From 09497551313cfedac1c55ad64e41588c460aae10 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E2=80=98topepo=E2=80=99?= <‘mxkuhn@gmail.com’> Date: Wed, 3 Jul 2024 07:50:18 -0400 Subject: [PATCH] "Please provide package anchors for all Rd \link{} targets not in the package itself and the base packages." --- R/recipe.R | 2 +- man/bake.Rd | 2 +- man/juice.Rd | 2 +- man/recipe.Rd | 4 ++-- man/selections.Rd | 18 +++++++++--------- man/step_bs.Rd | 2 +- 6 files changed, 15 insertions(+), 15 deletions(-) diff --git a/R/recipe.R b/R/recipe.R index 3cc32930b..27602c98c 100644 --- a/R/recipe.R +++ b/R/recipe.R @@ -596,7 +596,7 @@ bake <- function(object, ...) { #' @param ... One or more selector functions to choose which variables will be #' returned by the function. See [selections()] for more details. #' If no selectors are given, the default is to use -#' [everything()]. +#' [dplyr::everything()]. #' @param composition Either "tibble", "matrix", "data.frame", or #' "dgCMatrix" for the format of the processed data set. Note that #' all computations during the baking process are done in a diff --git a/man/bake.Rd b/man/bake.Rd index 119ce5cad..996c24c63 100644 --- a/man/bake.Rd +++ b/man/bake.Rd @@ -16,7 +16,7 @@ one preprocessing operation.} \item{...}{One or more selector functions to choose which variables will be returned by the function. See \code{\link[=selections]{selections()}} for more details. If no selectors are given, the default is to use -\code{\link[=everything]{everything()}}.} +\code{\link[dplyr:reexports]{dplyr::everything()}}.} \item{new_data}{A data frame or tibble for whom the preprocessing will be applied. If \code{NULL} is given to \code{new_data}, the pre-processed \emph{training diff --git a/man/juice.Rd b/man/juice.Rd index 4a17124b1..dcf796b52 100644 --- a/man/juice.Rd +++ b/man/juice.Rd @@ -13,7 +13,7 @@ juice(object, ..., composition = "tibble") \item{...}{One or more selector functions to choose which variables will be returned by the function. See \code{\link[=selections]{selections()}} for more details. If no selectors are given, the default is to use -\code{\link[=everything]{everything()}}.} +\code{\link[dplyr:reexports]{dplyr::everything()}}.} \item{composition}{Either "tibble", "matrix", "data.frame", or "dgCMatrix" for the format of the processed data set. Note that diff --git a/man/recipe.Rd b/man/recipe.Rd index f6ca83b32..0d569cd01 100644 --- a/man/recipe.Rd +++ b/man/recipe.Rd @@ -80,8 +80,8 @@ added to a recipe. \itemize{ \item \strong{Steps} can include operations like scaling a variable, creating dummy variables or interactions, and so on. More computationally -complex actions such as dimension reduction or imputation can also -be specified. +complex actions such as dimension reduction or imputation can also be +specified. \item \strong{Checks} are operations that conduct specific tests of the data. When the test is satisfied, the data are returned without issue or modification. Otherwise, an error is thrown. diff --git a/man/selections.Rd b/man/selections.Rd index 7620151f1..3c14d0e9b 100644 --- a/man/selections.Rd +++ b/man/selections.Rd @@ -116,20 +116,20 @@ will not work. When creating variable selections: \itemize{ -\item If you are using column filtering steps, such as \code{step_corr()}, try -to avoid hardcoding specific variable names in downstream steps in -case those columns are removed by the filter. Instead, use +\item If you are using column filtering steps, such as \code{step_corr()}, try to +avoid hardcoding specific variable names in downstream steps in case +those columns are removed by the filter. Instead, use \code{\link[dplyr:reexports]{dplyr::any_of()}} and \code{\link[dplyr:reexports]{dplyr::all_of()}}. \itemize{ -\item \code{\link[dplyr:reexports]{dplyr::any_of()}} will be tolerant if a -column has been removed. +\item \code{\link[dplyr:reexports]{dplyr::any_of()}} will be tolerant if a column +has been removed. \item \code{\link[dplyr:reexports]{dplyr::all_of()}} will fail unless all of the columns are present in the data. } -\item For both of these functions, if you are going to save the recipe as -a binary object to use in another R session, try to avoid referring -to a vector in your workspace. +\item For both of these functions, if you are going to save the recipe as a +binary object to use in another R session, try to avoid referring to a +vector in your workspace. \itemize{ \item Preferred: \code{any_of(!!var_names)} \item Avoid: \code{any_of(var_names)} @@ -160,7 +160,7 @@ recipe(mpg ~ ., data = mtcars) \%>\% }\if{html}{\out{}} \if{html}{\out{
}}\preformatted{## Error in `step_log()`: -## Caused by error in `prep()` at recipes/R/recipe.R:478:9: +## Caused by error in `prep()` at recipes/R/recipe.R:479:9: ## ! Can't select columns that don't exist. ## x Column `wt` doesn't exist. }\if{html}{\out{
}} diff --git a/man/step_bs.Rd b/man/step_bs.Rd index 7cfbe353c..ffbe6d3d5 100644 --- a/man/step_bs.Rd +++ b/man/step_bs.Rd @@ -69,7 +69,7 @@ columns that are basis expansions of variables using B-splines. \code{step_bs} can create new features from a single variable that enable fitting routines to model this variable in a nonlinear manner. The extent of the possible nonlinearity is -determined by the \code{df}, \code{degree}, or \code{knot} arguments of +determined by the \code{df}, \code{degree}, or \code{knots} arguments of \code{\link[splines:bs]{splines::bs()}}. The original variables are removed from the data and new columns are added. The naming convention for the new variables is \code{varname_bs_1} and so on.