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(v1.6.0.9021) join functions update

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dr. M.S. (Matthijs) Berends
2021-05-12 18:15:03 +02:00
parent 3319fbae58
commit 29dbfa2f49
119 changed files with 973 additions and 1040 deletions
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8
R/pca.R
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@ -27,12 +27,12 @@
#'
#' Performs a principal component analysis (PCA) based on a data set with automatic determination for afterwards plotting the groups and labels, and automatic filtering on only suitable (i.e. non-empty and numeric) variables.
#' @inheritSection lifecycle Stable Lifecycle
#' @param x a [data.frame] containing numeric columns
#' @param x a [data.frame] containing [numeric] columns
#' @param ... columns of `x` to be selected for PCA, can be unquoted since it supports quasiquotation.
#' @inheritParams stats::prcomp
#' @details The [pca()] function takes a [data.frame] as input and performs the actual PCA with the \R function [prcomp()].
#'
#' The result of the [pca()] function is a [prcomp] object, with an additional attribute `non_numeric_cols` which is a vector with the column names of all columns that do not contain numeric values. These are probably the groups and labels, and will be used by [ggplot_pca()].
#' The result of the [pca()] function is a [prcomp] object, with an additional attribute `non_numeric_cols` which is a vector with the column names of all columns that do not contain [numeric] values. These are probably the groups and labels, and will be used by [ggplot_pca()].
#' @return An object of classes [pca] and [prcomp]
#' @importFrom stats prcomp
#' @export
@ -99,14 +99,14 @@ pca <- function(x,
x <- as.data.frame(new_list, stringsAsFactors = FALSE)
if (any(vapply(FUN.VALUE = logical(1), x, function(y) !is.numeric(y)))) {
warning_("Be sure to first calculate the resistance (or susceptibility) of variables with antimicrobial test results, since PCA works with numeric variables only. See Examples in ?pca.", call = FALSE)
warning_("Be sure to first calculate the resistance (or susceptibility) of variables with antimicrobial test results, since PCA works with [numeric] variables only. See Examples in ?pca.", call = FALSE)
}
# set column names
tryCatch(colnames(x) <- as.character(dots)[2:length(dots)],
error = function(e) warning("column names could not be set"))
# keep only numeric columns
# keep only [numeric] columns
x <- x[, vapply(FUN.VALUE = logical(1), x, function(y) is.numeric(y))]
# bind the data set with the non-numeric columns
x <- cbind(x.bak[, vapply(FUN.VALUE = logical(1), x.bak, function(y) !is.numeric(y) & !all(is.na(y))), drop = FALSE], x)