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我有一个数据框...

df <- tibble(
  id = 1:10, 
  family = c("a","a","b","b","c", "d", "e", "f", "g", "h"),
  col1_a = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),
  col1_b = c(1, 2, 3, 4, NA, NA, NA, NA, NA, NA),
  col2_a = c(11, 12, 13, 14, 15, 16, 17, 18, 19, 20),
  col2_b = c(11, 12, 13, 14, NA, NA, NA, NA, NA, NA),
  )

家庭最多只能包含 2 个成员（因此他们是个人或成对）。

对于个人（只有一行的家庭，即 id = 5:10），我想将 50% 的数据从以“a”结尾的列随机移动到以“b”结尾的列。

最后，数据应如下所示（取决于使用了 50% 的行）...

df <- tibble(
  id = 1:10, 
  family = c("a","a","b","b","c", "d", "e", "f", "g", "h"),
  col1_a = c(1, 2, 3, 4, 5, NA, 7, NA, 9, NA),
  col1_b = c(1, 2, 3, 4, NA, 6, NA, 8, NA, 10),
  col2_a = c(11, 12, 13, 14, NA, NA, 17, 18, NA, 20),
  col2_b = c(11, 12, 13, 14, 15, 16, NA, NA, 19, NA),
  )

我希望能够通过 group_by 和 mutate 的组合来做到这一点，因为我主要使用 Tidyverse。

更新：我忘了提到以“a”结尾的列中的值如果移至“b”，则应替换为 NA。

4

1 回答 1

0

我将通过两个主要步骤来完成此操作，首先创建fam_count列以确定哪些家庭只有 1 人。然后，创建两rand列，以确定我们是否使用b列中的值。

library(tidyverse)
set.seed(1)

df %>% group_by(family) %>% 
  mutate(fam_count = n()) %>% 
  ungroup() %>% 
  mutate(
    rand1 = sample(c(NA, 1), nrow(.), replace = TRUE),
    rand2 = sample(c(NA, 1), nrow(.), replace = TRUE),
    col1_b = ifelse(fam_count == 1, rand1 * col1_a, col1_b),
    col2_b = ifelse(fam_count == 1, rand2 * col2_a, col2_b)
  ) %>%
  mutate(
    col1_a = ifelse(fam_count == 1 & !is.na(col1_b), NA, col1_a),
    col2_a = ifelse(fam_count == 1 & !is.na(col2_b), NA, col2_a)
  ) %>%
  select(-rand1, -rand2, - fam_count)

# A tibble: 10 x 6
      id family col1_a col1_b col2_a col2_b
   <int> <chr>   <int>  <dbl>  <int>  <dbl>
 1     1 a           1      1     11     11
 2     2 a           2      2     12     12
 3     3 b           3      3     13     13
 4     4 b           4      4     14     14
 5     5 c           5     NA     NA     15
 6     6 d           6     NA     NA     16
 7     7 e          NA      7     17     NA
 8     8 f           8     NA     NA     18
 9     9 g          NA      9     19     NA
10    10 h          10     NA     20     NA
于 2020-05-29T16:18:06.570 回答