Student 3000 Criminal Data
coop711
2015년 10월 7일
Structure of Data
Data Manipulation
- W. S. Gosset 이 t-분포를 유도하느라고 모의실험에 활용한 자료는 다음과 같음.
table은 본질적으로matrix임. 행과 열의 이름에 측정값을 글자로 새겨 넣었기 때문에 long format으로 변환할 때 많은 주의가 필요함.
# options(width=132)
crimtab## 142.24 144.78 147.32 149.86 152.4 154.94 157.48 160.02 162.56 165.1
## 9.4 0 0 0 0 0 0 0 0 0 0
## 9.5 0 0 0 0 0 1 0 0 0 0
## 9.6 0 0 0 0 0 0 0 0 0 0
## 9.7 0 0 0 0 0 0 0 0 0 0
## 9.8 0 0 0 0 0 0 1 0 0 0
## 9.9 0 0 1 0 1 0 1 0 0 0
## 10 1 0 0 1 2 0 2 0 0 1
## 10.1 0 0 0 1 3 1 0 1 1 0
## 10.2 0 0 2 2 2 1 0 2 0 1
## 10.3 0 1 1 3 2 2 3 5 0 0
## 10.4 0 0 1 1 2 3 3 4 3 3
## 10.5 0 0 0 1 3 7 6 4 3 1
## 10.6 0 0 0 1 4 5 9 14 6 3
## 10.7 0 0 1 2 4 9 14 16 15 7
## 10.8 0 0 0 2 5 6 14 27 10 7
## 10.9 0 0 0 0 2 6 14 24 27 14
## 11 0 0 0 2 6 12 15 31 37 27
## 11.1 0 0 0 3 3 12 22 26 24 26
## 11.2 0 0 0 3 2 7 21 30 38 29
## 11.3 0 0 0 1 0 5 10 24 26 39
## 11.4 0 0 0 0 3 4 9 29 56 58
## 11.5 0 0 0 0 0 5 11 17 33 57
## 11.6 0 0 0 0 2 1 4 13 37 39
## 11.7 0 0 0 0 0 2 9 17 30 37
## 11.8 0 0 0 0 1 0 2 11 15 35
## 11.9 0 0 0 0 1 1 2 12 10 27
## 12 0 0 0 0 0 0 1 4 8 19
## 12.1 0 0 0 0 0 0 0 2 4 13
## 12.2 0 0 0 0 0 0 1 2 5 6
## 12.3 0 0 0 0 0 0 0 0 4 8
## 12.4 0 0 0 0 0 0 1 1 1 2
## 12.5 0 0 0 0 0 0 0 1 0 1
## 12.6 0 0 0 0 0 0 0 0 0 1
## 12.7 0 0 0 0 0 0 0 0 0 1
## 12.8 0 0 0 0 0 0 0 0 0 0
## 12.9 0 0 0 0 0 0 0 0 0 0
## 13 0 0 0 0 0 0 0 0 0 0
## 13.1 0 0 0 0 0 0 0 0 0 0
## 13.2 0 0 0 0 0 0 0 0 0 0
## 13.3 0 0 0 0 0 0 0 0 0 0
## 13.4 0 0 0 0 0 0 0 0 0 0
## 13.5 0 0 0 0 0 0 0 0 0 0
## 167.64 170.18 172.72 175.26 177.8 180.34 182.88 185.42 187.96 190.5
## 9.4 0 0 0 0 0 0 0 0 0 0
## 9.5 0 0 0 0 0 0 0 0 0 0
## 9.6 0 0 0 0 0 0 0 0 0 0
## 9.7 0 0 0 0 0 0 0 0 0 0
## 9.8 0 0 0 0 0 0 0 0 0 0
## 9.9 0 0 0 0 0 0 0 0 0 0
## 10 0 0 0 0 0 0 0 0 0 0
## 10.1 0 0 0 0 0 