Remove more references to tabyl functions

.gitignore

@@ -10,3 +10,4 @@ docs
 Meta
 docs/
 janitor.Rproj
+inst/doc

NEWS.md

@@ -1,5 +1,7 @@
 # janitor 2.2.0.9000 - unreleased development version
 
+* All `tabyl` and related functions were moved to the new `tabyl` package.
+
 ## Breaking changes
 
 These are all minor breaking changes resulting from enhancements and are not expected to affect the vast majority of users.
@@ -293,7 +295,7 @@ No further changes are planned to `clean_names()` and its results should be stab
 
 ## Major features
 
-- `clean_names()` transliterates accented letters, e.g., `çãüœ` becomes `cauoe` [(#120)](https://github.com/sfirke/janitor/issues/120).  Thanks to **@fernandovmacedo**.
+- `clean_names()` transliterates accented letters, e.g., `C'C#C<E` becomes `cauoe` [(#120)](https://github.com/sfirke/janitor/issues/120).  Thanks to **@fernandovmacedo**.
 
 - `clean_names()` offers multiple options for variable name styling.  In addition to `snake_case` output you can select `smallCamelCase`, `BigCamelCase`, `ALL_CAPS` and others. [(#131)](https://github.com/sfirke/janitor/issues/131).
   - Thanks to **@tazinho**, who wrote the [snakecase](https://github.com/Tazinho/snakecase/) package that janitor depends on to do this, as well as the patch to incorporate it into `clean_names()`.  And thanks to **@maelle** for proposing this feature.

R/utils-pipe.R

@@ -12,7 +12,4 @@
 #' @param rhs A function call using the magrittr semantics.
 #' @return The result of calling `rhs(lhs)`.
 #' @examples
-#' mtcars %>%
-#'   tabyl(carb, cyl) %>%
-#'   adorn_totals()
 NULL

README.md

@@ -210,104 +210,6 @@ roster %>% get_dupes(contains("name"))
 Yes, some teachers appear twice. We ought to address this before
 counting employees.
 
-#### Tabulating tools
-
-A variable (or combinations of two or three variables) can be tabulated
-with `tabyl()`. The resulting data.frame can be tweaked and formatted
-with the suite of `adorn_` functions for quick analysis and printing of
-pretty results in a report. `adorn_` functions can be helpful with
-non-tabyls, too.
-
-#### `tabyl()`
-
-Like `table()`, but pipe-able, data.frame-based, and fully featured.
-
-`tabyl()` can be called two ways:
-
-- On a vector, when tabulating a single variable:
-  `tabyl(roster$subject)`
-- On a data.frame, specifying 1, 2, or 3 variable names to tabulate:
-  `roster %>% tabyl(subject, employee_status)`.
-  - Here the data.frame is passed in with the `%>%` pipe; this allows
-    `tabyl` to be used in an analysis pipeline
-
-One variable:
-
-``` r
-roster %>%
-  tabyl(subject)
-#>     subject n    percent valid_percent
-#>  Basketball 1 0.08333333           0.1
-#>   Chemistry 1 0.08333333           0.1
-#>        Dean 1 0.08333333           0.1
-#>    Drafting 1 0.08333333           0.1
-#>     English 2 0.16666667           0.2
-#>       Music 1 0.08333333           0.1
-#>          PE 1 0.08333333           0.1
-#>     Physics 1 0.08333333           0.1
-#>     Science 1 0.08333333           0.1
-#>        <NA> 2 0.16666667            NA
-```
-
-Two variables:
-
-``` r
-roster %>%
-  filter(hire_date > as.Date("1950-01-01")) %>%
-  tabyl(employee_status, full_time)
-#>  employee_status No Yes
-#>   Administration  0   1
-#>            Coach  2   0
-#>          Teacher  3   4
-```
-
-Three variables:
-
-``` r
-roster %>%
-  tabyl(full_time, subject, employee_status, show_missing_levels = FALSE)
-#> $Administration
-#>  full_time Dean
-#>        Yes    1
-#> 
-#> $Coach
-#>  full_time Basketball NA_
-#>         No          1   1
-#> 
-#> $Teacher
-#>  full_time Chemistry Drafting English Music PE Physics Science NA_
-#>         No         0        0       2     0  0       0       1   0
-#>        Yes         1        1       0     1  1       1       0   1
-```
-
-#### Adorning tabyls
-
-The `adorn_` functions dress up the results of these tabulation calls
-for fast, basic reporting. Here are some of the functions that augment a
-summary table for reporting:
-
-``` r
-roster %>%
-  tabyl(employee_status, full_time) %>%
-  adorn_totals("row") %>%
-  adorn_percentages("row") %>%
-  adorn_pct_formatting() %>%
-  adorn_ns() %>%
-  adorn_title("combined")
-#>  employee_status/full_time         No        Yes
-#>             Administration   0.0% (0) 100.0% (1)
-#>                      Coach 100.0% (2)   0.0% (0)
-#>                    Teacher  33.3% (3)  66.7% (6)
-#>                      Total  41.7% (5)  58.3% (7)
-```
-
-Pipe that right into `knitr::kable()` in your RMarkdown report.
-
-These modular adornments can be layered to reduce R’s deficit against
-Excel and SPSS when it comes to quick, informative counts. Learn more
-about `tabyl()` and the `adorn_` functions from the [tabyls
-vignette](https://sfirke.github.io/janitor/articles/tabyls.html).
-
 ## <i class="fa fa-bullhorn" aria-hidden="true"></i> Contact me
 
