r - 创建事件的累积计数并保留每个事件前后的第一年

Question

我有一个纵向数据集，其中包含个人以及有关他们当前居住地的信息。下面的代码创建了一个示例 df:

set.seed(123)
df <- tibble(
  id = c(1, 2, 3, 4, 5,     
         1, 2, 3, 5, 6, 7,  
         2, 3, 4, 6, 7, 8,  
         1, 2, 3, 4, 6, 7, 8   
         ), 
  year = c(rep(2009, 5), 
           rep(2010, 6), 
           rep(2011, 6), 
           rep(2012, 7)),
  age = c(0, 0, 0, 0, 0,
          1, 1, 1, 1, 0, 1,
          2, 2, 2, 1, 2, 2,
          3, 3, 3, 3, 2, 3, 3),
  town = c("0", "0", "2", "0", "0",
          "1", "2", "1", "3", "0", "1",
          "3", "1", "4", "1", "2", "1",
          "4", "2", "2", "1", "2", "1", "5")
)

我对搬家的原因很感兴趣(例如，收入、受教育程度、家庭结构等是否对你是否搬家有影响，以及它是否会影响你搬家的地区)，所以我编码了事件，“移动”，以及使用以下代码的“flag_first_move”:

df3 <- df %>%
  arrange(year, id) %>%
  group_by(id) %>%
  mutate(first_year = min(year)) %>%
  mutate(first_town = list(town[year==first_year])) %>%
  mutate(flag_move = as.numeric(year != first_year & !(town %in% unlist(first_town)) & town !="")) %>%
  mutate(flag_first_move = (flag_move==1 & as.numeric(!duplicated(flag_move)))) %>%
  mutate(moved = case_when(town !=lag(town)  ~ 1,
                           TRUE  ~ 0)) %>%
  mutate(flag_cum_move = (cumsum(c(0, diff(moved)) !=0) + 1)) #This doesn't work as intended

“flag_first_move”给我移动的第一个事件。每次移动时，“移动”都会给我一个标志。最后，通过尝试创建变量“flag_cum_move”，我想要每个事件的累积计数(这样每次一个人移动它都会加 1)——我不知道该怎么做!

最后，我想看看每个人在每个事件(移动)前后的一年。这是我试图完成此任务的代码:

df4 <- df3 %>%
  group_by(id) %>%
  filter(any(flag_first_move == 1)) %>%
  mutate(
    year_before = ifelse(
      between(year[moved == 1] - year, 1, 1), 1, 0),
    year_after = ifelse(
      between(year - year[moved == 1], 1, 1), 1, 0),
  )

它在只发生一个事件的情况下工作正常，但在每年发生多个事件的情况下，它会向我发出“year_after”变量的警告，而且我也没有得到预期的结果.我不明白为什么。

Answer 1

看看这是不是你想要的。最好能在问题中显示预期的输出，所以如果我误解了什么，请在下面的评论中指出，我可以相应地进行调整。

library(tidyverse)

df <- tibble(
  id = c(
    1, 2, 3, 4, 5,
    1, 2, 3, 5, 6, 7,
    2, 3, 4, 6, 7, 8,
    1, 2, 3, 4, 6, 7, 8
  ),
  year = c(
    rep(2009, 5),
    rep(2010, 6),
    rep(2011, 6),
    rep(2012, 7)
  ),
  age = c(
    0, 0, 0, 0, 0,
    1, 1, 1, 1, 0, 1,
    2, 2, 2, 1, 2, 2,
    3, 3, 3, 3, 2, 3, 3
  ),
  town = c(
    "0", "0", "2", "0", "0",
    "1", "2", "1", "3", "0", "1",
    "3", "1", "4", "1", "2", "1",
    "4", "2", "2", "1", "2", "1", "5"
  )
)

df3 <- df %>%
  arrange(id, year) %>%
  group_by(id) %>%
  mutate(
    first_year = min(year),
    first_town = if_else(year == first_year, town, NA_character_)
  ) %>%
  fill(first_town) %>%
  mutate(
    flag_move = if_else(year != first_year & town != first_town, 1, 0),
    flag_first_move = if_else(cumsum(flag_move) == 1, 1, 0),
    moved = if_else(town != lag(town), 1, 0)
  ) %>%
  replace_na(list(moved = 0)) %>%
  mutate(flag_cum_move = cumsum(moved))

df4 <- df3 %>%
  filter(any(flag_first_move == 1)) %>%
  mutate(
    year_before = if_else(lead(moved) == 1, 1, 0),
    year_after = if_else(lag(moved) == 1, 1, 0)
  ) %>%
  ungroup()

df4
#> # A tibble: 24 × 12
#>       id  year   age town  first_year first_town flag_move flag_first_move moved
#>    <dbl> <dbl> <dbl> <chr>      <dbl> <chr>          <dbl>           <dbl> <dbl>
#>  1     1  2009     0 0           2009 0                  0               0     0
#>  2     1  2010     1 1           2009 0                  1               1     1
#>  3     1  2012     3 4           2009 0                  1               0     1
#>  4     2  2009     0 0           2009 0                  0               0     0
#>  5     2  2010     1 2           2009 0                  1               1     1
#>  6     2  2011     2 3           2009 0                  1               0     1
#>  7     2  2012     3 2           2009 0                  1               0     1
#>  8     3  2009     0 2           2009 2                  0               0     0
#>  9     3  2010     1 1           2009 2                  1               1     1
#> 10     3  2011     2 1           2009 2                  1               0     0
#> # … with 14 more rows, and 3 more variables: flag_cum_move <dbl>,
#> #   year_before <dbl>, year_after <dbl>

^{由 reprex package 创建于 2022-06-22 (v2.0.1)}