0 0 0 0 0
## 10.2 0 0 0 0 0 0 0 0 0 0
## 10.3 0 0 0 0 0 0 0 0 0 0
## 10.4 0 0 0 0 0 0 0 0 0 0
## 10.5 3 1 0 1 0 0 0 0 0 0
## 10.6 1 0 0 1 0 0 0 0 0 0
## 10.7 3 1 2 0 0 0 0 0 0 0
## 10.8 1 2 1 0 0 0 0 0 0 0
## 10.9 10 4 1 0 0 0 0 0 0 0
## 11 17 10 6 0 0 0 0 0 0 0
## 11.1 24 7 4 1 0 0 0 0 0 0
## 11.2 27 20 4 1 0 0 0 0 0 0
## 11.3 26 24 7 2 0 0 0 0 0 0
## 11.4 26 22 10 11 0 0 0 0 0 0
## 11.5 38 34 25 11 2 0 0 0 0 0
## 11.6 48 38 27 12 2 2 0 1 0 0
## 11.7 48 45 24 9 9 2 0 0 0 0
## 11.8 41 34 29 10 5 1 0 0 0 0
## 11.9 32 35 19 10 9 3 1 0 0 0
## 12 42 39 22 16 8 2 2 0 0 0
## 12.1 22 28 15 27 10 4 1 0 0 0
## 12.2 23 17 16 11 8 1 1 0 0 0
## 12.3 10 13 20 23 6 5 0 0 0 0
## 12.4 7 12 4 7 7 1 0 0 1 0
## 12.5 3 12 11 8 6 8 0 2 0 0
## 12.6 0 3 5 7 8 6 3 1 1 0
## 12.7 1 7 5 5 8 2 2 0 0 0
## 12.8 1 2 3 1 8 5 3 1 1 0
## 12.9 0 1 2 2 0 1 1 0 0 0
## 13 3 0 1 0 1 0 2 1 0 0
## 13.1 0 1 1 0 0 0 0 0 0 0
## 13.2 1 1 0 1 0 3 0 0 0 0
## 13.3 0 0 0 0 0 0 1 0 1 0
## 13.4 0 0 0 0 0 0 0 0 0 0
## 13.5 0 0 0 0 0 0 0 1 0 0
## 193.04 195.58
## 9.4 0 0
## 9.5 0 0
## 9.6 0 0
## 9.7 0 0
## 9.8 0 0
## 9.9 0 0
## 10 0 0
## 10.1 0 0
## 10.2 0 0
## 10.3 0 0
## 10.4 0 0
## 10.5 0 0
## 10.6 0 0
## 10.7 0 0
## 10.8 0 0
## 10.9 0 0
## 11 0 0
## 11.1 0 0
## 11.2 0 1
## 11.3 0 0
## 11.4 0 0
## 11.5 0 0
## 11.6 0 0
## 11.7 0 0
## 11.8 0 0
## 11.9 0 0
## 12 0 0
## 12.1 0 0
## 12.2 0 0
## 12.3 0 0
## 12.4 0 0
## 12.5 0 0
## 12.6 0 0
## 12.7 0 0
## 12.8 0 0
## 12.9 0 0
## 13 0 0
## 13.1 0 0
## 13.2 0 0
## 13.3 0 0
## 13.4 0 0
## 13.5 0 0str(crimtab)## 'table' int [1:42, 1:22] 0 0 0 0 0 0 1 0 0 0 ...
## - attr(*, "dimnames")=List of 2
## ..$ : chr [1:42] "9.4" "9.5" "9.6" "9.7" ...
## ..$ : chr [1:22] "142.24" "144.78" "147.32" "149.86" ...- 이러한 table 구조의 행과 열에 이름을 붙이려면,
list로 부여- cm 단위로 되어 있는 키의 계급을 인치 단위로 변환하면 숨어있던 자료구조다 드러남.
