英文:
Plotly showing NA for values in hover over
问题
我正在尝试将ggplot2图形转换为plotly图形，似乎工作正常，但悬停时显示Tumor_Volume变量的值为NA。它还显示组变量两次：悬停截图。
library(ggplot2)library(plotly)mouse_data$Mouse <- as.factor(mouse_data$Mouse)mouse_data$Group <- as.factor(mouse_data$Group)p <- ggplot(mouse_data, aes(x=Day, y=Tumor_Volume, color=Group,)) +stat_summary(aes(group=Group), fun=mean, geom="line", size=1) +stat_summary(aes(group=Group), fun=mean, geom="point", size=2) +stat_summary(fun.data = mean_se, geom='errorbar', width=.5, size=0.7) +theme_classic()pggplotly(p)
不确定如何修复这个问题，有任何帮助吗？
EDIT：由于我忘记提供样本数据，请求样本数据的代码如下：
Mouse <- c(1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4)Group <- c('A','A','A','B','B','B','A','A','A','B','B','B')Day <- c(1, 3, 5, 1, 3, 5, 1, 3, 5, 1, 3, 5)Tumor_Volume <- c(1, 1.0829917, 1.2260616, 1, 1.1432288, 1.3644288,1, 1.0551514, 1.3203255, 1, 1.3336704, 1.5578587)Weight <- c(0, -1, -1, 0, 0, 1, 0, 0, 0, 0, 0, -1)mouse_data <- data.frame(Mouse, Group, Day, Tumor_Volume)
Mouse是老鼠编号，总共有四只老鼠，有重复的测量值
Group是组变量，有两个组：A和B
Tumor_Volume是肿瘤体积，以1.00作为基线进行转换
Weight是标准化的体重值，以第1天为0，然后查看后续天数的体重变化
EDIT2：dput(mouse_data) 输出如下：（此部分文本太长，无法全部显示，请使用代码示例中的数据代替。）
英文:
I"m trying to convert a ggplot2 graph into a plotly graph, which seems to be working fine however the hover-over shows the values for the Tumor_Volume variable as NA. It also shows the group variable twice: Screenshot of hover-over.
library(ggplot2)library(plotly)mouse_data$Mouse <- as.factor(mouse_data$Mouse)mouse_data$Group <- as.factor(mouse_data$Group)p <- ggplot(mouse_data, aes(x=Day, y=Tumor_Volume, color=Group,)) +stat_summary(aes(group=Group), fun=mean, geom="line", size=1) +stat_summary(aes(group=Group), fun=mean, geom="point", size=2) +stat_summary(fun.data = mean_se, geom='errorbar', width=.5, size=0.7) +theme_classic()pggplotly(p)
Not sure how to fix this, any help?
EDIT: Sample data requested due to me forgetting, apologies
Mouse <- c(1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4)Group <- c('A','A','A','B','B','B','A','A','A','B','B','B')Day <- c(1, 3, 5, 1, 3, 5, 1, 3, 5, 1, 3, 5)Tumor_Volume <- c(1, 1.0829917, 1.2260616, 1, 1.1432288, 1.3644288,1, 1.0551514, 1.3203255, 1, 1.3336704, 1.5578587)Weight <- c(0, -1, -1, 0, 0, 1, 0, 0, 0, 0, 0, -1)mouse_data <- data.frame(Mouse, Group, Day, Tumor_Volume)
mouse is mouse number, four mice total with repeated measures
group is the group variable, two groups; A and B
tumor_volume tumor volume transformed with 1.00 as baseline
weight normalized weight values with day 1 at 0 and then looking at delta in weight for further days
EDIT2: dput(mouse_data) output:
structure(list(Mouse = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 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, 4L, 4L, 4L, 4L, 4L, 4L, 4L,4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L), levels = c("1", "2", "3","4", "5", "6"), class = "factor"), Group = 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, 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, 1L, 1L, 1L, 1L, 1L, 1L,1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), levels = c("Ionis-2","PBS"), class = "factor"), Day = c(1, 3, 5, 7, 9, 11, 13, 15,17, 19, 21, 23, 25, 27, 29, 31, 1, 3, 5, 7, 9, 11, 13, 15, 17,19, 21, 23, 25, 27, 29, 31, 1, 3, 5, 7, 9, 11, 13, 15, 17, 19,21, 23, 25, 27, 29, 31, 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21,23, 