r - 长格式的时间序列数据，合并特定行时间点，同时忽略每个参与者的其他时间点

问题描述

我正在为以下内容寻找一个 - 最好是整洁的 - 解决方案。我有来自 4 个时间点的长格式纵向数据，有时我感兴趣的变量 ( var1, var2, ...) 在不同时间都有缺失值。我正在寻找一种仅在以下条件下合并每个值t1和t2行的方法：id

对于以开头的 cols var，如果有NAs at t1，则使用它们对应的值 from t2。
同样，如果处有缺失值t2，请尝试用值填充它们t1。
如果两者都是NA，则将它们保留为NA。
如果和有不同的值t1，请保持t2原样。
忽略t3和t4s重视一起

我认为我在group_by,starts_with和summarise函数的组合上走在正确的轨道上，但我无法获得所需的确切输出。这里的其他几个线程是相似的，但没有满足忽略其他时间的特定时间点标准。

示例数据：

df1
# A tibble: 16 x 4
   id    time   var1  var2
   <chr> <chr> <dbl> <dbl>
 1 A1    t1       NA    NA
 2 A1    t2        2     3
 3 A1    t3        2     2
 4 A1    t4        3     2
 5 A2    t1        1     2
 6 A2    t2       NA    NA
 7 A2    t3        2    NA
 8 A2    t4        1     2
 9 A3    t1        2     3
10 A3    t2       NA     1
11 A3    t3       NA    NA
12 A3    t4        2     2
13 A4    t1       NA    NA
14 A4    t2       NA     1
15 A4    t3        1     1
16 A4    t4        1     1

期望的输出

df2
# A tibble: 16 x 4
   id    time   var1  var2
   <chr> <chr> <dbl> <dbl>
 1 A1    t1        2     3
 2 A1    t2        2     3
 3 A1    t3        2     2
 4 A1    t4        3     2
 5 A2    t1        1     2
 6 A2    t2        1     2
 7 A2    t3        2    NA
 8 A2    t4        1     2
 9 A3    t1        2     3
10 A3    t2        2     1
11 A3    t3       NA    NA
12 A3    t4        2     2
13 A4    t1       NA     1
14 A4    t2       NA     1
15 A4    t3        1     1
16 A4    t4        1     1

表示数据集：

df1 <- structure(list(id = c("A1", "A1", "A1", "A1", "A2", "A2", "A2", 
"A2", "A3", "A3", "A3", "A3", "A4", "A4", "A4", "A4"), time = c("t1", 
"t2", "t3", "t4", "t1", "t2", "t3", "t4", "t1", "t2", "t3", "t4", 
"t1", "t2", "t3", "t4"), var1 = c(NA, 2, 2, 3, 1, NA, 2, 1, 2, 
NA, NA, 2, NA, NA, 1, 1), var2 = c(NA, 3, 2, 2, 2, NA, NA, 2, 
3, 1, NA, 2, NA, 1, 1, 1)), class = c("spec_tbl_df", "tbl_df", 
"tbl", "data.frame"), row.names = c(NA, -16L), spec = structure(list(
    cols = list(id = structure(list(), class = c("collector_character", 
    "collector")), time = structure(list(), class = c("collector_character", 
    "collector")), var1 = structure(list(), class = c("collector_double", 
    "collector")), var2 = structure(list(), class = c("collector_double", 
    "collector"))), default = structure(list(), class = c("collector_guess", 
    "collector")), skip = 1), class = "col_spec"))

df2 <- structure(list(id = c("A1", "A1", "A1", "A1", "A2", "A2", "A2", 
"A2", "A3", "A3", "A3", "A3", "A4", "A4", "A4", "A4"), time = c("t1", 
"t2", "t3", "t4", "t1", "t2", "t3", "t4", "t1", "t2", "t3", "t4", 
"t1", "t2", "t3", "t4"), var1 = c(2, 2, 2, 3, 1, 1, 2, 1, 2, 
2, NA, 2, NA, NA, 1, 1), var2 = c(3, 3, 2, 2, 2, 2, NA, 2, 3, 
1, NA, 2, 1, 1, 1, 1)), class = c("spec_tbl_df", "tbl_df", "tbl", 
"data.frame"), row.names = c(NA, -16L), spec = structure(list(
    cols = list(id = structure(list(), class = c("collector_character", 
    "collector")), time = structure(list(), class = c("collector_character", 
    "collector")), var1 = structure(list(), class = c("collector_double", 
    "collector")), var2 = structure(list(), class = c("collector_double", 
    "collector"))), default = structure(list(), class = c("collector_guess", 
    "collector")), skip = 1), class = "col_spec"))

任何帮助将非常感激！

标签： rdplyrtidyverse

bind_rows( df1 %>% group_by(id) %>% filter(time %in% c("t1", "t2")) %>% fill(c("var1", "var2"), .direction = "updown"), df1 %>% filter(time %in% c("t3", "t4")) ) %>% arrange(id, time) %>% ungroup() # A tibble: 16 x 4 id time var1 var2 <chr> <chr> <dbl> <dbl> 1 A1 t1 2 3 2 A1 t2 2 3 3 A1 t3 2 2 4 A1 t4 3 2 5 A2 t1 1 2 6 A2 t2 1 2 7 A2 t3 2 NA 8 A2 t4 1 2 9 A3 t1 2 3 10 A3 t2 2 1 11 A3 t3 NA NA 12 A3 t4 2 2 13 A4 t1 NA 1 14 A4 t2 NA 1 15 A4 t3 1 1 16 A4 t4 1 1

r - 长格式的时间序列数据，合并特定行时间点，同时忽略每个参与者的其他时间点

问题描述

解决方案

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