General
PromptBeginner5 minmarkdownQuality: 24
scaffold_analysis(myproject
outcome = score
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General
PromptBeginner5 minmarkdownQuality: 24
n_dup
ndup / nrow * 100))
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General
PromptBeginner5 minmarkdownQuality: 24
cat(sprintf( %-25s %5d (%.1f%%)\n
lbl
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General
PromptBeginner5 minmarkdownQuality: 24
cat(sprintf( ... and %d more levels\n
nlv - topn_levels))
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General
PromptBeginner5 minmarkdownQuality: 24
pct <- round(cnt / n_row * 100
1)
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General
PromptBeginner5 minmarkdownQuality: 24
show <- min(topnlevels
n_lv)
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General
PromptBeginner5 minmarkdownQuality: 24
tbl <- sort(table(x
useNA = no)
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General
PromptBeginner5 minmarkdownQuality: 24
cat(sprintf(\n %s (%d unique values)\n
col
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General
PromptBeginner5 minmarkdownQuality: 24
──────
───
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General
PromptBeginner5 minmarkdownQuality: 24
cat_cols <- names(df)[sapply(df
function(x) is.factor(x) | is.character(x))]
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General
PromptBeginner5 minmarkdownQuality: 24
min(x)
mean(x)
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General
PromptBeginner5 minmarkdownQuality: 24
col
bar
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General
PromptBeginner5 minmarkdownQuality: 24
Column
Min
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General
PromptBeginner5 minmarkdownQuality: 24
num_cols <- names(df)[sapply(df
is.numeric)]
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General
PromptBeginner5 minmarkdownQuality: 24
bar <- paste0(rep(█
bar_len)
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General
PromptBeginner5 minmarkdownQuality: 24
pctna <- round(colswithna[col] / nrow * 100
1)
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General
PromptBeginner5 minmarkdownQuality: 24
cat(sprintf( Columns with NAs: %d of %d\n\n
length(colswithna)
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General
PromptBeginner5 minmarkdownQuality: 24
naflag <- if (nna == 0) " else sprintf( * %d NAs (%.1f%%)
n_na
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General
PromptBeginner5 minmarkdownQuality: 24
na_counts <- sapply(df
function(x) sum(is.na(x)))
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General
PromptBeginner5 minmarkdownQuality: 24
col
cls
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Data
PromptBeginner5 minmarkdownQuality: 24
check_data <- function(df
topnlevels = 8) {
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General
PromptBeginner5 minmarkdownQuality: 24
pct <- round(nna / nrow * 100
1)
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General
PromptBeginner5 minmarkdownQuality: 24
cat(sprintf( Rows: %d Columns: %d\n
n_row
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General
PromptBeginner5 minmarkdownQuality: 24
par(mfrow = c(1
1))
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