From f1699bfa5dd9d4d85ecac9477ad874301c293cb5 Mon Sep 17 00:00:00 2001
From: Joseph Larmarange <joseph@larmarange.net>
Date: Fri, 5 Jun 2020 18:26:35 +0200
Subject: [PATCH] weighted_mean_sd and weighted_median_iqr instead of mean_sd
 and median_iqr

fix #370
---
 NAMESPACE                  |  4 ++--
 R/gg-plots.R               | 12 ++++++------
 man/ggally_summarise_by.Rd | 16 ++++++++--------
 3 files changed, 16 insertions(+), 16 deletions(-)

diff --git a/NAMESPACE b/NAMESPACE
index c3fc1f922..75977a035 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -98,8 +98,6 @@ export(mapping_string)
 export(mapping_swap_x_y)
 export(max1)
 export(mean0)
-export(mean_sd)
-export(median_iqr)
 export(min0)
 export(model_beta_label)
 export(model_beta_variables)
@@ -118,6 +116,8 @@ export(stat_prop)
 export(stat_weighted_mean)
 export(uppertriangle)
 export(v1_ggmatrix_theme)
+export(weighted_mean_sd)
+export(weighted_median_iqr)
 export(wrap)
 export(wrap_fn_with_param_arg)
 export(wrap_fn_with_params)
diff --git a/R/gg-plots.R b/R/gg-plots.R
index 2bd9b2bb7..2e6018ce9 100644
--- a/R/gg-plots.R
+++ b/R/gg-plots.R
@@ -1718,7 +1718,7 @@ ggally_autopointDiag <- function(data, mapping, ...) {
 #' ggally_summarise_by(tips, mapping = aes(x = total_bill, y = day), size = 6)
 #'
 #' # change statistic to display
-#' ggally_summarise_by(tips, mapping = aes(x = total_bill, y = day), text_fn = mean_sd)
+#' ggally_summarise_by(tips, mapping = aes(x = total_bill, y = day), text_fn = weighted_mean_sd)
 #'
 #' # custom stat function
 #' weighted_sum <- function(x, weights = NULL) {
@@ -1729,7 +1729,7 @@ ggally_autopointDiag <- function(data, mapping, ...) {
 ggally_summarise_by <- function(
   data,
   mapping,
-  text_fn = median_iqr,
+  text_fn = weighted_median_iqr,
   text_fn_vertical = NULL,
   ...)
 {
@@ -1794,9 +1794,9 @@ ggally_summarise_by <- function(
 #' @param x a numeric vector
 #' @param weights an optional numeric vectors of weights. If \code{NULL}, equal weights of 1 will be taken into account.
 #' @details
-#' \code{median_iqr} computes median and interquartile range.
+#' \code{weighted_median_iqr} computes weighted median and interquartile range.
 #' @export
-median_iqr <- function(x, weights = NULL) {
+weighted_median_iqr <- function(x, weights = NULL) {
   require_namespaces("Hmisc")
   s <- round(Hmisc::wtd.quantile(x, weights = weights, probs = c(.25, .5, .75), na.rm = TRUE), digits = 1)
   paste0("Median: ", s[2], " [", s[1], "-", s[3], "]")
@@ -1804,9 +1804,9 @@ median_iqr <- function(x, weights = NULL) {
 
 #' @rdname ggally_summarise_by
 #' @details
-#' \code{mean_sd} computes mean and standard deviation.
+#' \code{weighted_mean_sd} computes weighted mean and standard deviation.
 #' @export
-mean_sd <- function(x, weights = NULL) {
+weighted_mean_sd <- function(x, weights = NULL) {
   require_namespaces("Hmisc")
   m <- round(Hmisc::wtd.mean(x, weights = weights, na.rm = TRUE), digits = 1)
   sd <- round(sqrt(Hmisc::wtd.var(x, weights = weights, na.rm = TRUE)), digits = 1)
diff --git a/man/ggally_summarise_by.Rd b/man/ggally_summarise_by.Rd
index e483dde69..3fbb3bec7 100644
--- a/man/ggally_summarise_by.Rd
+++ b/man/ggally_summarise_by.Rd
@@ -2,21 +2,21 @@
 % Please edit documentation in R/gg-plots.R
 \name{ggally_summarise_by}
 \alias{ggally_summarise_by}
-\alias{median_iqr}
-\alias{mean_sd}
+\alias{weighted_median_iqr}
+\alias{weighted_mean_sd}
 \title{Summarize a continuous variable by each value of a discrete variable}
 \usage{
 ggally_summarise_by(
   data,
   mapping,
-  text_fn = median_iqr,
+  text_fn = weighted_median_iqr,
   text_fn_vertical = NULL,
   ...
 )
 
-median_iqr(x, weights = NULL)
+weighted_median_iqr(x, weights = NULL)
 
-mean_sd(x, weights = NULL)
+weighted_mean_sd(x, weights = NULL)
 }
 \arguments{
 \item{data}{data set using}
@@ -37,9 +37,9 @@ mean_sd(x, weights = NULL)
 Display summary statistics of a continuous variable for each value of a discrete variable.
 }
 \details{
-\code{median_iqr} computes median and interquartile range.
+\code{weighted_median_iqr} computes weighted median and interquartile range.
 
-\code{mean_sd} computes mean and standard deviation.
+\code{weighted_mean_sd} computes weighted mean and standard deviation.
 }
 \examples{
 data(tips, package = "reshape")
@@ -55,7 +55,7 @@ ggally_summarise_by(tips, mapping = aes(x = day, y = total_bill, color = day))
 ggally_summarise_by(tips, mapping = aes(x = total_bill, y = day), size = 6)
 
 # change statistic to display
-ggally_summarise_by(tips, mapping = aes(x = total_bill, y = day), text_fn = mean_sd)
+ggally_summarise_by(tips, mapping = aes(x = total_bill, y = day), text_fn = weighted_mean_sd)
 
 # custom stat function
 weighted_sum <- function(x, weights = NULL) {