From 38a2d27a06e8b629e76b65c6163cd943f748d349 Mon Sep 17 00:00:00 2001
From: Daniel <mail@danielluedecke.de>
Date: Sun, 13 Aug 2023 19:46:36 +0200
Subject: [PATCH] docs

---
 R/row_means.R    | 11 ++++++-----
 man/row_means.Rd | 13 +++++++------
 2 files changed, 13 insertions(+), 11 deletions(-)

diff --git a/R/row_means.R b/R/row_means.R
index 6b3f57133..bd2845499 100644
--- a/R/row_means.R
+++ b/R/row_means.R
@@ -22,11 +22,12 @@
 #'
 #' @details Rounding to a negative number of `digits` means rounding to a power of
 #' ten, for example `row_means(df, 3, digits = -2)` rounds to the nearest hundred.
-#' For `n`, must be a numeric value from `0` to `ncol(data)`. If a row in the
-#' data frame has at least `n` non-missing values, the row mean is returned. If
-#' `n` is a non-integer value from 0 to 1, `n` is considered to indicate the
-#' proportion of required non-missing values per row. E.g., if `n = 0.75`, a
-#' row must have at least `ncol(data) * n` non-missing values for the row mean
+#' For `min_valid`, if not `NULL`, `min_valid` must be a numeric value from `0`
+#' to `ncol(data)`. If a row in the data frame has at least `min_valid`
+#' non-missing values, the row mean is returned. If `min_valid` is a non-integer
+#' value from 0 to 1, `min_valid` is considered to indicate the proportion of
+#' required non-missing values per row. E.g., if `min_valid = 0.75`, a row must
+#' have at least `ncol(data) * min_valid` non-missing values for the row mean
 #' to be calculated. See 'Examples'.
 #'
 #' @examples
diff --git a/man/row_means.Rd b/man/row_means.Rd
index 43aa64a60..9ebd05c12 100644
--- a/man/row_means.Rd
+++ b/man/row_means.Rd
@@ -47,11 +47,12 @@ valid (and not \code{NA}).
 \details{
 Rounding to a negative number of \code{digits} means rounding to a power of
 ten, for example \code{row_means(df, 3, digits = -2)} rounds to the nearest hundred.
-For \code{n}, must be a numeric value from \code{0} to \code{ncol(data)}. If a row in the
-data frame has at least \code{n} non-missing values, the row mean is returned. If
-\code{n} is a non-integer value from 0 to 1, \code{n} is considered to indicate the
-proportion of required non-missing values per row. E.g., if \code{n = 0.75}, a
-row must have at least \code{ncol(data) * n} non-missing values for the row mean
+For \code{min_valid}, if not \code{NULL}, \code{min_valid} must be a numeric value from \code{0}
+to \code{ncol(data)}. If a row in the data frame has at least \code{min_valid}
+non-missing values, the row mean is returned. If \code{min_valid} is a non-integer
+value from 0 to 1, \code{min_valid} is considered to indicate the proportion of
+required non-missing values per row. E.g., if \code{min_valid = 0.75}, a row must
+have at least \code{ncol(data) * min_valid} non-missing values for the row mean
 to be calculated. See 'Examples'.
 }
 \examples{
@@ -77,7 +78,7 @@ row_means(dat, min_valid = 3) # 2 valid return values
 # needs at least 2 non-missing values per row
 row_means(dat, min_valid = 2)
 
-# needs at least 1 non-missing value per row
+# needs at least 1 non-missing value per row, for two selected variables
 row_means(dat, select = c("c1", "c3"), min_valid = 1)
 
 # needs at least 50\% of non-missing values per row