Question

首先，这是我的数据框：

> df.combined
      MLSupr   MLSpred    MLSlwr    BPLupr    BPLpred     BPLlwr
1   1.681572  1.392213  1.102854  1.046068  0.8326201  0.6191719
2   3.363144  2.784426  2.205708  2.112885  1.6988250  1.2847654
3   5.146645  4.232796  3.318946  3.201504  2.5999694  1.9984346
4   6.930146  5.681165  4.432184  4.368555  3.6146180  2.8606811
5   8.713648  7.129535  5.545422  5.480557  4.5521112  3.6236659
6  10.497149  8.577904  6.658660  6.592558  5.4896044  4.3866506
7  12.280651 10.026274  7.771898  7.681178  6.3907488  5.1003198
8  14.064152 11.474644  8.885136  8.924067  7.4889026  6.0537381
9  15.847653 12.923013  9.998373 10.125539  8.5444783  6.9634176
10 17.740388 14.429805 11.119222 11.327011  9.6000541  7.8730970
11 19.633122 15.936596 12.240071 12.620001 10.7425033  8.8650055
12 21.525857 17.443388 13.360919 13.821473 11.7980790  9.7746850
13 23.535127 19.010958 14.486789 15.064362 12.8962328 10.7281032
14 25.544397 20.578528 15.612659 16.307252 13.9943865 11.6815215
15 27.553667 22.146098 16.738529 17.600241 15.1368357 12.6734300
16 29.562937 23.713668 17.864399 18.893231 16.2792849 13.6653384
17 31.572207 25.281238 18.990268 20.245938 17.4678163 14.6896948
18 33.581477 26.848807 20.116138 21.538928 18.6102655 15.6816033
19 35.590747 28.416377 21.242008 22.891634 19.7987969 16.7059597
20 37.723961 30.047177 22.370394 24.313671 21.0352693 17.7568676

因此，正如您所看到的，我预测了它们的95％CI的上限和下限。我想在同一块情节中为MLS和BPL绘制线条及其色带，但我不太确定如何。现在，对于单个数据集，我使用此命令：

ggplot(BULISeason, aes(x = 1:length(BULISeason$`Running fit`), y = `Running fit`)) + 
  geom_line(aes(fill = "black")) +
  geom_ribbon(aes(ymin = `Running lwr`, ymax = `Running upr`, fill = "red"),alpha = 0.25)

注意：独立数据框的变量不同。

Answer 1

当然，您可以将您的情节构建为一系列图层，就像您在问题中所暗示的那样。为此，您可以使用以下代码：

ggplot(data = df.combined) +
geom_ribbon(aes(x = x, ymin = MLSlwr, ymax = MLSupr), 
            fill = "blue", alpha = 0.25) +
geom_line(aes(x = x, y = MLSpred), color = "black") +
geom_ribbon(aes(x = x, ymin = BPLlwr, ymax = BPLupr), 
            fill = "red", alpha = 0.25) +
geom_line(aes(x = x, y = BPLpred), color = "black")

并获得以下内容：

但是，将数据集重新转换为"tidy"或长格式有一些优点。例如，您可以将预测的原点映射为颜色，并将预测类型映射到结果图中的线型：

您可以使用以下代码实现此目的：

library(tidyr)

tidy.data  <- df.combined %>% 
  # add id variable
  mutate(x = 1:20) %>% 
  # reshape to long format
  gather("variable", "value", 1:6) %>% 
  # separate variable names at position 3
  separate(variable, 
           into = c("model", "line"), 
           sep = 3, 
           remove = TRUE)

# plot
ggplot(data = tidy.data, aes(x        = x, 
                             y        = value, 
                             linetype = line, 
                             color    = model)) + 
  geom_line() + 
  scale_linetype_manual(values = c("dashed", "solid", "dashed"))

您仍然可以通过将数据帧扩展回宽（r）格式来在绘图中使用色带：

# back to wide
wide.data <- tidy.data %>% 
  spread(line, value)

# plot with ribbon
ggplot(data = wide.data, aes(x = x, y = pred)) +
  geom_ribbon(aes(ymin = lwr, ymax = upr, fill = model), alpha = .5) +
  geom_line(aes(group = model))

希望这有帮助！

无法在同一个GG图上绘制多个数据集及其置信区间。包括数据框架

1 个答案: