访问 R 中嵌套列表中具有特定名称的所有列

Question

我想知道如何访问嵌套列表中具有特定名称的所有列。下面有一个可重现的例子。如何调用所有“平均”列并将所有列整理到单个 data.frame 中，其中 data.frame 作为另外两个指定关联类和 Output1/Output2 的列（示例 1）。示例 2 稍微复杂一点，其中嵌套的“均值”列表是一个 data.frame。我需要同时访问“ts”和“value”列。也就是说，我需要知道每个值对应的ts（除了classes和Output1/Output2）。

示例 1

classes <- c("F", "G", "M", "O")
classes <- structure(unique(classes), names = unique(classes))

S1 = data.frame(X1 = rnorm(100), X2 = rnorm(100), X3 = rnorm(100),  X4 = rep(classes, 25))
S2 = data.frame(X1 = rnorm(100), X2 = rnorm(100), X3 = rnorm(100),  X4 = rep(classes, 25))

P <- lapply(classes, function(c){
  Output1 <- list ("model" = lm(X3~ X1+X2, data = S1),"mean" = apply(S1[S1$X4 == c, 1:3], 2, mean), "sum" = apply(S1[S1$X4 == c, 1:3], 2, sum))
  Output2 <- list ("model" = lm(X3~ X1+X2, data = S2), "mean" = apply(S2[S2$X4 == c, 1:3], 2, mean), "sum" = apply(S2[S2$X4 == c, 1:3], 2, sum))
  output <- list ("Output1" = Output1, "Output2" = Output2)
  return(output)
})

示例 2

classes <- c("F", "G", "M", "O")
classes <- structure(unique(classes), names = unique(classes))

S1 = data.frame( X1 = rnorm(100), X2 = rnorm(100), X3 = rnorm(100),  X4 = rep(classes, 25), ts = seq(from = ISOdate(1910,1,1),  by = "30 min", length.out = 100 ))
S2 = data.frame( X1 = rnorm(100), X2 = rnorm(100), X3 = rnorm(100),  X4 = rep(classes, 25),ts = seq(from = ISOdate(1910,1,1),  by = "30 min", length.out = 100 ))

P <- lapply(classes, function(c){
  Output1 <- list ("model" = lm(X3~ X1+X2, data = S1),"mean" = data.frame(ts = S1[S1$X4 == c, "ts"], 
                                                                          value = S1[S1$X4 == c, "X1"]) ,
                   "sum" = apply(S1[S1$X4 == c, 1:3], 2, sum))
  Output2 <- list ("model" = lm(X3~ X1+X2, data = S2),
                   "mean" = data.frame(ts = S2[S2$X4 == c, "ts"],
                                       value = S2[S2$X4 == c, "X1"]), 
                   "sum" = apply(S2[S2$X4 == c, 1:3], 2, sum))
  output <- list ("Output1" = Output1, "Output2" = Output2)
  return(output)
})

Answer 1

我们可以使用rvest 的pluck 从P 获取“平均”列，并将它们与map_df 绑定在一起。

purrr::map_df(P, ~rvest::pluck(.x, "mean"), .id = "Class")

# A tibble: 12 x 3
#   Class Output1 Output2
#   <chr>   <dbl>   <dbl>
# 1 F      0.0315 -0.0946
# 2 F      0.0935  0.219 
# 3 F      0.155   0.172 
# 4 G      0.123   0.182 
# 5 G     -0.114  -0.128 
# 6 G     -0.0654 -0.0990
# 7 M      0.111   0.0794
# 8 M     -0.176   0.405 
# 9 M      0.265  -0.0747
#10 O      0.0207 -0.250 
#11 O     -0.0407  0.0117
#12 O     -0.162  -0.195 

在base R中，你可以这样做：

temp <- lapply(P, function(x) sapply(x, `[[`, "mean"))
do.call(rbind, Map(cbind.data.frame, temp, Class = names(temp)))

---

编辑

对于数据框示例，我们可以在pluck 之后使用bind_rows。

map_df(P, ~rvest::pluck(.x, "mean") %>% bind_rows(.id= "output"), .id = "Class")