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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General
PromptBeginner5 minmarkdownQuality: 24
cat_cols <- names(df)[sapply(df
function(x) is.character(x) | is.factor(x))]
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General
PromptBeginner5 minmarkdownQuality: 24
print(nareport[nareport$n_miss > 0
])
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General
PromptBeginner5 minmarkdownQuality: 24
head(df
10)
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General
PromptBeginner5 minmarkdownQuality: 24
pct_miss = round(colMeans(is.na(df)) * 100
1)
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General
PromptBeginner5 minmarkdownQuality: 24
library(lmtest) # Breusch-Pagan
Durbin-Watson etc.
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General
PromptBeginner5 minmarkdownQuality: 24
library(car) # Type II/III ANOVA
VIF
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General
PromptBeginner5 minmarkdownQuality: 24
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