AgentSkillify

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Find agent skills by outcome

123,283 skills indexed with the new KISS metadata standard.

Showing 24 of 123,283Categories: Data & Insights, Creative, General
General
PromptBeginner5 minmarkdownQuality: 24

cor_mat <- cor(df[num_cols]

use = complete.obs)

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General
PromptBeginner5 minmarkdownQuality: 24

plot(df$predictor

df$outcome_var

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General
PromptBeginner5 minmarkdownQuality: 24

col = adjustcolor(steelblue

alpha.f = 0.5)

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General
PromptBeginner5 minmarkdownQuality: 24

par(mfrow = c(2

2))

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General
PromptBeginner5 minmarkdownQuality: 24

# prop.table(table(df$group

df$category)

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General
PromptBeginner5 minmarkdownQuality: 24

))

3)

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General
PromptBeginner5 minmarkdownQuality: 24

# table(df$group

df$category

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General
PromptBeginner5 minmarkdownQuality: 24

median = median(x

na.rm = TRUE)

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General
PromptBeginner5 minmarkdownQuality: 24

max = max(x

na.rm = TRUE)

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General
PromptBeginner5 minmarkdownQuality: 24

min = min(x

na.rm = TRUE)

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General
PromptBeginner5 minmarkdownQuality: 24

mean = mean(x

na.rm = TRUE)

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General
PromptBeginner5 minmarkdownQuality: 24

sd = sd(x

na.rm = TRUE)

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General
PromptBeginner5 minmarkdownQuality: 24

round(sapply(df[num_cols]

function(x) c(

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General
PromptBeginner5 minmarkdownQuality: 24

num_cols <- names(df)[sapply(df

is.numeric)]

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General
PromptBeginner5 minmarkdownQuality: 24

# df <- df[df$year >= 2010

]

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General
PromptBeginner5 minmarkdownQuality: 24

# df <- df[complete.cases(df[

c(outcome

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General
PromptBeginner5 minmarkdownQuality: 24

# breaks = c(0

25

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General
PromptBeginner5 minmarkdownQuality: 24

# labels = c(18-25

26-45

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General
PromptBeginner5 minmarkdownQuality: 24

# df$gender <- ifelse(df$gender == 1

Male

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General
PromptBeginner5 minmarkdownQuality: 24

# df$date <- as.Date(df$date

format = %Y-%m-%d)

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General
PromptBeginner5 minmarkdownQuality: 24

cat(sprintf(\n%s (%d unique):\n

col

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General
PromptBeginner5 minmarkdownQuality: 24

print(table(df[[col]]

useNA = ifany))

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General
PromptBeginner5 minmarkdownQuality: 24

cat(sprintf(Duplicate rows: %d\n

n_dup))

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General
PromptBeginner5 minmarkdownQuality: 24

cat_cols <- names(df)[sapply(df

function(x) is.character(x) | is.factor(x))]

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