我设法用我的 2 个定量变量创建了一个多面箱线图；我知道如何运行 kruskal-wallis，然后进行 Wilcoxon 检验，并在箱线图中显示字母的显着差异，但仅在一个简单的箱线图中，有一个变量且没有方面。我能怎么做 ？（如果可能的话，我想用字母表示显着差异，我希望我能够发布我已经做过的照片，但显然我不允许）另外，我还有另一个问题；函数 stat_function_mean 执行哪个测试？我尝试使用此功能，但我不知道如何使用它......这是我的代码没有测试，只有我的两个变量的分面箱线图：
带有 2 个测量变量（FF 和 FM）的方面箱线图的代码
dat.m2 <- melt(pheno,id.vars=c("fusion","Genotype","Hormone"),
measure.vars=c('FF','MF'))
dat.m2$fusion<-factor(dat.m2$fusion, levels=c("Control", "CK 20 mg/L", "CK 100 mg/L", "CK 500 mg/L", "GA 20 mg/L", "GA 100 mg/L", "GA 500 mg/L"))
levels(dat.m2$fusion)
ggplot(dat.m2) +
geom_boxplot(aes(x=fusion, y=value, colour=variable))+
facet_wrap(~Genotype)+
xlab(" ")+
ylab("Days after sowing")
在图表上添加显着差异的代码，带有字母，但只有 1 个测量变量 (FF)，没有刻面
mymat <-tri.to.squ(pp$p.value)
mymat
myletters <- multcompLetters(mymat,compare="<=",threshold=0.05,Letters=letters)
myletters
myletters_df <- data.frame(fusion=names(myletters$Letters),letter = myletters$Letters )
myletters_df
ggplot(pheno, aes(x=fusion, y=FF, colour=fusion))+
geom_boxplot()+
geom_text(data = myletters_df, aes(label = letter, y = 30 ), colour="black", size=5)+
ylab("Days after sowing")+
xlab("")+
labs(title="Days to female flower production")+
theme(plot.title = element_text(hjust = 0.5))+
> dput(pheno)
structure(list(Genotype = structure(c(2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L,
3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L,
3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("F1045",
"FF", "M1585", "M1610"), class = "factor"), X = structure(c(1L,
105L, 116L, 127L, 138L, 149L, 160L, 171L, 182L, 2L, 13L, 24L,
35L, 46L, 57L, 68L, 79L, 90L, 101L, 106L, 107L, 108L, 109L, 110L,
111L, 112L, 113L, 114L, 115L, 117L, 118L, 119L, 120L, 121L, 122L,
123L, 124L, 125L, 126L, 128L, 129L, 130L, 131L, 132L, 133L, 134L,
135L, 136L, 137L, 139L, 140L, 141L, 142L, 143L, 144L, 145L, 146L,
147L, 148L, 150L, 151L, 152L, 153L, 154L, 155L, 156L, 157L, 158L,
159L, 161L, 162L, 163L, 164L, 165L, 166L, 167L, 168L, 169L, 170L,
172L, 173L, 174L, 175L, 176L, 177L, 178L, 179L, 180L, 181L, 183L,
184L, 185L, 186L, 187L, 188L, 189L, 190L, 191L, 192L, 3L, 4L,
5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 14L, 15L, 16L, 17L, 18L, 19L,
20L, 21L, 22L, 23L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L,
34L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 47L, 48L,
49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 58L, 59L, 60L, 61L, 62L,
63L, 64L, 65L, 66L, 67L, 69L, 70L, 71L, 72L, 73L, 74L, 75L, 76L,
77L, 78L, 80L, 81L, 82L, 83L, 84L, 85L, 86L, 87L, 88L, 89L, 91L,
92L, 93L, 94L, 95L, 96L, 97L, 98L, 99L, 100L, 102L, 103L, 104L
), .Label = c("H1", "H10", "H100", "H101", "H102", "H103", "H104",
"H105", "H106", "H107", "H108", "H109", "H11", "H110", "H111",
"H112", "H113", "H114", "H115", "H116", "H117", "H118", "H119",
"H12", "H120", "H121", "H122", "H123", "H124", "H125", "H126",
"H127", "H128", "H129", "H13", "H130", "H131", "H132", "H133",
"H134", "H135", "H136", "H137", "H138", "H139", "H14", "H140",
"H141", "H142", "H143", "H144", "H145", "H146", "H147", "H148",
"H149", "H15", "H150", "H151", "H152", "H153", "H154", "H155",
"H156", "H157", "H158", "H159", "H16", "H160", "H161", "H162",
