Añadiendo la opción de excluir del agrupamiento.

R/ggheatmap.R

@@ -5,10 +5,10 @@ ggheatmap<-function(df, x=NULL, y=NULL, value=NULL, grouping="mean", exclude_gro
 
   df<-rename(df, "VarX"=all_of(x), "VarY"=all_of(y), "Value"=all_of(value))
   
-  if (!is.null(exclude_group)){
+  if (is.null(exclude_group)){
     df<-df %>% group_by(VarX,VarY)
   }else{
-    df<-df %>% group_by(VarX,VarY,all_of(exclude_group))
+    df<-df %>% group_by_("VarX","VarY",exclude_group) #%>% rename(exclude_group="all_of(exclude_group)")
   }
   if (grouping == "mean"){
     df<-df %>% summarise(Value=mean(Value)) %>% ungroup
@@ -16,8 +16,7 @@ ggheatmap<-function(df, x=NULL, y=NULL, value=NULL, grouping="mean", exclude_gro
   if (grouping == "median"){
     df<-df %>% summarise(Value=median(Value)) %>% ungroup
   }
-
-  order<-clustsort(df %>% spread(VarY,Value) %>% as.data.frame)
+  order<-clustsort(df %>% spread(VarY,Value) %>% select(!all_of(exclude_group)) %>% as.data.frame)
 
   df$VarX<-factor(df$VarX, levels=order$x)
   df$VarY<-factor(df$VarY, levels=order$y)

man/ggheatmap.Rd

@@ -2,7 +2,7 @@
 \alias{ggheatmap}
 \title{ggheatmap}
 \usage{
-ggheatmap(df, x=NULL, y=NULL, value=NULL, grouping="mean")
+ggheatmap(df, x=NULL, y=NULL, value=NULL, grouping="mean", exclude_group=NULL)
 }
 \arguments{
   \item{df}{A data frame in "long" format.}
@@ -10,6 +10,7 @@ ggheatmap(df, x=NULL, y=NULL, value=NULL, grouping="mean")
   \item{y}{The variable that will be used for Y axis in the heatmap. If not specified, the second column will be used.}
   \item{value}{The variable that will be used for colouring the heatmap. If not specified, the third column will be used.}
   \item{grouping}{The function that will be used to group if there is more than one observation for each X-Y combination. "mean" or "median" are posible, defaulting to "mean".}
+  \item{exclude_group}{If you want to exclude columns from grouping, you can introduce a character vector here. Useful if you want to facet the plot.}
 }
 \description{
 Generates a heatmap using ggplot for a dataframe.