General
PromptBeginner5 minmarkdown
barplot(table(df$category)
main = Counts
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General
PromptBeginner5 minmarkdown
pch = 19
col = steelblue
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General
PromptBeginner5 minmarkdown
plot(x
y
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General
PromptBeginner5 minmarkdown
con <- file(big.csv
r)
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General
PromptBeginner5 minmarkdown
chunk <- readLines(con
n = 100)
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General
PromptBeginner5 minmarkdown
save(df1
df2
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Data
PromptBeginner5 minmarkdown
saveRDS(obj
data.rds)
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General
PromptBeginner5 minmarkdown
# RDS (single R object
preserves types)
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Data
PromptBeginner5 minmarkdown
df <- read.table(data.txt
header = TRUE
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General
PromptBeginner5 minmarkdown
strsplit(a
b
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Data
PromptBeginner5 minmarkdown
df <- read.csv(data.csv
stringsAsFactors = FALSE)
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General
PromptBeginner5 minmarkdown
gsub(old
new
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General
PromptBeginner5 minmarkdown
grepl(pattern
x) # logical vector
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General
PromptBeginner5 minmarkdown
grep(pattern
x) # indices of matches
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General
PromptBeginner5 minmarkdown
paste0(x
1:3) # x1 x2 x3
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General
PromptBeginner5 minmarkdown
substr(hello
1
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General
PromptBeginner5 minmarkdown
sprintf(%.2f%%
3.14159) # 3.14%
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Data
PromptBeginner5 minmarkdown
aggregate(value ~ group
data = df
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General
PromptBeginner5 minmarkdown
mapply(function(x
y) x + y
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General
PromptBeginner5 minmarkdown
paste(a
b
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General
PromptBeginner5 minmarkdown
apply(m
2
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General
PromptBeginner5 minmarkdown
tapply(df$value
df$group
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General
PromptBeginner5 minmarkdown
# apply — over matrix margins (1=rows
2=cols)
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General
PromptBeginner5 minmarkdown
lapply(lst
function(x) x[1])
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