"H163", "H164", "H165", "H166", "H167", "H168", "H169", "H17",
"H170", "H171", "H172", "H173", "H174", "H175", "H176", "H177",
"H178", "H179", "H18", "H180", "H181", "H182", "H183", "H184",
"H185", "H186", "H187", "H188", "H189", "H19", "H190", "H191",
"H192", "H2", "H20", "H21", "H22", "H23", "H24", "H25", "H26",
"H27", "H28", "H29", "H3", "H30", "H31", "H32", "H33", "H34",
"H35", "H36", "H37", "H38", "H39", "H4", "H40", "H41", "H42",
"H43", "H44", "H45", "H46", "H47", "H48", "H49", "H5", "H50",
"H51", "H52", "H53", "H54", "H55", "H56", "H57", "H58", "H59",
"H6", "H60", "H61", "H62", "H63", "H64", "H65", "H66", "H67",
"H68", "H69", "H7", "H70", "H71", "H72", "H73", "H74", "H75",
"H76", "H77", "H78", "H79", "H8", "H80", "H81", "H82", "H83",
"H84", "H85", "H86", "H87", "H88", "H89", "H9", "H90", "H91",
"H92", "H93", "H94", "H95", "H96", "H97", "H98", "H99"), class = "factor"),
Hormone = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("CK", "Control", "GA"), class = "factor"),
Hormone.quantity = structure(c(4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L), .Label = c("100", "20", "500", "Control"
), class = "factor"), fusion = structure(c(4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("CK 100 mg/L",
"CK 20 mg/L", "CK 500 mg/L", "Control", "GA 100 mg/L", "GA 20 mg/L",
"GA 500 mg/L"), class = "factor"), Sowing.date = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = "25-mrt", class = "factor"),
BT = structure(c(6L, 7L, 6L, 6L, 6L, 6L, 6L, 6L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 6L, 4L, 4L, 4L, 4L, 2L, 4L, 4L, 2L,
2L, 2L, 2L, 2L, 6L, 6L, 6L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L,
1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L,
2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
2L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 6L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 8L, 4L, 6L, 6L, 6L, 4L, 3L, 4L, 4L, 3L,
4L, 3L, 3L, 3L, 3L, 6L, 6L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 4L, 3L, 4L, 3L, 3L, 3L, 4L, 3L, 6L, 6L, 8L, 6L, 4L, 4L,
4L, 8L, 4L, 4L, 2L, 3L, 3L, 3L, 3L, 6L, 3L, 5L, 4L, 5L, 5L,
4L, 3L), .Label = c("16-apr", "17-apr", "18-apr", "19-apr",
"21-mei", "23-apr", "26-apr", "30-apr"), class = "factor"),
ff = structure(c(14L, 20L, 4L, 10L, 20L, 3L, 1L, 14L, 9L,
11L, 20L, 11L, 9L, 9L, 9L, 11L, 12L, 12L, 6L, 12L, 12L, 16L,
12L, 12L, 17L, 17L, 12L, 16L, 17L, 18L, 12L, 6L, 20L, 20L,
15L, 15L, 15L, 20L, 20L, 11L, 11L, 11L, 9L, 9L, 9L, 9L, 20L,
20L, 20L, 4L, 1L, 4L, 4L, 4L, 8L, 20L, 4L, 20L, 12L, 4L,
14L, 14L, 11L, 11L, 15L, 15L, 11L, 11L, 9L, 15L, 9L, 9L,
11L, 11L, 14L, 1L, 5L, 4L, 4L, 20L, 20L, 20L, 20L, 20L, 20L,
20L, 20L, 20L, 15L, 15L, 14L, 13L, 15L, 15L, 11L, 9L, 9L,
11L, 9L, 11L, 1L, 20L, 1L, 20L, 20L, 20L, 20L, 1L, 1L, 4L,
20L, 20L, 20L, 15L, 15L, 14L, 15L, 1L, 15L, 15L, 20L, 11L,
11L, 11L, 11L, 15L, 10L, 10L, 16L, 10L, 12L, 10L, 17L, 8L,
16L, 12L, 8L, 4L, 4L, 8L, 20L, 10L, 1L, 20L, NA, 12L, 10L,
20L, 20L, 20L, 1L, 20L, 1L, 20L, 12L, 16L, 12L, 2L, 8L, 4L,
10L, 4L, 4L, 4L, 10L, 8L, 4L, 8L, 20L, 20L, 20L, NA, 20L,
1L, 20L, 1L, 8L, 20L, 1L, 1L, 7L, 17L, 19L, 19L, 12L, 10L,
12L, 19L, 10L, 10L, 10L, 17L), .Label = c("10-mei", "13-jun",
