v1.5.0

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: cleaner
 Title: Fast and Easy Data Cleaning
-Version: 1.4.0.9000
-Date: 2020-05-28
+Version: 1.5.0
+Date: 2020-06-01
 Authors@R: 
   person(
     given = c("Matthijs", "S."),

NEWS.md

@@ -1,4 +1,4 @@
-# cleaner 1.4.0.9000
+# cleaner 1.5.0
 
 * New function `format_names()` to quickly and easily change names of `data.frame` columns, `list`s or `character` vectors.
   ```r
@@ -26,6 +26,7 @@
   starwars %>% 
     na_replace() # replace NAs in all columns ("" for hair_color and 0 for birth_year)
   ```
+* Support for the upcoming R 4.1.0
 
 # cleaner 1.4.0
 

R/na_replace.R

@@ -138,7 +138,7 @@ na_replace.data.frame <- function(x, ..., replacement = NULL) {
       if (vctr_colname %in% colnames(attrbt$groups)) {
         attrbt$groups[which(is.na(attrbt$groups[, vctr_colname, drop = TRUE])), vctr_colname] <- replace_val
         # groups are always ordered on alphabet, so order it again with the new replacement value
-        attrbt$groups <- attrbt$groups[order(attrbt$groups[, vctr_colname]),]
+        attrbt$groups <- attrbt$groups[order(attrbt$groups[, vctr_colname]), ]
       }
     }
   }

README.md

@@ -228,6 +228,49 @@ Use `clean()` to clean data. It guesses what kind of data class would best fit y
   #> 2       31.40
   ```
 
+#### Other cleaning
+
+* Use `format_names()` to quickly and easily change names of `data.frame` columns, `list`s or `character` vectors.
+  ```r
+  format_names(df, snake_case = TRUE)
+  format_names(df, c(old.name = "new_name", value = "measurement"))
+
+  library(dplyr)
+  starwars %>% 
+    format_names(camelCase = TRUE) %>% # changes column names
+    mutate(name = name %>% 
+             format_names(snake_case = TRUE)) # changes values in column
+  ```
+
+* Use the generic function `na_replace()` to replace `NA` values in any data type. Its default replacement value is dependent on the data type that is given as input: `0` for numeric values and class `matrix`, `FALSE` for class `logical`, today for class `Date`, and `""` otherwise.
+
+  ```r
+  na_replace(c(1, 2, NA, NA))
+  #> [1] 1 2 0 0
+  na_replace(c(1, 2, NA, NA), replacement = -1)
+  #> [1]  1  2 -1 -1
+  na_replace(c(1, 2, NA, NA), replacement = c(0, -1))
+  #> [1]  1  2  0 -1
+
+  na_replace(c("a", "b", NA, NA))
+  #> [1] "a" "b" ""  ""
+  ```
+
+  It also supports replacing `NA`s in complete data sets and supports grouped variables used by the `dplyr` package:
+
+  ```r
+  library(dplyr)
+  starwars %>% 
+    na_replace(hair_color) # only replace NAs in this column
+
+  starwars %>% 
+    na_replace() # replace NAs in all columns ("" for hair_color and 0 for birth_year)
+
+  starwars %>%
+    group_by(hair_color) %>%
+    na_replace(hair_color, replacement = "TEST!") %>%
+    summarise(n = n())
+  ```
 
 ### Checking