我似乎错过了ggplot2如何工作的变化.我有一个统计教科书的例子(A. Field(2012),使用R,p.593发现统计数据),我确信它可以工作,但现在不再产生分组数据之间的连接线.
这是示例数据:
participant<-gl(20, 9, labels = c("P01", "P02", "P03", "P04", "P05", "P06", "P07", "P08", "P09", "P10", "P11", "P12", "P13", "P14", "P15", "P16", "P17", "P18", "P19", "P20" ))
drink<-gl(3, 3, 180, labels = c("Beer", "Wine", "Water"))
imagery<-gl(3, 1, 180, labels = c("Positive", "Negative", "Neutral"))
groups<-gl(9, 1, 180, labels = c("beerpos", "beerneg", "beerneut", "winepos", "wineneg", "wineneut", "waterpos", "waterneg", "waterneut"))
attitude<-c(1, 6, 5, 38, -5, 4, 10, -14, -2, 26, 27, 27, 23, -15, 14, 21, -6, 0, 1, -19, -10, 28, -13, 13, 33, -2, 9, 7, -18, 6, 26, -16, 19, 23, -17, 5, 22, -8, 4, 34, -23, 14, 21, -19, 0, 30, -6, 3, 32, -22, 21, 17, -11, 4, 40, -6, 0, 24, -9, 19, 15, -10, 2, 15, -9, 4, 29, -18, 7, 13, -17, 8, 20, -17, 9, 30, -17, 12, 16, -4, 10, 9, -12, -5, 24, -15, 18, 17, -4, 8, 14, -11, 7, 34, -14, 20, 19, -1, 12, 43, 30, 8, 20, -12, 4, 9, -10, -13, 15, -6, 13, 23, -15, 15, 29, -1, 10, 15, 15, 12, 20, -15, 6, 6, -16, 1, 40, 30, 19, 28, -4, 0, 20, -10, 2, 8, 12, 8, 11, -2, 6, 27, 5, -5, 17, 17, 15, 17, -6, 6, 9, -6, -13, 30, 21, 21, 15, -2, 16, 19, -20, 3, 34, 23, 28, 27, -7, 7, 12, -12, 2, 34, 20, 26, 24, -10, 12, 12, -9, 4)
longAttitude<-data.frame(participant, drink, imagery, groups, attitude)
Run Code Online (Sandbox Code Playgroud)
这是情节代码:
library(ggplot2)
attitudeInt <- ggplot(longAttitude, aes(drink, attitude, colour = imagery))
attitudeInt + stat_summary(fun.y = mean, geom = "point") +
stat_summary(fun.y = mean, geom = "line", aes(group = imagery)) +
stat_summary(fun.data = mean_cl_boot, geom = "errorbar", width = 0.2) +
labs(x = "Type of Drink", y = "Mean Attitude", colour = "Type of Imagery")
Run Code Online (Sandbox Code Playgroud)
是不是部件stat_summary(fun.y = mean, geom="line", aes(group = imagery))应该准确地绘制这些连接线?
谢谢你的帮助.
这不会解决问题,ggplot2但这是解决方法.
首先总结一下你的数据.与mean_cl_boot用于计算置信区间的原始代码一样,也在本示例中使用.
library(plyr)
dfAtt<-ddply(longAttitude,~drink+imagery,function(x) mean_cl_boot(x$attitude))
dfAtt
drink imagery y ymin ymax
1 Beer Positive 21.05 15.65000 26.90750
2 Beer Negative 4.45 -2.60125 12.00000
3 Beer Neutral 10.00 5.49750 14.75000
4 Wine Positive 25.35 22.40000 28.25000
5 Wine Negative -12.00 -14.40000 -9.49875
6 Wine Neutral 11.65 8.95000 14.40125
7 Water Positive 17.40 14.40000 20.45000
8 Water Negative -9.20 -12.25000 -6.34875
9 Water Neutral 2.35 -0.75125 4.90000
Run Code Online (Sandbox Code Playgroud)
然后绘制您的数据:
ggplot(dfAtt, aes(x=drink, y=y, colour=imagery,group=imagery)) +
geom_errorbar(aes(ymin=ymin, ymax=ymax), width=.2) +
geom_line() +
geom_point() +
labs(x = "Type of Drink", y = "Mean Attitude", colour = "Type of Imagery")
Run Code Online (Sandbox Code Playgroud)

| 归档时间: |
|
| 查看次数: |
2756 次 |
| 最近记录: |