如何将整齐的分层数据框转换为R中的分层列表网格？
这是前一个问题的一个更复杂的版本，我已经抽取了实际问题太多以应用答案。 R将整齐的分层数据帧转换为分层列表
我已经使用for循环将具有两个分组级别的分层数据帧转换为分层列表网格。
是否有更高效的R，Tidyverse或其他方法来实现这一目标？
在真实数据集中：
规则
第1组和第2组标题为描述列第1组标题仅出现一次，第2组标题为第1组标题的子项，只有在有第2组标题时才会更改说明是第2组标题的子项
由此
g1 g2 desc var1 var2 var3
A a d1 KS3 0.0500 2 PLs
A a d2 CTI 0.0500 9 7O0
A b d3 b8x 0.580 5 he2
A b d4 XOf 0.180 12 XJE
A b d5 ygn 0.900 11 v48
A c d6 dGY 0.770 6 UcH
A d d7 jpG 0.600 4 P5M
B d d8 Z95 0.600 10 j6O
对此
desc var1 var2 var3
A
a
d1 KS3 0.0500 2 PLs
d2 CTI 0.0500 9 7O0
b
d3 b8x 0.580 5 he2
d4 XOf 0.180 12 XJE
d5 ygn 0.900 11 v48
c
d6 dGY 0.770 6 UcH
d
d7 jpG 0.600 4 P5M
B
d
码
library(tidyverse)
library(stringi)
set.seed(2018)
tib <- tibble(g1 = c("A", "A", "A", "A", "A", "A", "A", "B", "B", "B", "B", "C"),
g2 = c("a", "a", "b", "b", "b", "c", "d", "d", "b", "b", "e", "e"),
desc = paste0("d", 1:12, " ", stri_rand_strings(12, 3)),
var1 = round(runif(12), 2),
var2 = sample.int(12),
var3 = stri_rand_strings(12, 3))
tib
# Number of rows in final table
n_rows <- length(unique(tib$g1)) + length(unique(paste0(tib$g1, tib$g2))) + nrow(tib)
# create empty output tibble
output <-
as_tibble(matrix(nrow = n_rows, ncol = ncol(tib)-1)) %>%
rename(id = V1, desc = V2, var1 = V3, var2 = V4, var3 = V5) %>%
mutate(id = NA_character_,
desc = NA_character_,
var1 = NA_real_,
var2 = NA_integer_,
var3 = NA_character_)
# Loop counters
level_1 <- 0
level_2 <- 0
output_row <- 1
for(i in seq_len(nrow(tib))){
# level 1 headings
if(tib$g1[[i]] != level_1) {
output$id[[output_row]] <- "g1"
output$desc[[output_row]] <- tib$g1[[i]]
output_row <- output_row + 1
}
# level 2 headings
if(paste0(tib$g1[[i]], tib$g2[[i]]) != paste0(level_1, level_2)) {
output$id[[output_row]] <- "g2"
output$desc[[output_row]] <- tib$g2[[i]]
output_row <- output_row + 1
}
level_1 <- tib$g1[[i]]
level_2 <- tib$g2[[i]]
# Description and data grid
output$desc[[output_row]] <- tib$desc[[i]]
output$var1[[output_row]] <- tib$var1[[i]]
output$var2[[output_row]] <- tib$var2[[i]]
output$var3[[output_row]] <- tib$var3[[i]]
output_row <- output_row + 1
}
output
调整tyluRp R的答案将整齐的分层数据框转换为层次列表我已经选择了一个解决方案。
library(tidyverse)
library(stringi)
set.seed(2018)
tib <- tibble(g1 = c("A", "A", "A", "A", "A", "A", "A", "B", "B", "B", "B", "C"),
g2 = c("a", "a", "b", "b", "b", "c", "d", "d", "b", "b", "e", "e"),
desc = paste0("d", 1:12, " ", stri_rand_strings(12, 3)),
var1 = round(runif(12), 2),
var2 = sample.int(12),
var3 = stri_rand_strings(12, 3))
# add unique identifier for description and variable rows
tib <-
tib %>%
rowid_to_column() %>%
mutate(rowid = paste0("z_", rowid))
# separate tibble for variables associated with descriptions
tib_var <-
tib %>%
select(rowid, var1, var2, var3)
# code adapted from tyluRp to reorder the data and add description variables
tib <-
tib %>%
select(g1, g2, desc, rowid) %>%
mutate(g2 = paste(g1, g2, sep = "_")) %>%
transpose() %>%
unlist() %>%
stack() %>%
distinct(values, ind) %>%
mutate(detect_var = str_detect(values, "^z_"),
ind = lead(case_when(detect_var == TRUE ~ values)),
values = case_when(detect_var == TRUE ~ NA_character_,
TRUE ~ values))%>%
drop_na(values) %>%
select(values, ind) %>%
mutate(values = str_remove(values, "D_")) %>%
left_join(tib_var, by = c("ind" = "rowid")) %>%
select(-ind) %>%
replace_na(list(var1 = "", var2 = "", var3 = ""))
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