25, 27, 29, 31, 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23,25, 27, 29, 31, 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25,27, 29, 31), Tumor_Volume = c(1, 1.08299168, 1.22606163, 1.28005149,1.15473202, 1.77751867, 1.7775596, 1.42810373, 1.49398489, 1.73608742,1.9960584, 2.41555584, 2.44329879, 2.83244784, 2.95047186, 3.13712572,1, 1.14322875, 1.36442879, 1.62265073, 1.41229115, 1.69515171,1.85693702, 2.00477197, 2.45190977, 2.81710137, 2.95579987, 3.24677192,3.7952463, 4.672606, 4.65405432, 5.04395284, 1, 1.08678546, 1.4051892,1.70719996, 1.91914965, 2.77444381, 2.91922649, 3.12429506, 3.08423878,3.1993417, 3.79480258, 3.45039433, 3.97340486, 4.40332097, 4.99459949,5.19001667, 1, 1.05515139, 1.32032553, 1.31451857, 1.36498317,1.48691696, 1.71555664, 1.69085447, 1.40778153, 1.16562843, 1.43153217,1.14711724, 1.00752507, 0.93548112, 0.89387479, 0.5831787, 1,1.33367041, 1.55785873, 1.97875617, 2.58821435, 2.66654602, 3.64662179,3.06141446, 2.84366305, 2.56583405, 2.74313995, 2.31355113, 2.2229406,2.18822338, 1.80662598, 1.59483541, 1, 1.59580807, 1.92068763,2.1997625, 2.03248152, 2.45503449, 2.5517737, 2.57760473, 2.40887638,3.15143769, 3.01258129, 2.79074441, 2.5628939, 2.86507289, 2.76465271,2.45859679), Weight = c(0, -1, -1, -1, -1, -2, -1, -1, -2, -1,-1, -2, -2, -2, -2, -2, 0, 0, 1, 1, 0, 0, 0, 0, -1, -2, -1, -1,-1, -2, -2, -1, 0, 0, 0, 0, 0, -1, -1, -1, 0, -1, -1, -1, -1,-1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 3, 3, 3, 2, 2, 2, 0,0, 0, 0, 0, -1, -1, 1, 0, 1, 3, 3, 2, 3, 3, 3, 0, -1, 0, 0, 0,0, 0, 0, 0, 0, 1, 1, 1, 2, 1, 1)), row.names = c(NA, -96L), class = c("tbl_df","tbl", "data.frame"))
答案1
得分: 0
`stat_summary`在内部计算汇总信息，所以在这种情况下（因为您正在使用`ggplotly(p)`并且想要显示汇总信息），我建议在绘图之前明确汇总，然后使用`geom_line`和`geom_point`代替`stat_summary`：
library(dplyr)
mouse_plot <- mouse_data %>%
summarize(TV_mean = mean(Tumor_Volume),
.by = c(Day, Group))
或者对于较旧版本的dplyr：
mouse_plot <- mouse_data %>%
group_by(Day, Group) %>%
summarize(TV_mean = mean(Tumor_Volume))
p <- ggplot(mouse_plot, aes(x = Day, y = TV_mean, color = Group)) +
geom_line(size = 1) +
geom_point(size = 2) +
theme_classic()
ggplotly(p)
或者不创建新数据集：
p <- mouse_data %>%
summarize(Tumor_Volume = mean(Tumor_Volume),
.by = c(Day, Group)) %>%
ggplot(aes(x=Day, y=Tumor_Volume, color=Group)) +
geom_line(size = 1) +
geom_point(size = 2) +
theme_classic()
ggplotly(p)
无论哪种方式，都可以获得以下结果：[![enter image description here][1]][1]
英文:
stat_summary internally computes aggregates, so in this case (since you are using ggplotly(p) and want to show the aggregates) I would suggest explicitly summarizing before plotting, then using geom_line and geom_point instead of stat_summary:
library(dplyr)mouse_plot <- mouse_data %>%summarize(TV_mean = mean(Tumor_Volume),.by = c(Day, Group))## or for older versions of dplyr:mouse_plot <- mouse_data %>%group_by(Day, Group) %>%summarize(TV_mean = mean(Tumor_Volume))p <- ggplot(mouse_plot, aes(x = Day, y = TV_mean, color = Group)) +geom_line(size = 1) +geom_point(size = 2) +theme_classic()ggplotly(p)
Or without creating a new dataset:
p <- mouse_data %>%summarize(Tumor_Volume = mean(Tumor_Volume),.by = c(Day, Group)) %>%ggplot(aes(x=Day, y=Tumor_Volume, color=Group)) +geom_line(size = 1) +geom_point(size = 2) +theme_classic()ggplotly(p)
Either way you get:
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