General
PromptBeginner5 minmarkdownQuality: 24
col = red
lwd = 2)
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General
PromptBeginner5 minmarkdownQuality: 24
cormat <- cor(df[numcols]
use = complete.obs)
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General
PromptBeginner5 minmarkdownQuality: 24
plot(df$predictor
df$outcome_var
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General
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col = adjustcolor(steelblue
alpha.f = 0.5)
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General
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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 = 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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