dimnames(crimtab)## [[1]]
## [1] "9.4" "9.5" "9.6" "9.7" "9.8" "9.9" "10" "10.1" "10.2" "10.3"
## [11] "10.4" "10.5" "10.6" "10.7" "10.8" "10.9" "11" "11.1" "11.2" "11.3"
## [21] "11.4" "11.5" "11.6" "11.7" "11.8" "11.9" "12" "12.1" "12.2" "12.3"
## [31] "12.4" "12.5" "12.6" "12.7" "12.8" "12.9" "13" "13.1" "13.2" "13.3"
## [41] "13.4" "13.5"
##
## [[2]]
## [1] "142.24" "144.78" "147.32" "149.86" "152.4" "154.94" "157.48"
## [8] "160.02" "162.56" "165.1" "167.64" "170.18" "172.72" "175.26"
## [15] "177.8" "180.34" "182.88" "185.42" "187.96" "190.5" "193.04"
## [22] "195.58"crimtab.2 <- crimtab
colnames(crimtab.2) <- as.numeric(colnames(crimtab.2))/2.54
(dimnames(crimtab.2) <- list(finger = rownames(crimtab.2), height = colnames(crimtab.2)))## $finger
## [1] "9.4" "9.5" "9.6" "9.7" "9.8" "9.9" "10" "10.1" "10.2" "10.3"
## [11] "10.4" "10.5" "10.6" "10.7" "10.8" "10.9" "11" "11.1" "11.2" "11.3"
## [21] "11.4" "11.5" "11.6" "11.7" "11.8" "11.9" "12" "12.1" "12.2" "12.3"
## [31] "12.4" "12.5" "12.6" "12.7" "12.8" "12.9" "13" "13.1" "13.2" "13.3"
## [41] "13.4" "13.5"
##
## $height
## [1] "56" "57" "58" "59" "60" "61" "62" "63" "64" "65" "66" "67" "68" "69"
## [15] "70" "71" "72" "73" "74" "75" "76" "77"crimtab.2## height
## finger 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77
## 9.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 9.5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 9.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 9.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 9.8 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 9.9 0 0 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 10 1 0 0 1 2 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
## 10.1 0 0 0 1 3 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 10.2 0 0 2 2 2 1 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0
## 10.3 0 1 1 3 2 2 3 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 10.4 0 0 1 1 2 3 3 4 3 3 0 0 0 0 0 0 0 0 0 0 0 0
## 10.5 0 0 0 1 3 7 6 4 3 1 3 1 0 1 0 0 0 0 0 0 0 0
## 10.6 0 0 0 1 4 5 9 14 6 3 1 0 0 1 0 0 0 0 0 0 0 0
## 10.7 0 0 1 2 4 9 14 16 15 7 3 1 2 0 0 0 0 0 0 0 0 0
## 10.8 0 0 0 2 5 6 14 27 10 7 1 2 1 0 0 0 0 0 0 0 0 0
## 10.9 0 0 0 0 2 6 14 24 27 14 10 4 1 0 0 0 0 0 0 0 0 0
## 11 0 0 0 2 6 12 15 31 37 27 17 10 6 0 0 0 0 0 0 0 0 0
## 11.1 0 0 0 3 3 12 22 26 24 26 24 7 4 1 0 0 0 0 0 0 0 0
## 11.2 0 0 0 3 2 7 21 30 38 29 27 20 4 1 0 0 0 0 0 0 0 1
## 11.3 0 0 0 1 0 5 10 24 26 39 26 24 7 2 0 