General
PromptBeginner5 minmarkdown
# df <- df[complete.cases(df)
] # drop rows with any NA
0
Explore
Find agent skills by outcome
111,173 skills indexed with the new KISS metadata standard.
Showing 24 of 111,173Categories: Coding & Debugging, Data, Cursor-rules, Openclaw, General
General
PromptBeginner5 minmarkdown
hist(df$%s
main = Distribution of %s
0
General
PromptBeginner5 minmarkdown
cat(Dimensions:
dim(df)
0
General
PromptBeginner5 minmarkdown
df <- read.csv(%s
stringsAsFactors = FALSE)
0
General
PromptBeginner5 minmarkdown
out_file <- paste0(project_name
_analysis.R)
0
Data
PromptBeginner5 minmarkdown
if (is.null(data_file)) data_file <- paste0(project_name
.csv)
0
General
PromptBeginner5 minmarkdown
# scaffold_analysis(myproject
outcome = score
0
General
PromptBeginner5 minmarkdown
dims = c(rows = n_row
cols = n_col)
0
General
PromptBeginner5 minmarkdown
n_dup
n_dup / n_row * 100))
0
General
PromptBeginner5 minmarkdown
cat(sprintf( %-25s %5d (%.1f%%)\n
lbl
0
General
PromptBeginner5 minmarkdown
cat(sprintf( ... and %d more levels\n
n_lv - top_n_levels))
0
General
PromptBeginner5 minmarkdown
pct <- round(cnt / n_row * 100
1)
0
General
PromptBeginner5 minmarkdown
cat(sprintf(\n %s (%d unique values)\n
col
0
General
PromptBeginner5 minmarkdown
show <- min(top_n_levels
n_lv)
0
General
PromptBeginner5 minmarkdown
tbl <- sort(table(x
useNA = no)
0
General
PromptBeginner5 minmarkdown
cat_cols <- names(df)[sapply(df
function(x) is.factor(x) | is.character(x))]
0
General
PromptBeginner5 minmarkdown
min(x)
mean(x)
0
General
PromptBeginner5 minmarkdown
──────
───
0
General
PromptBeginner5 minmarkdown
num_cols <- names(df)[sapply(df
is.numeric)]
0
General
PromptBeginner5 minmarkdown
Column
Min
0
General
PromptBeginner5 minmarkdown
col
bar
0
General
PromptBeginner5 minmarkdown
pct_na <- round(cols_with_na[col] / n_row * 100
1)
0
General
PromptBeginner5 minmarkdown
cat(sprintf( Columns with NAs: %d of %d\n\n
length(cols_with_na)
0
General
PromptBeginner5 minmarkdown
bar <- paste0(rep(█
bar_len)
0