r - 如何根据 r 数据框中的多列条件创建基于排名的列

Question

我有一个包含 3 列的数据框，我想根据其他列中给出的值创建第四列。为了创建 new_rank 列，我们从 1 作为所有用户的起点，当 matric_1 大于 15 并且 matric_2 大于 20 时，后续的排名值加 1。

我觉得我需要在 r 中使用 cumsum 函数，但正在努力解决 ifelse 条件。数据帧的代码如下

df<-data.frame(user_id=c("a","a","a","a","b","b","b","c","c","c","c","c","d","d","d","d"),matric_1=c(10,23,4,5,17,5,40,1,2,18,19,5,18,2,19,2),matric_2=c(10,25,10,13,21,10,7,3,4,22,21,4,23,4,21,4),new_rank=c(1,1,2,2,1,2,2,1,1,1,2,3,1,2,2,3))


User_id matric_1    matric_2    new_rank
a      10%  10%    1
a      23%  25%    1
a      4%   10%    2
a      5%   13%    2
b      17%  21%    1
b      5%   10%    2
b      40%  7%     2
c      1%   3%     1
c      2%   4%     1
c      18%  22%    1
c      19%  21%    2
c      5%   6%     3
d      18%  23%    1
d      2%   4%     2
d      19%  21%    2
d      2%   4%     3

Answer 1

按“user_id”分组后，通过获取逻辑向量的cumsum的lag来创建“new_rank1”

library(dplyr)
df %>% 
   group_by(user_id) %>% 
   mutate(new_rank1 = lag(cumsum(matric_1 > 15 & matric_2 > 20) + 1, default = 1))
# A tibble: 16 x 5
# Groups: user_id [4]
#   user_id matric_1 matric_2 new_rank new_rank1
#   <fctr>     <dbl>    <dbl>    <dbl>     <dbl>
# 1 a          10.0     10.0      1.00      1.00
# 2 a          23.0     25.0      1.00      1.00
# 3 a           4.00    10.0      2.00      2.00
# 4 a           5.00    13.0      2.00      2.00
# 5 b          17.0     21.0      1.00      1.00
# 6 b           5.00    10.0      2.00      2.00
# 7 b          40.0      7.00     2.00      2.00
# 8 c           1.00     3.00     1.00      1.00
# 9 c           2.00     4.00     1.00      1.00
#10 c          18.0     22.0      1.00      1.00
#11 c          19.0     21.0      2.00      2.00
#12 c           5.00     4.00     3.00      3.00
#13 d          18.0     23.0      1.00      1.00
#14 d           2.00     4.00     2.00      2.00
#15 d          19.0     21.0      2.00      2.00
#16 d           2.00     4.00     3.00      3.00