具有多个因子的分组（因子）数据。错误：大小不兼容 (0)，期望 1（组大小）或 1

这篇文章是后续根据“几个因素”斜率更改 ggplot 中的线条颜色 https://stackoverflow.com/questions/39023962/changing-line-color-in-ggplot-based-on-several-factors-slope/39025244#39025244

我想按“PQ”对数据（如下）进行分组，但是出现以下错误：

“不兼容的大小 (0)，期望 1（组大小）或 1”

Data

ID<-c("A_P1","A_P1","A_P1","A_P1","A_P1","A_P2","A_P2","A_P2","A_P2","A_P2","A_P2","B_P1","B_P1","B_P1","B_P1","B_P1","B_P1","B_P1","B_P1","B_P2","B_P2","B_P2","B_P2","B_P2","B_P2","B_P2","B_P2")
Q<-c("C1","C1","C2","C3","C3","C1","C1","C2","C2","C3","C3","Q1","Q1","Q1","Q1","Q3","Q3","Q4","Q4","Q1","Q1","Q1","Q1","Q3","Q3","Q4","Q4")
PQ<-c("A_P1C1","A_P1C1","A_P1C2","A_P1C3","A_P1C3","A_P2C1","A_P2C1","A_P2C2","A_P2C2","A_P2C3","A_P2C3","B_P1Q1","B_P1Q1","B_P1Q1","B_P1Q1","B_P1Q3","B_P1Q3","B_P1Q4","B_P1Q4","B_P2Q1","B_P2Q1","B_P2Q1","B_P2Q1","B_P2Q3","B_P2Q3","B_P2Q4","B_P2Q4")
AS<-c("CF","CF","CF","CF","CF","CTF","CTF","CTF","CTF","CTF","CTF","CTF","CTF","CTF","CTF","CTF","CTF","CTF","CTF","CTF","CTF","CTF","CTF","CTF","CTF","CTF","CTF")
N<-c("N2","N3","N3","N2","N3","N2","N3","N2","N3","N2","N3","N0","N1","N2","N3","N1","N3","N0","N1","N0","N1","N2","N3","N1","N3","N0","N1")
Value<-c(4.7,8.61,8.34,5.89,8.36,1.76,2.4,5.01,2.12,1.88,3.01,2.4,7.28,4.34,5.39,11.61,10.14,3.02,9.45,8.8,7.4,6.93,8.44,7.37,7.81,6.74,8.5)

df<-data.frame(ID=ID,Q=Q,PQ=PQ,AS=AS,N=N,Value=Value)

产生错误的代码

#calculate slopes for N0 and N1
    df %>% 
      filter(N=="N0" | N=="N1") %>%
      group_by(PQ) %>%
      # use diff to calculate slope
      mutate(slope = diff(Value)) -> dat01

#calculate slopes for N0 and N2
    df %>% 
      filter(N=="N0" | N=="N2") %>%
      group_by(PQ) %>%
      # use diff to calculate slope
      mutate(slope = diff(Value)) -> dat02

此外，我想计算其余“PQ”因子（如果存在）的斜率，即 N0-N3;N1-N2 ...等等

该错误是由于输出的长度差异造成的diff相对于原始数据集。它返回比原始数据少一个元素。因此附加 0 或 NA 即可解决问题

df %>% 
   filter(N=="N0" | N=="N1") %>%
   group_by(PQ) %>% 
   mutate(slope = c(0, diff(Value)))

为了使其紧凑，而不是==， 我们可以用%in%当有多个元素时

df %>%
   filter(N %in%  paste0("N", 0:1)) %>%
   group_by(PQ) %>%
   mutate(slope = c(0, diff(Value)))

关于第二个问题，对于“N”中的所有组合执行此操作，请使用combn on the unique'N' 的元素，filter根据组合值的“N”，按“PQ”分组后，计算diff的“价值”。输出将是list正如我们指定的simplify = FALSE.

combn(as.character(unique(df$N)),2, FUN = function(x) df %>% 
            filter(N %in% x) %>% 
            group_by(PQ) %>%
            mutate(slope = c(0, diff(Value))), simplify = FALSE )