Geom_point 以及 ggboxplot 和 gg 在 ggplot 中错误地配对了所有绘图点

Question

我正在尝试绘制一些简单的箱形图，但我注意到我在数据框中得到的点只是在 ggplot 中绘制不正确，在所有上述类型的绘图中。

我的数据是

structure(list(rownum = 1:74, Device = c("Dexcom", "Dexcom", 
"Dexcom", "Dexcom", "Dexcom", "Dexcom", "Dexcom", "Dexcom", "Dexcom", 
"Dexcom", "Dexcom", "Dexcom", "Dexcom", "Dexcom", "Dexcom", "Libreview", 
"Libreview", "Libreview", "Libreview", "Libreview", "Libreview", 
"Libreview", "Libreview", "Libreview", "Libreview", "Libreview", 
"Libreview", "Libreview", "Diasend Manual", "Diasend Manual", 
"Diasend Manual", "Diasend Manual", "Diasend Manual", "Diasend Manual", 
"Diasend Manual", "Diasend Manual", "Diasend CGM", "Diasend Manual", 
"Diasend Manual", "Diasend Manual", "Diasend Manual", "Diasend Manual", 
"Diasend CGM", "Diasend CGM", "Diasend Manual", "Diasend Manual", 
"Diasend Manual", "Diasend Manual", "Diasend CGM", "Diasend Manual", 
"Diasend Manual", "Diasend CGM", "Diasend Manual", "Diasend Manual", 
"Diasend Manual", "Diasend Manual", "Diasend Manual", "Diasend CGM", 
"Diasend Manual", "Diasend CGM", "Diasend Manual", "Diasend Manual", 
"Diasend Manual", "Diasend CGM", "Diasend Manual", "Diasend CGM", 
"Diasend Manual", "Diasend Manual", "Diasend Manual", "Diasend Manual", 
"Diasend Manual", "Diasend Manual", "Diasend CGM", "Diasend Manual"
), PREMean = c(10.0484850182022, 7.84715557883709, 7.28766699205132, 
8.47011442894507, 10.7497970736388, 8.6565711351755, 12.2666572965045, 
12.8489327534292, 9.38152123552124, 9.82593283758822, 9.25191807020791, 
10.590004260355, 10.1991015796402, 8.11500023112837, 9.3887371146612, 
9.05289979902383, 16.3938994229184, 11.2269812823576, 8.46589333710567, 
9.45301483336544, 9.654521175124, 9.17169712793734, 5.90663637838715, 
15.1026720647773, 8.73502786461873, 12.515518913676, 10.2021609195402, 
8.88323924469535, 9.138, 10.5977853492334, 14.7827906976744, 
10.9643874643875, 8.04525252525253, 9.2234693877551, 9.2234693877551, 
13.4109826589595, 8.65916169339799, 9.07101449275362, 10.7026923076923, 
17.9097799511002, 6.05655339805825, 7.24913151364764, 7.84826142795985, 
11.6334796926454, 10.0795389048991, 9.63545878693624, 11.7388888888889, 
11.3917218543046, 8.11740335319385, 9.41461318051576, 12.9295681063123, 
10.2035994083164, 7.68975155279503, 10.249885583524, 5.79714285714286, 
10.0638826185102, 8.44704049844237, 10.6952513150205, 9.36492957746479, 
9.83008799318762, 9.6688654353562, 8.00041753653445, 9.26, 9.38389756944444, 
8.55568181818182, 8.63457241816674, 8.12372881355932, 9.84208494208494, 
11.28828125, 9.04013157894737, 11.6740659340659, 9.61797752808989, 
13.8315843798383, 10.1719101123596), POSTMean = c(8.19190208049315, 
7.61158509359437, 7.20120148352596, 8.57923580164976, 10.6268789167925, 
8.37193152150653, 12.3593220150292, 13.9380512091038, 9.30225121492054, 
8.19597861420017, 8.73307014253563, 8.23531795760565, 10.4691064145347, 
8.78835006435006, 9.48096681373489, 9.12521085925145, 13.1253985706432, 
10.2115876974231, 7.65094314018184, 11.1021567021567, 12.3527429320352, 
8.74159058145123, 6.82408707865169, 9.2207729468599, 8.33679846938776, 
11.2045885361817, 12.2492643845594, 8.41001977587343, 8.24191419141914, 
10.7707317073171, 12.2390334572491, 8.28022598870056, 7.67814207650273, 
9.48614130434783, 9.48614130434783, 11.0455128205128, 8.36162310181728, 
10.2825581395349, 10.1807407407407, 16.3283333333333, 7.56851851851852, 
6.80612244897959, 7.6510029661656, 12.1434984833165, 12.2157894736842, 
11.2797101449275, 19.1619047619048, 13.2472361809045, 8.87069342340552, 
8.40763888888889, 13.5286956521739, 10.4632632632633, 8.76877470355731, 
10.6271903323263, 8.2667701863354, 8.61640378548896, 6.96209386281588, 
8.29738799201886, 8.51794871794872, 8.10574666733237, 8.43217993079585, 
7.7244635193133, 13.9224137931034, 9.19426699426699, 8.15335753176044, 
8.30695218383485, 5.89611231101512, 9.45526315789474, 9.406875, 
9.78860759493671, 9.33200934579439, 9.406875, 11.2342145015106, 
11.2984126984127)), row.names = c(NA, -74L), na.action = structure(c(`19` = 19L, 
`30` = 30L, `38` = 38L, `39` = 39L, `42` = 42L, `44` = 44L, `51` = 51L, 
`62` = 62L, `79` = 79L, `84` = 84L), class = "omit"), class = c("tbl_df", 
"tbl", "data.frame"))

然后

ggplot(data, aes(x=PREMean, y=POSTMean)) + geom_point()

绘制一些明显太低的点 - 小于 5。None 个数字小于 5。

使用 ggboxplot 和 ggpaired 绘图也给我的分数太低了。

我正在撕扯我的头发，我只是不明白为什么这些点明显绘制不正确？请帮忙，谢谢。

Answer 1

正如@RichardTelford 所述，您的情节符合预期。

我已将两个图都添加到答案中以展示 ggplot's 默认坐标轴比例和用户定义比例之间的区别。

ggplot 不知道您将如何解释坐标轴：它只是获取每个坐标轴的最小值和最大值并将它们拟合到可用的 space 并尽其所能标记刻度线. ggplot 依赖于 reader 进行锻炼，在默认版本使用 data 的情况下，x 轴上的次要网格线代表 2.5，因此 x 原点略大于 5。

如果您想明确轴值和中断，您必须告诉 ggplot 打印什么。您有很大的灵活性：您可以设置限制、中断和比例...

如果您想要一对特定的极限和一系列图表的突破，那么您最好创建一个函数来为您完成这项工作；那是另一个问题的主题；你可以看看这个答案，它将比例设置为从 0 到数据的限制：Setting y axis breaks in ggplot


library(ggplot2)
library(patchwork)

p1 <- ggplot(data, aes(x=PREMean, y=POSTMean)) +
  geom_point()+
  ggtitle("Default axis scales")


p2 <- ggplot(data, aes(x=PREMean, y=POSTMean)) +
  geom_point()+
  scale_x_continuous(limits = c(0,20))+
  scale_y_continuous(limits = c(0,20))+
  ggtitle("Defined axis scales")


p1/p2

^{由 reprex package (v0.3.0)}

于 2020-06-27 创建

Geom_point 以及 ggboxplot 和 gg 在 ggplot 中错误地配对了所有绘图点

Geom_point and ggboxplot and ggpaired all plotting points incorrectly in ggplot

plot

r

ggplot2

pairing