0 0 0 0 0 0 0
## 11.4 0 0 0 0 3 4 9 29 56 58 26 22 10 11 0 0 0 0 0 0 0 0
## 11.5 0 0 0 0 0 5 11 17 33 57 38 34 25 11 2 0 0 0 0 0 0 0
## 11.6 0 0 0 0 2 1 4 13 37 39 48 38 27 12 2 2 0 1 0 0 0 0
## 11.7 0 0 0 0 0 2 9 17 30 37 48 45 24 9 9 2 0 0 0 0 0 0
## 11.8 0 0 0 0 1 0 2 11 15 35 41 34 29 10 5 1 0 0 0 0 0 0
## 11.9 0 0 0 0 1 1 2 12 10 27 32 35 19 10 9 3 1 0 0 0 0 0
## 12 0 0 0 0 0 0 1 4 8 19 42 39 22 16 8 2 2 0 0 0 0 0
## 12.1 0 0 0 0 0 0 0 2 4 13 22 28 15 27 10 4 1 0 0 0 0 0
## 12.2 0 0 0 0 0 0 1 2 5 6 23 17 16 11 8 1 1 0 0 0 0 0
## 12.3 0 0 0 0 0 0 0 0 4 8 10 13 20 23 6 5 0 0 0 0 0 0
## 12.4 0 0 0 0 0 0 1 1 1 2 7 12 4 7 7 1 0 0 1 0 0 0
## 12.5 0 0 0 0 0 0 0 1 0 1 3 12 11 8 6 8 0 2 0 0 0 0
## 12.6 0 0 0 0 0 0 0 0 0 1 0 3 5 7 8 6 3 1 1 0 0 0
## 12.7 0 0 0 0 0 0 0 0 0 1 1 7 5 5 8 2 2 0 0 0 0 0
## 12.8 0 0 0 0 0 0 0 0 0 0 1 2 3 1 8 5 3 1 1 0 0 0
## 12.9 0 0 0 0 0 0 0 0 0 0 0 1 2 2 0 1 1 0 0 0 0 0
## 13 0 0 0 0 0 0 0 0 0 0 3 0 1 0 1 0 2 1 0 0 0 0
## 13.1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0
## 13.2 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 3 0 0 0 0 0 0
## 13.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0
## 13.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 13.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0str(crimtab.2)## 'table' int [1:42, 1:22] 0 0 0 0 0 0 1 0 0 0 ...
## - attr(*, "dimnames")=List of 2
## ..$ finger: chr [1:42] "9.4" "9.5" "9.6" "9.7" ...
## ..$ height: chr [1:22] "56" "57" "58" "59" ...- long format 으로 변환
- 1차적으로 각 손가락 길이와 키의 조합을 갖는 인원수로 구성된 data frame으로 변환하고, case 단위의 long format data frame으로 2단계 변환
as.data.frame()에서stringsAsFactors = FALSE가 매우 중요한 역할을 하는 것임. 이 옵션을 설정하지 않을 경우Factor로 잡히면numeric으로 전환할 수 없게 됨.Factor는 본질적으로 음이 아닌 정수로 취급됨.- 보통 이 설정은
stringsAsFactors = default.stringsAsFactors()가 default 설정으로 되어 있고, 따라서default.stringsAsFactors() =FALSE 에 따라 설정을 바꿔주면 되어야 하나 써 있는 대로 되지 않는 경우가 있어서 가능한 설정해주는 것이 안전함. - 단순히
data.frame()으로 변환할 경우Factor로 설정되어numeric으로 변환하더라도 의미없는 숫자를 얻게 됨. as.data.frame()의 결과물로 두 개의 character vector 와 counts를 나타내는 새로운 변수Freq가 나오게 됨. 손가락 길이와 키를 나타내는 character를 numeric으로 전환하고 다음 작업 진행.
crimtab.2.df <- as.data.frame(crimtab.2, stringsAsFactors = FALSE)
str(crimtab.2.df)## 'data.frame': 924 obs. of 3 variables:
## $ finger: chr "9.4" "9.5" "9.6" "9.7" ...
## $ height: chr "56" "56" "56" "56" ...
## $ Freq : int 0 0 0 0 0 0 1 0 0 0 ...crimtab.2.df[1:2] <- sapply(crimtab.2.df[1:2], as.numeric)
str(crimtab.2.df)## 'data.frame': 924 obs. of 3 variables:
