ggplot分组框图（R）中的平均值

时间：2017-02-12 12:33:39

标签： r ggplot2 mean boxplot

虽然之前曾问here这个问题，但我有一个新的数据框，因此是一个新问题。数据样本如下所示：

ID,Region,Dimension,BlogsInd.,BlogsNews,BlogsTech,Columns
1,PK,Dim1,-4.75,NA,NA,NA
2,PK,Dim1,-5.69,NA,NA,NA
3,PK,Dim1,-0.27,NA,NA,NA
4,PK,Dim1,-2.76,NA,NA,NA
5,PK,Dim1,-8.24,NA,NA,NA
6,PK,Dim1,-12.51,NA,NA,NA
7,PK,Dim1,-1.28,NA,NA,NA
8,PK,Dim1,0.95,NA,NA,NA
9,PK,Dim1,-5.96,NA,NA,NA
10,PK,Dim1,-8.81,NA,NA,NA
11,PK,Dim1,-8.46,NA,NA,NA
12,PK,Dim1,-6.15,NA,NA,NA
13,PK,Dim1,-13.98,NA,NA,NA
14,PK,Dim1,-16.43,NA,NA,NA
15,PK,Dim1,-4.09,NA,NA,NA
16,PK,Dim1,-11.06,NA,NA,NA
17,PK,Dim1,-9.04,NA,NA,NA
18,PK,Dim1,-8.56,NA,NA,NA
19,PK,Dim1,-8.13,NA,NA,NA
20,PK,Dim2,-14.46,NA,NA,NA
21,PK,Dim2,-4.21,NA,NA,NA
22,PK,Dim2,-4.96,NA,NA,NA
23,PK,Dim2,-5.48,NA,NA,NA
24,PK,Dim2,-4.53,NA,NA,NA
25,PK,Dim2,6.31,NA,NA,NA
26,PK,Dim2,-11.16,NA,NA,NA
27,PK,Dim2,-1.27,NA,NA,NA
28,PK,Dim2,-11.49,NA,NA,NA
29,PK,Dim2,-0.9,NA,NA,NA
30,PK,Dim2,-12.27,NA,NA,NA
31,PK,Dim2,6.85,NA,NA,NA
32,PK,Dim2,-5.21,NA,NA,NA
33,PK,Dim2,-1.06,NA,NA,NA
34,PK,Dim2,-2.6,NA,NA,NA
35,PK,Dim2,-0.95,NA,NA,NA
36,PK,Dim3,-0.82,NA,NA,NA
37,PK,Dim3,-7.65,NA,NA,NA
38,PK,Dim3,0.64,NA,NA,NA
39,PK,Dim3,-2.25,NA,NA,NA
40,PK,Dim3,-1.58,NA,NA,NA
41,PK,Dim3,-5.73,NA,NA,NA
42,PK,Dim3,0.37,NA,NA,NA
43,PK,Dim3,-5.46,NA,NA,NA
44,PK,Dim3,-3.48,NA,NA,NA
45,PK,Dim3,0.88,NA,NA,NA
46,PK,Dim3,-2.11,NA,NA,NA
47,PK,Dim3,-10.13,NA,NA,NA
48,PK,Dim3,-2.08,NA,NA,NA
49,PK,Dim3,-4.33,NA,NA,NA
50,PK,Dim3,1.09,NA,NA,NA
51,PK,Dim3,-4.23,NA,NA,NA
52,PK,Dim3,-1.46,NA,NA,NA
53,PK,Dim3,9.37,NA,NA,NA
54,PK,Dim3,5.84,NA,NA,NA
55,PK,Dim3,8.21,NA,NA,NA
56,PK,Dim3,7.34,NA,NA,NA
57,PK,Dim4,1.83,NA,NA,NA
58,PK,Dim4,14.39,NA,NA,NA
59,PK,Dim4,22.02,NA,NA,NA
60,PK,Dim4,4.83,NA,NA,NA
61,PK,Dim4,-3.24,NA,NA,NA
62,PK,Dim4,-5.69,NA,NA,NA
63,PK,Dim4,-22.92,NA,NA,NA
64,PK,Dim4,0.41,NA,NA,NA
65,PK,Dim4,-4.42,NA,NA,NA
66,PK,Dim4,-10.72,NA,NA,NA
67,PK,Dim4,-11.29,NA,NA,NA
68,PK,Dim4,-2.89,NA,NA,NA
69,PK,Dim4,-7.59,NA,NA,NA
70,PK,Dim4,-7.45,NA,NA,NA
71,US,Dim1,-12.49,NA,NA,NA
72,US,Dim1,-11.59,NA,NA,NA
73,US,Dim1,-4.6,NA,NA,NA
74,US,Dim1,-22.83,NA,NA,NA
75,US,Dim1,-4.83,NA,NA,NA
76,US,Dim1,-14.76,NA,NA,NA
77,US,Dim1,-15.93,NA,NA,NA
78,US,Dim1,-2.78,NA,NA,NA
79,US,Dim1,-16.39,NA,NA,NA
80,US,Dim1,-15.22,NA,NA,NA
81,US,Dim1,3.25,NA,NA,NA
82,US,Dim1,-2.73,NA,NA,NA
83,US,Dim1,0.96,NA,NA,NA
84,US,Dim1,-1.12,NA,NA,NA
85,US,Dim1,-0.33,NA,NA,NA
86,US,Dim1,-6.45,NA,NA,NA
87,US,Dim1,2.52,NA,NA,NA
88,US,Dim1,3.18,NA,NA,NA
89,US,Dim1,4.65,NA,NA,NA
90,US,Dim2,-1.75,NA,NA,NA
91,US,Dim2,-0.22,NA,NA,NA
92,US,Dim2,8.16,NA,NA,NA
93,US,Dim2,1.89,NA,NA,NA
94,US,Dim2,4.31,NA,NA,NA
95,US,Dim2,-0.41,NA,NA,NA
96,US,Dim2,-23.02,NA,NA,NA
97,US,Dim2,3.87,NA,NA,NA
98,US,Dim2,-4.76,NA,NA,NA
99,US,Dim2,4.95,NA,NA,NA
100,US,Dim2,4.78,NA,NA,NA
101,US,Dim2,-15.11,NA,NA,NA
102,US,Dim2,-3.74,NA,NA,NA
103,US,Dim2,-6.15,NA,NA,NA
104,US,Dim2,-8.33,NA,NA,NA
105,US,Dim2,-5.55,NA,NA,NA
106,US,Dim3,-5.1,NA,NA,NA
107,US,Dim3,-0.41,NA,NA,NA
108,US,Dim3,-8,NA,NA,NA
109,US,Dim3,-11.8,NA,NA,NA
110,US,Dim3,-10.39,NA,NA,NA
111,US,Dim3,-14.98,NA,NA,NA
112,US,Dim3,-13.14,NA,NA,NA
113,US,Dim3,-16.06,NA,NA,NA
114,US,Dim3,-16.75,NA,NA,NA
115,US,Dim3,-17.58,NA,NA,NA
116,US,Dim3,-13.12,NA,NA,NA
117,US,Dim3,-15.69,NA,NA,NA
118,US,Dim3,-9.29,NA,NA,NA
119,US,Dim3,-14.93,NA,NA,NA
120,US,Dim3,-18.75,NA,NA,NA
121,US,Dim3,-16.15,NA,NA,NA
122,US,Dim3,-14.38,NA,NA,NA
123,US,Dim3,-11.33,NA,NA,NA
124,US,Dim3,2.06,NA,NA,NA
125,US,Dim3,1.55,NA,NA,NA
126,US,Dim3,3.17,NA,NA,NA
127,US,Dim4,3.33,NA,NA,NA
128,US,Dim4,-3.31,NA,NA,NA
129,US,Dim4,5.67,NA,NA,NA
130,US,Dim4,-1.94,NA,NA,NA
131,US,Dim4,-4.2,NA,NA,NA
132,US,Dim4,-13.53,NA,NA,NA
133,US,Dim4,-10.84,NA,NA,NA
134,US,Dim4,-1.04,NA,NA,NA
135,US,Dim4,-8.02,NA,NA,NA
136,US,Dim4,-14.65,NA,NA,NA
137,US,Dim4,-6.39,NA,NA,NA
138,US,Dim4,-3.69,NA,NA,NA
139,US,Dim4,-11.62,NA,NA,NA
140,US,Dim4,-3.02,NA,NA,NA
141,US,Dim4,-28.84,NA,NA,NA

