Count 然后计算分组后第一行和前一行的差异，但忽略 r 中的文本/字符值

Question

根据以下按

id

和

visit

分组的数据，其中包括数字和文本/字符

values

的混合，如何创建这 3 个新列：

• count_wotxt

  ：按

  id

  和

  visit

  进行计数，但不考虑文本/字符值

• diff_value_first

  ：计算每个visit的每个数值

  与第一个

  id

  之间的差异，忽略文本/字符

  values
• diff_value_previous

  ：计算每个

  visit的每个数值与前一个

  id

  之间的差异，忽略文本/字符

  values

数据：

dat <-  
structure(list(id = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("1", "2"), class = "factor"), 
    visit = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 
    1L, 1L, 2L, 2L, 2L), .Label = c("1", "2"), class = "factor"), 
    value = c("5", "7", "10", "20", "15", "text0", "25", "text1", 
    "100", "text2", "text3", "120", "text4", "50", "45"), count = c(1L, 
    2L, 3L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 1L, 2L, 3L)), class = "data.frame", row.names = c(NA, 
-15L)) 

所需输出：

> dat2
   id visit value count count_wotxt diff_value_first diff_value_previous
1   1     1     5     1           1                0                   0
2   1     1     7     2           2                2                   2
3   1     1    10     3           3                5                   3
4   1     2    20     1           1                0                   0
5   1     2    15     2           2               -5                  -5
6   1     2 text0     3          NA               NA                  NA
7   1     2    25     4           3                5                  10
8   1     2 text1     5          NA               NA                  NA
9   2     1   100     1           1                0                   0
10  2     1 text2     2          NA               NA                  NA
11  2     1 text3     3          NA               NA                  NA
12  2     1   120     4           2               20                  20
13  2     2 text4     1          NA               NA                  NA
14  2     2    50     2           1               NA                   0
15  2     2    45     3           2               NA                  -5 

感谢您的帮助

Answer 1

# A tibble: 15 × 7
   id    visit value count count_wotxt diff_value_first diff_value_previous
   <fct> <fct> <chr> <int>       <int>            <dbl>               <dbl>
 1 1     1     5         1           1                0                   0
 2 1     1     7         2           2                2                   2
 3 1     1     10        3           3                5                   3
 4 1     2     20        1           1                0                   0
 5 1     2     15        2           2               -5                  -5
 6 1     2     text0     3          NA               NA                   0
 7 1     2     25        4           3                5                  10
 8 1     2     text1     5          NA               NA                   0
 9 2     1     100       1           1                0                   0
10 2     1     text2     2          NA               NA                   0
11 2     1     text3     3          NA               NA                   0
12 2     1     120       4           2               20                  20
13 2     2     text4     1          NA               NA                  NA
14 2     2     50        2           1               NA                  NA
15 2     2     45        3           2               NA                  -5
Warning message:
There were 3 warnings in `mutate()`.
The first warning was:
ℹ In argument: `value_numeric = as.numeric(as.character(value))`.
ℹ In group 2: `id = 1`, `visit = 2`.
Caused by warning:
! NAs introduced by coercion
ℹ Run dplyr::last_dplyr_warnings() to see the 2 remaining warnings.