## $ finger: num 9.4 9.5 9.6 9.7 9.8 9.9 10 10.1 10.2 10.3 ...
## $ height: num 56 56 56 56 56 56 56 56 56 56 ...
## $ Freq : int 0 0 0 0 0 0 1 0 0 0 ...crimtab.2.long <- mapply(function(x) rep(x, crimtab.2.df$Freq), crimtab.2.df[c("finger", "height")])
# crimtab.2.long <- mapply(function(x, y) rep(x, y = crimtab.2.df$Freq), crimtab.2.df[c("finger", "height")])
# crimtab.2.long <- mapply(function(x, y) rep(x, y), y = crimtab.2.df$Freq, crimtab.2.df[c("finger", "height")])
# crimtab.2.long <- mapply(function(x) rep(x, crimtab.2.df$Freq), crimtab.2.df[, c("finger", "height")])
# crimtab.2.long <- mapply(function(x) rep(x, crimtab.2.df$Freq), crimtab.2.df[1:2])
# crimtab.2.long <- mapply(function(x) rep(x, crimtab.2.df$Freq), crimtab.2.df[, 1:2])
# crimtab.2.long <- mapply(function(x) rep(x, crimtab.2.df$Freq), crimtab.2.df[, 2])
# crimtab.2.long <- mapply(function(x) rep(x, crimtab.2.df$Freq), crimtab.2.df$height)
str(crimtab.2.long)## num [1:3000, 1:2] 10 10.3 9.9 10.2 10.2 10.3 10.4 10.7 10 10.1 ...
## - attr(*, "dimnames")=List of 2
## ..$ : NULL
## ..$ : chr [1:2] "finger" "height"crimtab.2.long.df <- data.frame(crimtab.2.long)
str(crimtab.2.long.df)## 'data.frame': 3000 obs. of 2 variables:
## $ finger: num 10 10.3 9.9 10.2 10.2 10.3 10.4 10.7 10 10.1 ...
## $ height: num 56 57 58 58 58 58 58 58 59 59 ...Graphic Representation
Base Graphics
- 키와 손가락길이의 산점도
plot(finger ~ height, data = crimtab.2.long.df)
- 변수 각각의 히스토그램은?
par(mfrow=c(1,2))
hist(crimtab.2.long.df$height, main="Histogram of Height", xlab="height(inches)")
hist(crimtab.2.long.df$finger, main="Histogram of Finger Length", xlab= "finger length(cm)")
# hist(crimtab.2.long.df["height"], main="Histogram of Height", xlab="height(inches)")
# hist(crimtab.2.long.df["finger"], main="Histogram of Finger Length", xlab= "finger length(cm)")- 평균과 표준편차를 한번에 구하려면 다음과 같이 anonymous function을 작성하고
mapply()를 이용하는 게 편함. 이를 모수로 하는 정규곡선을 덧씌워 볼 것.mean.sd()도 anonymous function 으로 평균과 표준편차를 계산해서 출력하는 함수임. 이와 같은 함수를 저장해 놓으려면dump()를 이용함.- 이와 같이 계산한 평균과 표준편차를 모수로 하는 정규곡선을 덧씌워 볼 것.
mean.sd <- function(x) {
mean <- mean(x, na.rm = TRUE)
sd <- sd(x)
list(mean = mean, sd = sd)
}
(crimtab.stat <- mapply(mean.sd, crimtab.2.long.df))## finger height
## mean 11.54737 65.473
## sd 0.5487137 2.557757str(crimtab.stat)## List of 4
## $ : num 11.5
## $ : num 0.549
## $ : num 65.5
## $ : num 2.56
## - attr(*, "dim")= int [1:2] 2 2
## - attr(*, "dimnames")=List of 2
## ..$ : chr [1:2] "mean" "sd"
## ..$ : chr [1:2] "finger" "height"# apply(crimtab.2.long, 2, mean)
# apply(crimtab.2.long, 2, sd)
dump("mean.sd", file="mean_sd.R")crimtab.stat이 어떤 성격을 갖는지 다음 질문과 추출 작업을 통해서 알아보자.
