.0
 
 * Added functions `clean_double()` and `clean_integer()`
 * Added a method for `median()` in percentages
 * Fixed a bug where `NA` in percentages would not be formatted correctly
 * Fixed a bug in frequency tables where sometimes the number of digits used for percentages would be astronomical
 
+
 # cleaner 1.2.0
 
 * **DUE TO CRAN POLICY: RENAMED TO PACKAGE TO `cleaner`**
@@ -121,6 +130,7 @@
 * Fix for `clean_character()` on R v3.5 and lower
 * Fix for digits in frequency tables for numeric values
 
+
 # clean 1.1.0
 
 * Added support for currency as a new class: `as.currency()` and `clean_currency()`. They also come with 'S3 methods' for `print`, `format`, `sum`, `min` and `max`.
@@ -132,6 +142,7 @@
 * `clean_numeric()` now supports currency
 * Fix for `freq()` where the precentage of NAs in the header was not calculated right
 
+
 # clean 1.0.0
 
 * First release

R/currency.R

@@ -96,21 +96,22 @@ c.currency <- function(x, ...) {
 }
 
 txt2symb <- function(txt) {
-  switch(txt,
-         "USD" = "\u0024",
-         "EUR" = "\u20ac",
-         "JPY" = "\u00a5",
-         "GBP" = "\u00a3",
-         txt)
-}
-
-symb2txt <- function(txt) {
-  switch(txt,
-         "\u0024" = "USD",
-         "\u20ac" = "EUR",
-         "\u00a5" = "JPY",
-         "\u00a3" = "GBP",
-         txt)
+  txt <- toupper(txt)
+  sym <- unname(pkg_env$symbols[which(names(pkg_env$symbols) == txt)])
+  if (length(sym) == 0) {
+    txt
+  } else {
+    sym
+  }
+}
+
+symb2txt <- function(sym) {
+  txt <- unname(names(pkg_env$symbols)[which(pkg_env$symbols == sym)])
+  if (length(txt) == 0) {
+    sym
+  } else {
+    txt
+  }
 }
 
 #' @rdname currency

R/zzz.R

@@ -17,6 +17,14 @@
 # useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY.              #
 # ==================================================================== #
 
+pkg_env <- new.env(hash = FALSE)
 .onLoad <- function(libname, pkgname) {
   backports::import(pkgname)
+  # read symbols from external file to prevent CRAN errors
+  symbols <- tryCatch(utils::read.delim(system.file("symbols.txt", package = "cleaner"), sep = ","), error = function(e) NULL)
+  if (!is.null(symbols)) {
+    pkg_env$symbols <- stats::setNames(symbols$symbol, symbols$txt)
+  } else {
+    pkg_env$symbols <- character(0)
+  }
 }

README.md

@@ -24,7 +24,7 @@ Contents:
 ----
 
 ## Why this package
-As a data scientist, I'm often served with data that is not clean, not tidy and consequently not ready for analysis at all. For tidying data, there's of course the `tidyverse` (https://www.tidyverse.org), which lets you manipulate data in any way you can think of. But for *cleaning*, I think our community was still lacking a neat solution that makes data cleaning fast and easy with functions that kind of 'think on their own' to do that.
+You are probably often served with data that is not clean, not tidy and consequently not ready for analysis at all. For tidying data, there's of course the `tidyverse` (https://www.tidyverse.org), which lets you manipulate data in any way you can think of. But for *cleaning*, our community might still have been lacking a neat solution that makes data cleaning fast and easy with functions that kind of 'think on their own' to do that.
 
 If the CRAN button at the top of this page is green, install the package with:
 

inst/symbols.txt

@@ -0,0 +1,7 @@
+txt,symbol
+"CNY","元"
+"EUR","€"
+"GBP","£"
+"JPY","¥"
+"KRW","₩"
+"USD","$"

tests/testthat/test-currency.R

@@ -21,4 +21,5 @@ context("currency.R")
 
 test_that("currency works", {
   expect_true(is.currency(clean_currency(c("no5538", "no929", "yes2390", "no841", "no2610"))))
+  expect_identical(symb2txt(txt2symb("EUR")), "EUR")
 })