"14-apr", "14-mei", "17-mei", "18-jun", "21-jun", "21-mei",
"23-apr", "24-mei", "26-apr", "28-mei", "3-apr", "3-mei",
"30-apr", "31-mei", "4-jun", "5-jul", "7-jun", "7-mei"), class = "factor"),
FH = c(3.5, 6, 9, 16, 5.5, 12, 11.5, 4, 4.5, 6, 8, 5, 4.5,
3.5, 4, 5, 20, 42, 14, 40, 27, 42, 27, 26, 16, 18, 35, 17,
20, 28, 15, 20, 33, 32, 14.5, 14.5, 14.5, 35, 32, 12.5, 13.5,
12, 14.5, 12, 15, 14.5, 18, 18, 18.5, 35, 23, 25, 30, 37,
53, 27.5, 37, 25.5, 35, 47, 8.5, 20.5, 13, 14.5, 13.5, 18.5,
10.5, 10, 14.3, 18.5, 15.3, 11.7, 16, 15, 13.5, 26, 36, 30,
43, 23.5, 23.5, 31.5, 29, 30.5, 30, 29, 30, 24.5, 19, 23,
21.5, 26.5, 18.5, 20, 15, 12.3, 17, 12, 15, 13, 43614, 25,
27, 22.5, 35, 23.5, 30, 42, 42, 55, 32.5, 26, 26, 9.5, 4.5,
5.5, 5, 15.5, 10, 4.5, 8.5, 6, 5, 5.5, 5, 4.5, 30, 20, 16,
16, 20, 22, 30, 22, 25, 11, 13.5, 11, 11, 14, 6, NA, 5.5,
7, NA, 12, 14, 7, 9.5, 6.5, 9, 8.5, 12.5, 8, 27, 33, 35,
32, 17, 14, 22, 11, 17, 12, 25, 22, 15, 10, 5, 3, 4, NA,
5, 8, 4.5, 6, 7, 5, 5.5, 7, 42, 23, 23, 21, 14, 21, 17, 22,
19, 18, 17, 17), SRDT = structure(c(2L, 7L, 14L, NA, 7L,
8L, 7L, NA, NA, NA, 3L, NA, 18L, 15L, 17L, 17L, 18L, 18L,
NA, 18L, 15L, 17L, 15L, 20L, 2L, NA, 11L, 17L, 18L, 2L, 2L,
2L, 14L, 12L, 17L, 15L, 12L, 9L, 9L, 6L, 6L, 15L, 15L, 15L,
15L, NA, 17L, 15L, 10L, 11L, 11L, 10L, 11L, 17L, 5L, 21L,
6L, NA, 20L, 5L, 12L, 7L, NA, 17L, 17L, 15L, 15L, 10L, 10L,
6L, 10L, 10L, 21L, NA, 15L, 15L, 5L, 15L, 15L, 11L, 10L,
21L, 1L, 21L, 21L, 21L, 1L, 5L, 18L, 2L, 9L, 9L, NA, 12L,
10L, NA, 16L, 6L, 6L, 15L, 6L, 10L, 10L, 10L, 1L, 10L, 1L,
21L, 21L, 1L, 21L, 5L, 18L, 2L, 17L, 20L, 9L, 14L, 5L, 9L,
9L, 11L, NA, 18L, 10L, 18L, 20L, 4L, 9L, 7L, 2L, 2L, 7L,
5L, 17L, 17L, 11L, 10L, 12L, 2L, 14L, 19L, 19L, 19L, NA,
NA, 2L, 11L, 17L, 14L, 17L, 9L, 10L, 10L, 2L, 7L, 17L, 14L,
2L, 11L, 20L, 2L, 15L, 15L, 11L, 5L, NA, 10L, NA, 2L, 8L,
NA, NA, 14L, 5L, 15L, 15L, NA, 22L, NA, 9L, 9L, 19L, 9L,
9L, 22L, 20L, 13L, 7L, 20L, 15L, 20L), .Label = c("10-mei",
"11-jun", "13-jun", "13-mei", "14-mei", "17-mei", "18-jun",
"2-jul", "21-jun", "21-mei", "24-mei", "25-jun", "26-jun",
"28-jun", "28-mei", "3-mei", "31-mei", "4-jun", "5-jul",
"7-jun", "7-mei", "9-jul"), class = "factor"), MH = c(26,
50, 58, NA, 46, 58, 61, NA, NA, NA, 40, NA, 68, 48, 47, 42,
26, 50, NA, 48, 27, 42, 27, 48, 25, NA, 25, 17, 20, 18, 32,
19, 75, 75, 65, 70, 73, 73, 71, 65, 70, 60, 80, 70, 70, NA,
54, 45, 45, 45, 45, 40, 49, 53, 45, 27.5, 44, NA, NA, 47,
47, 62, NA, 75, 60, 75, 70, 65, 80, 67, 80, 75, 52, NA, 67,
68, 26, 55, 60, 60, 60, 31.5, 39, 30.5, 30, 29, 39, 39, 86,
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45, 60, 39, 35, 32.5, 27, 32.5, 43, 70, 75, 60, 66, 58, 48,
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33, 36, 40, 21, 36, 23.5, 21, 44, 60, 37, 37, 55, 24, 45,
45, 35, 30, 25, 12, 27, 10, NA, 53, 35, NA, NA, 43, 11, 13,
7, NA, 22, NA, 42, 46, NA, 41, 43, 40, 26, 45, 35, 29, 17,
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80L, 57L, 50L, 60L, 50L, 50L, 50L, 60L, 57L, 50L, 57L, 43L,
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71L, 74L, 74L, 64L, 60L, 64L, 74L, 60L, 60L, 60L, 71L), MF = c(78L,
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用我的图表图片会更清楚，但显然我还不允许在我的帖子中包含图片，对不起
在此先感谢您的帮助
