updated code repo for CRAN

Author: mo2-amodu

R/forstringr-package.R

@@ -2,9 +2,7 @@
 "_PACKAGE"
 
 ## usethis namespace: start
-#' @importFrom dplyr %>%
-#' @importFrom dplyr across
-#' @importFrom dplyr mutate
+#' @importFrom dplyr %>% across mutate
 #' @importFrom stats na.omit
 #' @importFrom stringr str_to_title
 ## usethis namespace: end

R/ignore_unused_imports.R

@@ -10,7 +10,7 @@
 #' @inheritParams stringr::str_to_title
 #'
 #' @return
-#' A character vector the same length as the string and in the title case.
+#' A character vector the same length as the string and in title case.
 #'
 #' @export
 #'

R/str_title_case.R

@@ -79,7 +79,12 @@ library(forstringr)
 
 ethnicity <- c("Hausa", NA, "Yoruba", "Ijaw", "Igbo", NA, "Ibibio", "Tiv", "Fulani", "Kanuri", "Others")
 
-length(ethnicity) # Count all the observations, including the NAs.
+# count all the observations, including NAs.
+
+length(ethnicity) 
+
+
+# count all the observations, without NAs.
 
 length_omit_na(ethnicity)
 ```
@@ -171,13 +176,14 @@ It is important to note that `str_englue()` must be used inside a function. `str
 library(ggplot2)
 
 histogram_plot <- function(df, var, binwidth) {
- df |>
+ df %>%  
    ggplot(aes(x = {{ var }})) +
    geom_histogram(binwidth = binwidth) +
    labs(title = str_englue("A histogram of {{var}} with binwidth {binwidth}"))
 }
 
-iris |> histogram_plot(Sepal.Length, binwidth = 0.1)
+iris %>% 
+  histogram_plot(Sepal.Length, binwidth = 0.1)
 ```
 
 
@@ -186,12 +192,12 @@ iris |> histogram_plot(Sepal.Length, binwidth = 0.1)
 Extra spaces are accidentally entered when working with survey data, and problems can arise when evaluating such data because of extra spaces. Therefore, the function `str_rm_whitespace_df()` eliminates your data frame unnecessary leading, trailing, or other whitespaces.
 
 ```{r example 6a}
-# A dataframe with whitespaces
+# a dataframe with whitespaces
 
 richest_in_nigeria
 ```
 ```{r example6b}
-# A dataframe with no whitespaces
+# a dataframe with no whitespaces
 
 str_rm_whitespace_df(richest_in_nigeria)
 ```

README.Rmd

@@ -77,9 +77,14 @@ library(forstringr)
 
 ethnicity <- c("Hausa", NA, "Yoruba", "Ijaw", "Igbo", NA, "Ibibio", "Tiv", "Fulani", "Kanuri", "Others")
 
-length(ethnicity) # Count all the observations, including the NAs.
+# count all the observations, including NAs.
+
+length(ethnicity) 
 #> [1] 11
 
+
+# count all the observations, without NAs.
+
 length_omit_na(ethnicity)
 #> [1] 9
 ```
@@ -202,13 +207,14 @@ transforms it to a string using the default name operation.
 library(ggplot2)
 
 histogram_plot <- function(df, var, binwidth) {
- df |>
+ df %>%  
    ggplot(aes(x = {{ var }})) +
    geom_histogram(binwidth = binwidth) +
    labs(title = str_englue("A histogram of {{var}} with binwidth {binwidth}"))
 }
 
-iris |> histogram_plot(Sepal.Length, binwidth = 0.1)
+iris %>% 
+  histogram_plot(Sepal.Length, binwidth = 0.1)
 ```
 
 <img src="man/figures/README-example_6-1.png" width="100%" />
@@ -221,7 +227,7 @@ Therefore, the function `str_rm_whitespace_df()` eliminates your data
 frame unnecessary leading, trailing, or other whitespaces.
 
 ``` r
-# A dataframe with whitespaces
+# a dataframe with whitespaces
 
 richest_in_nigeria
 #> # A tibble: 10 × 5
@@ -240,7 +246,7 @@ richest_in_nigeria
 ```
 
 ``` r
-# A dataframe with no whitespaces
+# a dataframe with no whitespaces
 
 str_rm_whitespace_df(richest_in_nigeria)
 #> # A tibble: 10 × 5

README.md

@@ -4,3 +4,4 @@ test_that("str_split_extract() split up a string into pieces and extract the res
     c("Ibadan", "Ikeja", "Ilorin")
   )
 })
+