fill in package-level docs and put CRAN links in canonical form

R/cattonum.R

@@ -1,6 +1,8 @@
-#' cattonum: TODO
+#' cattonum: Encode Categorical Features
 #'
-#' TODO.
+#' Functions for dummy encoding, frequency encoding,
+#' label encoding, leave-one-out encoding, mean encoding,
+#' and one-hot encoding.
 #'
 #' @docType package
 #' @name cattonum

README.Rmd

@@ -32,12 +32,12 @@ knitr::opts_chunk$set(
 
 There are many existing packages with which to encode categorical features, including (among others):
 
-* [CatEncoders](https://cran.r-project.org/web/packages/CatEncoders/index.html)
-* [dummies](https://cran.r-project.org/web/packages/dummies/index.html)
-* [fastDummies](https://cran.r-project.org/web/packages/fastDummies/index.html)
-* [h2o](https://cran.r-project.org/web/packages/h2o/index.html)
-* [makedummies](https://cran.r-project.org/web/packages/makedummies/index.html)
-* [recipes](https://cran.r-project.org/web/packages/recipes/index.html)
+* [CatEncoders](https://cran.r-project.org/package=CatEncoders)
+* [dummies](https://cran.r-project.org/package=dummies)
+* [fastDummies](https://cran.r-project.org/package=fastDummies)
+* [h2o](https://cran.r-project.org/package=h2o)
+* [makedummies](https://cran.r-project.org/package=makedummies)
+* [recipes](https://cran.r-project.org/package=recipes)
 
 The goal of `catto_num` is to be a one-stop shop for all categorical encoding needs.  Nothing more, nothing less.
 

README.md

@@ -24,15 +24,14 @@ features as numerics. It includes the following:
   - one-hot encoding: `catto_onehot`
 
 There are many existing packages with which to encode categorical
-features, including (among
-    others):
-
-  - [CatEncoders](https://cran.r-project.org/web/packages/CatEncoders/index.html)
-  - [dummies](https://cran.r-project.org/web/packages/dummies/index.html)
-  - [fastDummies](https://cran.r-project.org/web/packages/fastDummies/index.html)
-  - [h2o](https://cran.r-project.org/web/packages/h2o/index.html)
-  - [makedummies](https://cran.r-project.org/web/packages/makedummies/index.html)
-  - [recipes](https://cran.r-project.org/web/packages/recipes/index.html)
+features, including (among others):
+
+  - [CatEncoders](https://cran.r-project.org/package=CatEncoders)
+  - [dummies](https://cran.r-project.org/package=dummies)
+  - [fastDummies](https://cran.r-project.org/package=fastDummies)
+  - [h2o](https://cran.r-project.org/package=h2o)
+  - [makedummies](https://cran.r-project.org/package=makedummies)
+  - [recipes](https://cran.r-project.org/package=recipes)
 
 The goal of `catto_num` is to be a one-stop shop for all categorical
 encoding needs. Nothing more, nothing less.

cran-comments.md

@@ -10,9 +10,10 @@ Categorical features often are a key part of many modern datasets in different i
 
 ## R CMD check results
 
-0 errors | 0 warnings | 0 notes
+0 errors | 1 warning | 1 note
 
 * This is a new release.
+* 'qpdf' is needed for checks on size reduction of PDFs.
 
 ## Reverse dependencies
 

vignettes/introduction.Rmd

@@ -16,7 +16,7 @@ knitr::opts_chunk$set(
 
 ## Background
 
-Categorical features often are a key part of many modern datasets in different industries.  When it comes to performing supervised learning on these datasets, tree-based models theoretically (and in practice with certain software, like [h2o](https://cran.r-project.org/web/packages/h2o/index.html)) handle raw categorical features, but most other models do not.  Many of the popular tree-based packages even require all numeric predictors.  There are several other packages that encode categorical features as numeric features, including [CatEncoders](https://cran.r-project.org/web/packages/CatEncoders/index.html), [dummies](https://cran.r-project.org/web/packages/dummies/index.html), [fastDummies](https://cran.r-project.org/web/packages/fastDummies/index.html), [h2o](https://cran.r-project.org/web/packages/h2o/index.html), [makedummies](https://cran.r-project.org/web/packages/makedummies/index.html), and [recipes](https://cran.r-project.org/web/packages/recipes/index.html).  These packages either provide a more limited selection of encoding options and/or are signifantly larger in scope and much more heavyweight.  `cattonum` aims to provide a one-stop-shop for categorical encodings.  Nothing more, nothing less.
+Categorical features often are a key part of many modern datasets in different industries.  When it comes to performing supervised learning on these datasets, tree-based models theoretically (and in practice with certain software, like [h2o](https://cran.r-project.org/package=h2o)) handle raw categorical features, but most other models do not.  Many of the popular tree-based packages even require all numeric predictors.  There are several other packages that encode categorical features as numeric features, including [CatEncoders](https://cran.r-project.org/package=CatEncoders), [dummies](https://cran.r-project.org/package=dummies), [fastDummies](https://cran.r-project.org/package=fastDummies), [h2o](https://cran.r-project.org/package=h2o), [makedummies](https://cran.r-project.org/package=makedummies), and [recipes](https://cran.r-project.org/package=recipes).  These packages either provide a more limited selection of encoding options and/or are signifantly larger in scope and much more heavyweight.  `cattonum` aims to provide a one-stop-shop for categorical encodings.  Nothing more, nothing less.
 
 ## Case study