 You are welcome to:

_pkgdown.yml

@@ -5,21 +5,11 @@ template:
 
 reference:
 - title: Cleaning data
- 
+
 - subtitle: Cleaning variable names
   contents:
   - contains("clean_names")
-
-- title: Exploring data
-  desc: >
-    tabyls are an enhanced version of tables. See `vignette("tabyls")`
-    for more details.
-  contents:
-  - tabyl
-  - starts_with("adorn")
-  - contains("tabyl")
-  - -contains('.test')
-
+
 - subtitle: Change order
   contents:
   - row_to_names
@@ -38,9 +28,9 @@ reference:
   - get_one_to_one
   - top_levels
   - single_value
-    
+
 - title: Rounding / dates helpers
-  desc: > 
+  desc: >
     Help to mimic some behaviour from Excel or SAS.
     These should be used on vector.
   contents:

vignettes/.gitignore

@@ -0,0 +1,2 @@
+*.html
+*.R

vignettes/janitor.Rmd

@@ -79,23 +79,6 @@ compare_df_cols_same(df1, df3)
 compare_df_cols_same(df2, df3)
 ```
 
-## Exploring
-
-### `tabyl()` - a better version of `table()`
-`tabyl()` is a tidyverse-oriented replacement for `table()`.  It counts combinations of one, two, or three variables, and then can be formatted with a suite of `adorn_*` functions to look just how you want.  For instance:
-
-```{r}
-mtcars %>%
-  tabyl(gear, cyl) %>%
-  adorn_totals("col") %>%
-  adorn_percentages("row") %>%
-  adorn_pct_formatting(digits = 2) %>%
-  adorn_ns() %>%
-  adorn_title()
-```
-
-Learn more in the [tabyls vignette](https://sfirke.github.io/janitor/articles/tabyls.html).
-
 ### Explore records with duplicated values for specific combinations of variables with `get_dupes()`
 This is for hunting down and examining duplicate records during data cleaning - usually when there shouldn't be any.
 
@@ -230,23 +213,3 @@ row_to_names(dirt, 2)
 The function `find_header()` is a companion function to `row_to_names()`.  By default it will search a data.frame for the first row with no missing values and return that row number.
 
 It can also be used to return the row number where a given string is present in the first column, or in any specific column.  Then this result can be supplied to `row_to_names()`.
-
-
-## Exploring
-
-### Count factor levels in groups of high, medium, and low with `top_levels()`
-
-Originally designed for use with Likert survey data stored as factors.  Returns a `tbl_df` frequency table with appropriately-named rows, grouped into head/middle/tail groups.
-
-+ Takes a user-specified size for the head/tail groups
-+ Automatically calculates a percent column
-+ Supports sorting
-+ Can show or hide `NA` values.
-
-```{r}
-f <- factor(c("strongly agree", "agree", "neutral", "neutral", "disagree", "strongly agree"),
-  levels = c("strongly agree", "agree", "neutral", "disagree", "strongly disagree")
-)
-top_levels(f)
-top_levels(f, n = 1)
-```