我正在尝试创建一个分组的箱形图（使用一个函数），其中平均值显示在每个组的框图中。代码如下：

attach(data_Blogs)    
plotgraph <- function(x, y, colour, min, max){

      plot1 <- ggplot(dims_Blog, aes_string(x = x, y = y, fill = colour)) +
        geom_boxplot()+
        labs(color=colour) +
        #scale_y_continuous(breaks=c(seq(min,max,5)), limits = c(min, max))+
        labs(x="Dimensions", y="Dimension Score") +
        scale_fill_grey(start = 0.3, end = 0.7) + 
        theme_grey()+
        theme(legend.justification = c(1, 1), legend.position = c(1, 1))+
        geom_text(data= melt(with(dims_Blog, tapply(eval(parse(text=y)),list(eval(parse(text=x)),eval(parse(text=colour))), mean)),varnames=c("Dimension","Region"),value.name="med"),
                  aes_string(y = "med",x=x, label = "round(med,3)"),position=position_dodge(width = 0.8),size = 3, vjust = -0.5,colour="white")
      return(plot1)
    }
    plot1 <- plotgraph ("Dimension", "BlogsInd.", "Region")

我无法理解以＆＃34; geom_text＆＃34;开头的部分。将数据传递给平均值的位置。数据框正在融化（从长到宽格式），我认为在这种情况下不需要，因为数据已经是宽格式的。我尝试使用＆＃39; stats_summary＆＃39;功能没有成功。您的帮助将帮助我找到解决方案。

1 个答案:

答案 0 :(得分：0)

确实融化数据似乎是多余的。相反，您应该汇总数据，例如使用dplyr：

library(dplyr)
ggplot(dims_Blog, aes(x=Dimension, y=BlogsInd., fill=Region)) +
  geom_boxplot() +
  geom_text(data = dims_Blog %>% group_by(Dimension, Region) %>% summarise(mean = mean(BlogsInd.)), 
            aes(x = Dimension, y = mean, label = round(mean, 2)), 
            position = position_dodge(width = .7))

然后微调您的定位/格式。

编辑：我没有点击你之前的问题，这个问题已经扩展了上面的例子，以防止编程上下文中出现NSE。因此，请在函数中使用group_by_和aes_string。

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