DAA02

Size: px

Start display at page:

Download "DAA02"

ほのかゆきしげ
4 years ago
Views:

3 c(var1,var2,...,varn) > x<-c(1,2,3,4) > x [1] > x2<-c(x,5,6,7,8) > x2 [1]

4 c(var1,var2,...,varn) > y=c('a0','a1','b0','b1') > y [1] "a0" "a1" "b0" "b1 > z=c(x,y) > z [1] "1" "2" "3" "4" "a0" "a1" "b0" "b1"

5 rep(x, times) > x<-rep(1,4) (1) [1] > x<-rep(c(1,7,87),3) (2) [1,7,87] [1] > x<-rep(1:4,3) (3) 1:4 seq [1] > x<-sort(rep(1:4,3)) (4) (3) [1]

6 seq(start, end, increment/decrement) > x<-seq(1,4,1) [1] > x<-seq(0,40,10) [1] > x<-seq(10,2,-2) [1] > x<-1:4 # [1] > x<-10:1 # - [1]

8 > a=1:10 [1] > which(a<5) [1] > b=10:1 [1] > which(b<5) [1]

9 > x<-matrix(1:8, nrow=2) [,1] [,2] [,3] [,4] [1,] [2,] > x<-matrix(1:8, nrow=2,byrow=t) [,1] [,2] [,3] [,4] [1,] [2,]

10 data01<-data.frame(score = c(2,4,3,4), dose = c(rep(10,2),rep(100,2)), condition = rep(c('exp','control'),2)) > data01 score dose condition exp control exp control

11 dat01<-read.csv(" header=t) > dat01 x y z

12 dat02<-read.csv(" header=t, row.name=1) > dat02 x y z katsuo wakame tarachan

13 > dat03<-read.table(" header=t, row.name=4) > dat03 x y z sazae masuo tarachan

14 matrix M[ ] > dat03 x y z sazae masuo tarachan > dat03[1,1] #1 1 [1] 11

15 n M[n, ] m M[, m] > dat03 x y z sazae masuo tarachan > dat03[2,] # x y z masuo > dat03[,1] #1 [1]

16 M$varName > dat03 x y z sazae masuo tarachan > dat03$x [1] > dat03$y [1] > dat03$z [1]

17 > dat03 x y z sazae masuo tarachan > colnames(dat03)<-c("var1","var2","var3") > dat03 var1 var2 var3 sazae masuo tarachan

18 Dat03 score dat03 var1 var2 var3 Name Conditionn, var1, var2, var3 > dat04 score name condition 1 11 sazae var1 > dat masuo var2 var1 var2 var tarachan var3 sazae sazae var1 masuo masuo var tarachan var3 tarachan sazae var masuo var tarachan var3

19 score var1 var2 var3 Name Conditionn, var1, var2, var3 > dat04<-data.frame(score=c(dat03$var1,dat03$var2,dat03$var3), name=rep(rownames(dat03),3), condition = rep(c("var1","var2","var3"),3))

20 dat<-read.csv(" > head(dat) shoesize header=t); h gender M M M M F F > head(dat) shoesize height (meter) gender M M M M F F

21 mean(dat$shoesize[dat$gender == "M"]) [1] # mean(dat$shoesize[dat$gender == "F"]) [1] # mean(dat$shoesize[dat$h > 180]) [1] 27.5 # 180cm

23 v1 = seq(-3,3,0.1) v2 = v1^2 > plot(x = v1, y = v2) y x col= color > plot(v1, v2, col = 'red') y x

24 marker pch = N > plot(v1, v2, col= red ) > plot(v1, v2, col= red, pch = 20) # N: 0~25 # help(points)

25 marker cex = N > plot(v1, v2, col= red, pch = 20) > plot(v1, v2, col= red, pch = 20, cex = 3)

27 type= style > plot(v1, v2) > plot(v1, v2, type = l ) # style: p:points l:line b:both (points & line) o:overlay (points & line) n:none

28 lty = N #N: 1~6 lwd = W > plot(v1,v2,type='l',lty=4,lwd=3) y x

29 plot(v1, v2, main = "THIS IS THE TITLE", xlab = "Label for X-axis", ylab = "Label for Y-axis") THIS IS THE TITLE Label for Y-axis Label for X-axis

30 plot(v1, v2, main = "THIS IS THE TITLE", cex.lab = 1.5, xlab = "Label for X-axis",ylab = "Label for Y-axis")

31 X Y plot(v1, v2, main = "TITLE", xlab = "X here",ylab = "Y here", xlim = c(-3.5, 3.5), TITLE ylim = c(-0.5, 10)) Label for Y-axis THIS IS THE TITLE Y here Label for X-axis X here

32 plot(v1, v2, col = "blue", type = "o", lty = 2, pch = 19, cex.lab = 1.5, lwd = 3, main = "Y=X*X", xlab = "X", ylab="x*x", xlim=c(-3.5,3.5), ylim=c(-0.5, 10))

33 Histogram > dat<- read.csv(" > hist(dat$h)

34 Histogram > hist(dat$h, breaks = 20, main = Histogram of Height, xlab = "Height", col = 'blue', xlim = c(140, 190))

35 dens<-density(dat$h); # hist(dat$h, main = "Histogram of Height", xlab = "Height", xlim = c(140,190), probability = T) lines(dens, lwd = 2, col = red, lty=2) # Histogram of Height Density Height

36 #lines plot(v1, v2, col = "blue", type = "l", pch = 19, cex.lab = 1.5, lwd = 3, xlab = "X", ylab="f(x)", xlim=c(-3.5,3.5), ylim=c(-0.5, 10)) lines(v1, v1^3, col='red',lwd = 3)

37 #legend legend("bottomright", c("x^2","x^3"), col=c('blue','red'), lwd=2)

38 > boxplot(dat$h,main="boxplot of Height", ylab="height", col='cyan', ylim=c(140,190)) > boxplot(dat$h,main="boxplot of Height", xlab="height", col= ornage', horizontal=t) Boxplot of Height Height

40 boxplot(dat$h ~ dat$gender, main="distribution of Height by Gender", ylab="gender", xlab="height", col=c('blue','cyan'), ylim=c(140,190), horizontal=t) Distribution of Height by Gender Gender F M

41 dat<-read.table(" boxplot(dat$h ~ dat$gender + dat$affil, main="distribution of Height by Gender and Affiliation", ylab="gender x Affiliation", xlab="height", col=c('blue,'cyan,'red,'magenta'), ylim=c(140,190),horizontal=t) Distribution of Height by Gender and Affiliation Gender x Affiliation F.cs M.cs F.psy M.psy Height

42 interaction.plot(dat$gender, dat$affil, dat$h, Y pch=c(20,20), col=c("skyblue","orange"), xlab="gender", ylab= height", lwd=3,type='b',cex=2, trace.label="affiliation") Legend X

43 Distribution of Height by Gender and Affiliation Gender x Affiliation F.cs M.cs F.psy M.psy Height

44 HISTOGRAM par(mfrow=c(1,2)) # figure Dist. of Height for Female Participants Dist. of Height for Male Participants Density Density Height Height

45 HISTOGRAM hist(dat[dat$gender=='f',]$h, main="dist. of Height for Female Participants", xlab="height", xlim=c(140,190), probability=t) dens.f = density(dat[dat$gender=='f',]$h) lines(dens.f, col='blue',lwd=2) hist(dat[dat$gender== M,]$h, main= Dist. of Height for Male Participants, xlab= Height, xlim=c(140,190), probability=t,ylim=c(0,0.08)) dens.m = density(dat[dat$gender=='m',]$h) lines(dens.m, col='green', lwd=2)

46 HISTOGRAM Dist. of Height for Female Participants Dist. of Height for Male Participants Density Density Height Height

47 par(mfrow=c(1,1)) plot(dens.f,col='blue',lwd=2, ylab='density', xlim=c(140,190), main="dist. of Height by gender",xlab='height') lines(dens.m,col='green',lwd=2) legend("topleft", c('female','male'), col=c('blue','green'), cex=1.5,lwd=2)

48 # text(x,y, TEXT ) text(157.5, 0.04, 'Female', col='blue', cex=2) text(170, 0.04,'Male', col='green', cex=2) Dist. of Height by gender density Female Male Height

50 # plot(x,y, ) plot(dat$shoesize, dat$h, main="relationship b/w shoesize and height, xlab = 'shoesize, ylab='height, pch=19, col='red ) Relationship b/w shoesize and height height shoesize

51 txt = paste("r =",round(cor(dat$shoesize,dat$h), 4)) > txt[1] "r = 0.875" a=1:3 paste("s",a) => [1] "s 1" "s 2" "s 3" paste( s, a, sep= ) => [1] "s1" "s2" "s3"

52 txt = paste("r =", round(cor(dat$shoesize,dat$h), 4)) text(22, 175, txt, cex = 1.5) Relationship b/w shoesize and height height r = shoesize

53 abline: abline(h = mean(dat$h), col='blue'); abline(v = mean(dat$shoesize), col='green'); Relationship b/w shoesize and height H V height r = mean height mean shoesize shoesize

54 abline(lm(dat$h~dat$shoesize), lty=2, lwd=2) Relationship b/w shoesize and height height r = shoesize

55 plot(dat[dat$gender=='f',]$shoesize, dat[dat$gender=='f',]$h, main="relationship b/w shoesize and height", xlab='shoesize', ylab='height', cex.lab=1.5, pch=19, col='blue', xlim=c(20,29), ylim=c(140,190)) Relationship b/w shoesize and height height Female Male shoesize

56 lines(dat[dat$gender=='m',]$shoesize,dat[dat$gender=='m',]$h, type = 'p', pch = 15, col = 'green') legend("topleft", c('female','male'), pch =c(19,15), col = c('blue','green'), cex = 1.5) height Female Male Relationship b/w shoesize and height shoesize

57 plot(dat.reg, pch=20, col=c('blue')) material price design sales

58 plot(dat.pca, pch = rownames(dat.pca), cex = 1.7, col = 'blue') writing a b c d e f g h i a b c d e f g h i a b c d e f g h i thesis a b c d e f g h i a b c d e f g h i a b c d e f g h i interview

DAA03

DAA03 par(mfrow=c(1,2)) # figure Dist. of Height for Female Participants Dist. of Height for Male Participants Density 0.00 0.02 0.04 0.06 0.08 Density 0.00 0.02 0.04 0.06 0.08 140 150 160 170 180 190 Height