is.matrix(crimtab.stat)## [1] TRUEis.table(crimtab.stat)## [1] FALSEis.list(crimtab.stat)## [1] TRUEis.data.frame(crimtab.stat)## [1] FALSEcrimtab.stat[, 1]## $mean
## [1] 11.54737
##
## $sd
## [1] 0.5487137crimtab.stat[, "finger"]## $mean
## [1] 11.54737
##
## $sd
## [1] 0.5487137crimtab.stat[, "finger"][1]## $mean
## [1] 11.54737crimtab.stat[, "finger"][[1]]## [1] 11.54737crimtab.stat[1]## [[1]]
## [1] 11.54737crimtab.stat["finger"]## [[1]]
## NULLcrimtab.stat$finger## NULL(crimtab.stat.df <- data.frame(crimtab.stat))## finger height
## mean 11.54737 65.473
## sd 0.5487137 2.557757is.matrix(crimtab.stat.df)## [1] FALSEis.table(crimtab.stat.df)## [1] FALSEis.list(crimtab.stat.df)## [1] TRUEis.data.frame(crimtab.stat.df)## [1] TRUEcrimtab.stat.df[, 1]## $mean
## [1] 11.54737
##
## $sd
## [1] 0.5487137str(crimtab.stat.df[, 1])## List of 2
## $ mean: num 11.5
## $ sd : num 0.549crimtab.stat.df[, "finger"]## $mean
## [1] 11.54737
##
## $sd
## [1] 0.5487137str(crimtab.stat.df[, "finger"])## List of 2
## $ mean: num 11.5
## $ sd : num 0.549crimtab.stat.df[, "finger"][1]## $mean
## [1] 11.54737str(crimtab.stat.df[, "finger"][1])## List of 1
## $ mean: num 11.5crimtab.stat.df[, "finger"][[1]]## [1] 11.54737str(crimtab.stat.df[, "finger"][[1]])## num 11.5crimtab.stat.df[1]## finger
## mean 11.54737
## sd 0.5487137str(crimtab.stat.df[1])## 'data.frame': 2 obs. of 1 variable:
## $ finger:List of 2
## ..$ mean: num 11.5
## ..$ sd : num 0.549crimtab.stat.df["finger"]## finger
## mean 11.54737
## sd 0.5487137str(crimtab.stat.df["finger"])## 'data.frame': 2 obs. of 1 variable:
## $ finger:List of 2
## ..$ mean: num 11.5
## ..$ sd : num 0.549crimtab.stat.df["finger"][1]## finger
## mean 11.54737
## sd 0.5487137str(crimtab.stat.df["finger"][1])## 'data.frame': 2 obs. of 1 variable:
## $ finger:List of 2
## ..$ mean: num 11.5
## ..$ sd : num 0.549crimtab.stat.df["finger"][[1]]## $mean
## [1] 11.54737
##
## $sd
## [1] 0.5487137str(crimtab.stat.df["finger"][[1]])## List of 2
## $ mean: num 11.5
## $ sd : num 0.549crimtab.stat.df$finger## $mean
## [1] 11.54737
##
## $sd
## [1] 0.5487137str(crimtab.stat.df$finger)## List of 2
## $ mean: num 11.5
## $ sd : num 0.549crimtab.stat.df$finger[1]## $mean
## [1] 11.54737str(crimtab.stat.df$finger[1])## List of 1
## $ mean: num 11.5crimtab.stat.df$finger[[1]]## [1] 11.54737str(crimtab.stat.df$finger[[1]])## num 11.5ggplot
- 키와 손가락 길이의 산점도
library(ggplot2)
ggplot(crimtab.2.long.df, aes(x = height, y = finger)) + geom_point()
ggplot(crimtab.2.long.df, aes(x = height, y = finger)) + geom_point(alpha = 0.9)
ggplot(crimtab.2.long.df, aes(x = height, y = finger)) + geom_point(alpha = 0.5)
ggplot(crimtab.2.long.df, aes(x = height, y = finger)) + geom_point(alpha = 0.1)
ggplot(crimtab.2.long.df, aes(x = height, y = finger)) + geom_point(position = "jitter")
ggplot(crimtab.2.long.df, aes(x = height, y = finger)) + geom_point(position = "jitter", size = 0.7)
ggplot(crimtab.2.long.df, aes(x = height, y = finger)) + geom_point(position = position_jitter(), size = 0.7)
ggplot(crimtab.2.long.df, aes(x = height, y = finger)) + geom_point(position = position_jitter(width = 1, height = 0), size = 0.7)
ggplot(crimtab.2.long.df, aes(x = height, y = finger)) + geom_point(position = position_jitter(width = 1, height = 0.1), size = 0.7)
ggplot(crimtab.2.long.df, aes(x = height, y = finger)) + geom_point(position = position_jitter(width = 1, height = 0.1), size = 0.7) +
theme_bw()
- 변수 각각의 히스토그램
ggplot(crimtab.2.long.df, aes(x = height)) + geom_histogram(alpha=0.5)## stat_bin: binwidth defaulted to range/30. Use 'binwidth = x' to adjust this.
