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.data pronoun only allows one facet variable. I have changed into !!!syms().

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Marcel Costa
2025-03-06 13:12:00 +01:00
parent d42e4ff6f3
commit ab96f5ec6a
1 changed files with 3 additions and 3 deletions
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R/ggstats_add_xy.R
+3 -3
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@@ -10,11 +10,11 @@ ggstats_add_xy<-function(table_stat, table, xcol=NULL, group, y="max", bracket.o
if (is.null(exclude_group)){ if (is.null(exclude_group)){
table_agg<-table %>% group_by(.data[[x]]) table_agg<-table %>% group_by(.data[[x]])
}else{ }else{
table_agg<-table %>% group_by(.data[[x]], .data[[exclude_group]]) table_agg<-table %>% group_by(.data[[x]], !!!syms(exclude_group))
} }
if (y == "max"){ if (y == "max"){
agg<-table_agg %>% summarise(max=max(.data[[value.var]], na.rm = T)) agg<-table_agg %>% summarise(max=max(.data[[value.var]], na.rm = T))
if(!is.null(exclude_group)){agg<-table_agg %>% group_by(.data[[exclude_group]]) %>% summarise(max=max(.data[[value.var]], na.rm=T))} if(!is.null(exclude_group)){agg<-table_agg %>% group_by(!!!syms(exclude_group)) %>% summarise(max=max(.data[[value.var]], na.rm=T))}
}else if (y == "mean"){ }else if (y == "mean"){
agg<-table %>% group_by(.data[[x]],.data[[group]]) %>% summarise(mean=mean(.data[[value.var]], na.rm=T)) %>% spread(group, mean) agg<-table %>% group_by(.data[[x]],.data[[group]]) %>% summarise(mean=mean(.data[[value.var]], na.rm=T)) %>% spread(group, mean)
agg<- data.frame(x=agg[,1], "max"=apply(agg[,2:ncol(agg)], 1, max, na.rm=T)) agg<- data.frame(x=agg[,1], "max"=apply(agg[,2:ncol(agg)], 1, max, na.rm=T))
@@ -55,7 +55,7 @@ ggstats_add_xy<-function(table_stat, table, xcol=NULL, group, y="max", bracket.o
if (!is.null(exclude_group)){ if (!is.null(exclude_group)){
for (j in unique(pull(table_stat, all_of(exclude_group)))){ for (j in unique(pull(table_stat, all_of(exclude_group)))){
for (dia in unique(pull(table_stat,all_of(xcol)))){ for (dia in unique(pull(table_stat,all_of(xcol)))){
if (table_stat %>% filter(p < 0.05) %>% filter(.data[[x]] == dia & .data[[exclude_group]] == j) %>% nrow() > 0){ if (table_stat %>% filter(p < 0.05) %>% filter(.data[[x]] == dia & !!!syms(exclude_group) == j) %>% nrow() > 0){
t[table_stat[,x] == dia & table_stat[,exclude_group] == j,"y.position"]<-seq(t[table_stat[,x] == dia & table_stat[,exclude_group] == j,"y.position"][[1,1]], t[table_stat[,x] == dia & table_stat[,exclude_group] == j,"y.position"]<-seq(t[table_stat[,x] == dia & table_stat[,exclude_group] == j,"y.position"][[1,1]],
t[table_stat[,x] == dia & table_stat[,exclude_group] == j,"y.position"][[1,1]]+diff(range(table[,value.var], na.rm = T))*bracket.inspace*(nrow(table_stat[table_stat[,x] == dia & table_stat[,exclude_group] == j,])-1), t[table_stat[,x] == dia & table_stat[,exclude_group] == j,"y.position"][[1,1]]+diff(range(table[,value.var], na.rm = T))*bracket.inspace*(nrow(table_stat[table_stat[,x] == dia & table_stat[,exclude_group] == j,])-1),
by=diff(range(table[,value.var], na.rm = T))*bracket.inspace) by=diff(range(table[,value.var], na.rm = T))*bracket.inspace)