Skip to content

updated prepare_boxly to display outlier using type=2 #47

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
jeetendersinghc wants to merge 2 commits into
base: main
Choose a base branch
from
Open

updated prepare_boxly to display outlier using type=2 #47

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
db8cc73
updated prepare_boxly to display outlier using type=2
jeetendersinghc Dec 12, 2025
e779248
Style code (GHA)
jeetendersinghc Dec 12, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
34 changes: 21 additions & 13 deletions R/prepare_boxly.R
View file
Open in desktop
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),
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$outlier <- ifelse((s[[y]] > upper_outliers | s[[y]] < lower_outliers), s[[y]], NA)
iqr.range <- vals[4] - vals[2] # Q3 - Q1 (type=2)
upper_outliers <- vals[4] + iqr.range * 1.5 # Q3 + 1.5*IQR
lower_outliers <- vals[2] - iqr.range * 1.5 # Q1 - 1.5*IQR
s$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
)

Expand Down