ggplot(crimtab.2.long.df, aes(x = finger)) + geom_histogram(alpha=0.5)## stat_bin: binwidth defaulted to range/30. Use 'binwidth = x' to adjust this.
ggplot(crimtab.2.long.df, aes(x = height)) + geom_histogram(aes(y = ..density..), binwidth=1, alpha=0.5)
ggplot(crimtab.2.long.df, aes(x = finger)) + geom_histogram(aes(y = ..density..), binwidth=0.1, alpha=0.5)
(g.h.1 <- ggplot(crimtab.2.long.df, aes(x = height)) + geom_histogram(aes(y = ..density..), binwidth = 1, fill = "white", colour = "black"))
(g.f.1 <- ggplot(crimtab.2.long.df, aes(x = finger)) + geom_histogram(aes(y = ..density..), binwidth = 0.2, fill = "white", colour = "black"))
breaks설정의 필요성- default 로 그린 히스토그램에 평균과 표준편차를 위치시켜보면, Quetelet의 가슴둘레 자료를 히스토그램으로 표현할 때와 같이 0.5만큼 치우친 것을 알 수 있음.
- 따라서
geom_histogram의 원형인stat_bin에breaks=를 재설정할 필요.
library(grid)
(mean.finger <- crimtab.stat[, 1][[1]])## [1] 11.54737(sd.finger <- crimtab.stat[, 1][[2]])## [1] 0.5487137(mean.height <- crimtab.stat[, 2][[1]])## [1] 65.473(sd.height <- crimtab.stat[, 2][[2]])## [1] 2.557757x.finger <- seq(9.5, 13.5, length.out = 3000)
y.finger <- dnorm(x.finger, mean = mean.finger, sd = sd.finger)
x.height <- seq(56, 77, length.out = 3000)
y.height <- dnorm(x.height, mean = mean.height, sd = sd.height)
(g.h.2 <- g.h.1 + annotate("segment", x = mean.height, xend = mean.height, y= -0.02, yend = 0, arrow = arrow(length=unit(0.3, "cm"))))
(g.h.3 <- g.h.2 + theme_bw())
(g.h.4 <- g.h.3 + geom_line(aes(x = x.height, y = y.height)))
(g.h.5 <- ggplot(crimtab.2.long.df, aes(x = height)) + stat_bin(aes(y = ..density..), binwidth = 1, breaks = 55.5:77.5, fill = "white", colour="black"))
(g.h.6 <- g.h.5 + annotate("segment", x = mean.height, xend = mean.height, y= -0.02, yend = 0, arrow = arrow(length = unit(0.3, "cm"))))
(g.h.7 <- g.h.6 + theme_bw())
(g.h.8 <- g.h.7 + geom_line(aes(x = x.height, y = y.height)))
(g.f.1 <- ggplot(crimtab.2.long.df, aes(x = finger)) + geom_histogram(aes(y = ..density..), binwidth = 0.2, fill = "white", colour = "black"))
(g.f.2 <- g.f.1 + annotate("segment", x = mean.finger, xend = mean.finger, y= -0.1, yend = 0, arrow = arrow(length = unit(0.3, "cm"))))
(g.f.3 <- g.f.2 + theme_bw())
(g.f.4 <- g.f.3 + geom_line(aes(x = x.finger, y = y.finger)))
(g.f.5 <- ggplot(crimtab.2.long.df, aes(x = finger)) + stat_bin(aes(y = ..density..), breaks = seq(9.45, 13.55, by=0.2), fill = "white", colour="black"))
(g.f.6 <- g.f.5 + annotate("segment", x=mean.finger, xend = mean.finger, y=-0.1, yend=0, arrow=arrow(length=unit(0.3, "cm"))))
(g.f.7 <- g.f.6 + theme_bw())
(g.f.8 <- g.f.7 + geom_line(aes(x=x.finger, y=y.finger)))
Data 갈무리
save.image(file="crimtab_1007.rda")
# cor(crimtab.2.long[,1], crimtab.2.long[,2])