R 분할표

1 개요[ | ]

R 분할표

2 빈도를 세야 하는 경우[ | ]

성별×선호색상

R

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cases <- read.table( header=TRUE, stringsAsFactors=FALSE, text="
Sex Color
M   blue
F   brown
F   brown
F   brown
M   brown
")
table(cases)

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3 빈도가 계산된 경우[ | ]

3.1 xtabs()[ | ]

성별×선호색상

R

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counts <- read.table( header=TRUE, stringsAsFactors=FALSE, text="
Sex Color Freq
F   blue  0
M   blue  1
F   brown 3
M   brown 1
")
xtabs(Freq ~ Sex+Color, data=counts)

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성별×손쓰임

R

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counts <- read.table( header=TRUE, stringsAsFactors=FALSE, text="
Gender  Handedness  Freq
Male    Right       43
Male    Left        9
Female  Right       44
Female  Left        4
")
xtabs(Freq ~ Gender+Handedness, data=counts)

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성별×지지정당

R

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counts <- read.table( header=TRUE, stringsAsFactors=FALSE, text="
gender  party        freq
M       Democrat     484
M       Independent  239
M       Republican   477
F       Democrat     762
F       Independent  327
F       Republican   468
")
xtabs(freq ~ gender+party, data=counts)

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3.2 as.table()[ | ]

성별×손쓰임

R

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t <- as.table(rbind(c(43, 9), c(44, 4)))
dimnames(t) <- list(Gender = c("Male", "Female"), Handedness = c("Right","Left"))
t

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성별×지지정당

R

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t <- as.table(rbind(c(762, 327, 468), c(484, 239, 477)))
dimnames(t) <- list(gender = c("F", "M"), party = c("Democrat","Independent", "Republican"))
t

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4 같이 보기[ | ]