General
PromptBeginner5 minmarkdownQuality: 24
# scaffold_analysis(myproject
outcome = score
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General
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n_dup
n_dup / n_row * 100))
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General
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cat(sprintf( %-25s %5d (%.1f%%)\n
lbl
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General
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cat(sprintf( ... and %d more levels\n
n_lv - top_n_levels))
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General
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pct <- round(cnt / n_row * 100
1)
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General
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show <- min(top_n_levels
n_lv)
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General
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tbl <- sort(table(x
useNA = no)
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General
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cat(sprintf(\n %s (%d unique values)\n
col
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General
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──────
───
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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
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min(x)
mean(x)
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General
PromptBeginner5 minmarkdownQuality: 24
col
bar
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General
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Column
Min
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General
PromptBeginner5 minmarkdownQuality: 24
num_cols <- names(df)[sapply(df
is.numeric)]
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General
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bar <- paste0(rep(█
bar_len)
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General
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pct_na <- round(cols_with_na[col] / n_row * 100
1)
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General
PromptBeginner5 minmarkdownQuality: 24
cat(sprintf( Columns with NAs: %d of %d\n\n
length(cols_with_na)
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General
PromptBeginner5 minmarkdownQuality: 24
na_flag <- if (n_na == 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
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col
cls
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Data
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check_data <- function(df
top_n_levels = 8) {
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General
PromptBeginner5 minmarkdownQuality: 24
pct <- round(n_na / n_row * 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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