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updated prepare_boxly to display outlier using type=2 #47

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wangben718 merged 2 commits into from
Jan 9, 2026
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updated prepare_boxly to display outlier using type=2 #47

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updated prepare_boxly to display outlier using type=2
jeetendersinghc Dec 12, 2025
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jeetendersinghc Dec 12, 2025
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34 changes: 21 additions & 13 deletions R/prepare_boxly.R
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Original file line number Diff line number Diff line change
Expand Up @@ -150,13 +150,18 @@ prepare_boxly <- function(meta,
# Calculate summary statistics and add these variables into tbl
plotds <- mapply(
function(s, u) {
t <- as.vector(summary(s[[y]]))
vals <- stats::quantile(s[[y]],
probs = c(0, 0.25, 0.5, 0.75, 1),
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@wangben718 wangben718 Dec 16, 2025

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Hi @jeetendersinghc , it looks great. Could you also add one more argument for user to define the type and set default as 2?

type = 2, na.rm = TRUE, names = FALSE
)

if (nrow(s) > 5) {
iqr.range <- t[5] - t[2]
upper_outliers <- t[5] + iqr.range * 1.5
lower_outliers <- t[2] - iqr.range * 1.5
s$outlier <- ifelse((s[[y]] > upper_outliers | s[[y]] < lower_outliers), s[[y]], NA)
iqr.range <- vals[4] - vals[2] # Q3 - Q1 (type=2)
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@wangben718 wangben718 Dec 16, 2025

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Is there any difference to calculate outlier between different type?

upper_outliers <- vals[4] + iqr.range * 1.5 # Q3 + 1.5*IQR
lower_outliers <- vals[2] - iqr.range * 1.5 # Q1 - 1.5*IQR
s$outlier <- ifelse((s[[y]] > upper_outliers | s[[y]] < lower_outliers),
s[[y]], NA
)
} else if (nrow(s) > 0) {
s$outlier <- NA
} else {
Expand All @@ -168,18 +173,21 @@ prepare_boxly <- function(meta,
# mutate ans for output
if (nrow(s) > 0) {
ans <- s
ans$min <- t[1]
ans$q1 <- t[2]
ans$median <- t[3]
ans$mean <- t[4]
ans$q3 <- t[5]
ans$max <- t[6]
# ensure vals and mean_val exist (vals from quantile(..., type=2) earlier)
mean_val <- mean(s[[y]], na.rm = TRUE)

ans$min <- vals[1]
ans$q1 <- vals[2]
ans$median <- vals[3]
ans$mean <- mean_val
ans$q3 <- vals[4]
ans$max <- vals[5]

ans
}
},
split(tbl, tbl[, c(obs_var, obs_group, x)]),
names(split(tbl, tbl[, c(obs_var, obs_group, x)], sep = ", ")),
split(tbl, list(tbl[[obs_var]], tbl[[obs_group]], tbl[[x]])),
names(split(tbl, list(tbl[[obs_var]], tbl[[obs_group]], tbl[[x]]), sep = ", ")),
SIMPLIFY = FALSE
)

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