R - 绘制来自 r 中数据帧中可用的连续行对的数据对

Question

我有一个包含多个人的时间序列数据的数据框。数据包括每个个体随时间变化的动物表面间隔和潜水间隔。对于每个表面间隔，我想使用 ggplot 来绘制表面间隔的持续时间与前一次可用潜水的持续时间。如果连续有两个表面间隔，我想忽略它们，只绘制直接在它们之前有潜水的表面。我想按个人 ID 执行此操作。 我在下面提供了一些示例数据：

我更喜欢为个人使用 dplyr 包 group_by() 函数，但不确定如何选择每次潜水并将其与以下（后续）表面配对。

df <- data.frame(ID=c("A","A","A","A","A","A","A","A","A","B","B","B","B","B","B","B","B","B"), 
What=c("Dive", "Surface", "Dive","Surface","Dive", "Surface", "Surface", "Dive", "Surface", "Dive", "Surface", "Dive", "Dive", "Surface", "Dive", "Surface", "Dive", "Surface"), 
Start=c("2010-05-09 17:29:45", "2010-05-09 17:56:24", "2010-05-09 18:22:15", "2010-05-09 18:52:38", "2010-05-09 18:59:02", "2010-05-09 19:24:37","2010-05-09 19:30:00", "2010-05-09 19:30:57", "2010-05-09 19:48:00","2010-05-03 18:49:35", "2010-05-03 18:58:00", "2010-05-03 19:27:51","2010-05-03 19:35:42", "2010-05-03 20:15:41", "2010-05-03 20:24:13","2010-05-03 20:53:32", "2010-05-03 21:01:31", "2010-05-03 21:40:26"), 
End=c("2010-05-09 17:56:24", "2010-05-09 18:22:15", "2010-05-09 18:52:38","2010-05-09 18:59:02", "2010-05-09 19:24:37", "2010-05-09 19:29:28","2010-05-09 19:30:57", "2010-05-09 19:48:00", "2010-05-09 19:49:02", "2010-05-03 18:58:06", "2010-05-03 19:27:51", "2010-05-03 19:35:42", "2010-05-03 20:15:41", "2010-05-03 20:24:13", "2010-05-03 20:53:32", "2010-05-03 21:01:31", "2010-05-03 21:40:26", "2010-05-03 21:48:44"), 
Duration = c(26.65, 25.85, 30.38,  6.40, 25.58,  4.85,  0.95, 17.05, 1.03,  8.52, 29.85,  7.85, 39.98,  8.53, 29.32,  7.98, 38.92,  8.30))

df$Start<-as.POSIXct(df$Start, format = "%Y-%m-%d %H:%M:%S")
df$End<-as.POSIXct(df$End, format = "%Y-%m-%d %H:%M:%S")

我想制作一个 ggplot，x 轴为表面持续时间，y 轴为前一个潜水持续时间。如果连续进行两次潜水，则忽略第一次，将第二次与下一个表面相匹配；多个曲面也是如此；我只想选择在它们之前有潜水的表面。

任何帮助将不胜感激！

Answer 1

我不能 100% 确定您要做什么，但如果我理解正确...我们可以进行一些操作来获得一个八行数据框，其中每个数据框都有四个潜水面对两个人：

df2 <- 
  df %>% 
  group_by(ID) %>% 
  filter(What != lead(What) | is.na(lead(What))) %>% 
  select(ID, What, Duration) %>% 
  mutate(dive_number = ceiling(row_number() / 2)) %>% 
  ungroup() %>% 
  spread(What, Duration)

# A tibble: 8 x 4
  ID    dive_number  Dive Surface
  <fct>       <dbl> <dbl>   <dbl>
1 A               1 26.6    25.8 
2 A               2 30.4     6.4 
3 A               3 25.6     0.95
4 A               4 17.0     1.03
5 B               1  8.52   29.8 
6 B               2 40.0     8.53
7 B               3 29.3     7.98
8 B               4 38.9     8.3 

然后你可以绘制结果：

df2 %>% 
  ggplot(aes(x = Surface, y = Dive, color = ID)) +
  geom_point()