tmp <- data.frame( statistic=c(68,85,74,88,63,78,90,80,58,63), math=c(85,91,74,100,82,84,78,100,51,70))
library(ggplot2)
#head(tmp)
ggplot(tmp, aes(x=statistic, y=math)) + geom_point( color=“orange”, fill=“#69b3a2”, shape=21, alpha=0.5, size=6, stroke = 2 )
ggplot(tmp, aes(x=math )) + geom_bar(color=“blue”, fill=rgb(0.1,0.4,0.5,0.7) )
hist(tmp$math, col= “lightyellow”, main =“數學成績”, xlab =“成績”, ylab =“數學”)
data <- data.frame(
社團類型=c(“娛樂休閒”,“知識閱讀”,“體育競技”,“科技創新”,“公益活動”)
,
次數=c(185,82,36,28,25) ) ggplot(data, aes(x=社團類型, y=次數)) +
geom_bar(stat = “identity”, width=0.2, fill=“skyblue”)
data<- c(185,82,36,28,25) labels <- c(“娛樂休閒”,“知識閱讀”,“體育競技”,“科學創新”,“公益活動”)
pie(data,labels,main =“大學生最喜歡參加的社團的次數圓餅圖”, col=heat.colors(length(data)))
data2 <- data.frame( x=c(“娛樂休閒”,“知識閱讀”,“體育競技”,“科學創新”,“公益活動”), y=c(185,82,36,28,25)) ggplot(data2, aes(x=x, y=y)) + geom_segment( aes(x=x, xend=x, y=0, yend=y)) + geom_point( size=5, color=“red”, fill=alpha(“orange”, 0.3), alpha=0.7, shape=21, stroke=2)
data3 <-c(84,63,61,49,89,51,59,53,79,91) stem(data3) ## ## The decimal point is 1 digit(s) to the right of the | ## ## 4 | 9 ## 5 | 139 ## 6 | 13 ## 7 | 9 ## 8 | 49 ## 9 | 1 data4 <- c(84,63,61,49,89,51,59,53,79,91) mean(data4) ## [1] 67.9 median(data4) ## [1] 62 as.numeric(names(table(data4)))[which.max(table(data4))] ## [1] 49 sd(data4) ## [1] 16.25115 var(data4) ## [1] 264.1 quantile(data4, 1 / 4) ## 25% ## 54.5 quantile(data4, 3 / 4) ## 75% ## 82.75