如何解决使用嵌套类别将长数据范围扩大
我正在尝试将长数据转换为宽格式，但是我有多个类别需要嵌套。我当前的数据如下：
YRTR sub_cou SUBJ PATH path_count pre_drop_count freq
20173 ACCT 2251 ACCT 1051 -> 2251 1 235 0.40%
20183 ACCT 2251 ACCT 1051 -> 2251 1 217 0.50%
20203 ACCT 2251 ACCT 1051 -> 2251 1 248 0.40%
20213 ACCT 2251 ACCT 1051 -> 2251 1 219 0.50%
20213 ACCT 2251 ACCT 1051 and 2251 -> NA 1 219 0.50%
20173 ACCT 2251 ACCT 1853 -> 2251 2 235 0.90%
20183 ACCT 2251 ACCT 2251 -> 1051 1 217 0.50%
20173 ACCT 2251 ACCT 2251 -> 2251 224 235 95.30%
20183 ACCT 2251 ACCT 2251 -> 2251 210 217 96.80%
20193 ACCT 2251 ACCT 2251 -> 2251 240 258 93%
20203 ACCT 2251 ACCT 2251 -> 2251 223 248 89.90%
20213 ACCT 2251 ACCT 2251 -> 2251 204 219 93.20%
20173 ACCT 2251 ACCT 2251 -> NA 11 235 4.70%
20183 ACCT 2251 ACCT 2251 -> NA 6 217 2.80%
20193 ACCT 2251 ACCT 2251 -> NA 18 258 7.00%
20203 ACCT 2251 ACCT 2251 -> NA 25 248 10.10%
20213 ACCT 2251 ACCT 2251 -> NA 14 219 6.40%
20173 ACCT 2251 ACCT NA -> 2251 17 235 7.20%
20183 ACCT 2251 ACCT NA -> 2251 23 217 10.60%
20193 ACCT 2251 ACCT NA -> 2251 29 258 11%
20203 ACCT 2251 ACCT NA -> 2251 37 248 14.90%
20213 ACCT 2251 ACCT NA -> 2251 40 219 18.30%
我正在尝试通过YRTR将其转换为宽格式，但是还具有path_count，pre_drop_count和freq的值。因此理想情况下，它看起来应该像这样：
20173 20183 20193 20203
sub_cou SUBJ PATH path_count pre_drop_count freq path_count pre_drop_count freq path_count pre_drop_count freq path_count pre_drop_count freq
ACCT 2251 ACCT 1853 -> 2251 2 235 0.90% NA NA NA NA NA NA NA NA NA
ACCT 2251 ACCT NA -> 2251 17 235 7.20% 23 217 10.60% 29 258 11% 37 248 14.90%
ACCT 2251 ACCT 2251 -> NA 11 235 4.70% 6 217 2.80% 18 258 7.00% 25 248 10.10%
ACCT 2251 ACCT 2251 -> 2251 224 235 95.30% 210 217 96.80% 240 258 93% 223 248 89.90%
ACCT 2251 ACCT 1051 -> 2251 1 235 0.40% 1 217 0.50% NA NA NA 1 248 0.40%
ACCT 2251 ACCT 2251 -> 1051 NA NA NA 1 217 0.50% NA NA NA NA NA NA
我尝试过使用dcast，但似乎只想将YRTR放在首位。
编辑后添加dput（）输出：
dput(path_agg2)
structure(list(YRTR = c(20173L,20173L,20183L,20193L,20203L,20213L,20213L),sub_cou = c("ACCT 2251","ACCT 2251","ACCT 2251"),SUBJ = c("ACCT","ACCT","ACCT"),PATH = c("1853 -> 2251","NA -> 2251","2251 -> NA","2251 -> 2251","1051 -> 2251","2251 -> 1051","1051 and 2251 -> NA","NA -> 2251"),path_count = c(2L,17L,11L,224L,1L,6L,210L,23L,29L,240L,18L,223L,25L,37L,204L,14L,40L),pre_drop_count = c(235L,235L,217L,258L,248L,219L,219L),freq = c("0.9%","7.2%","4.7%","95.3%","0.4%","2.8%","0.5%","96.8%","10.6%","11.2%","93%","7%","89.9%","10.1%","14.9%","93.2%","6.4%","18.3%")),row.names = c(NA,-22L),class = "data.frame")
解决方法
此答案是否正确
> path_agg2_wider <- path_agg2 %>% pivot_wider(
+ names_from = YRTR,+ values_from = c(path_count,pre_drop_count,freq)
+ )
> path_agg2_wider <- path_agg2_wider[c(1:3,4,9,14,5,10,15,6,11,16,7,12,17,8,13,18)]
> path_agg2_wider
# A tibble: 7 x 18
sub_cou SUBJ PATH path_count_20173 pre_drop_count_~ freq_20173 path_count_20183 pre_drop_count_~ freq_20183 path_count_20193 pre_drop_count_~ freq_20193
<chr> <chr> <chr> <int> <int> <chr> <int> <int> <chr> <int> <int> <chr>
1 ACCT 2~ ACCT 1853~ 2 235 0.9% NA NA NA NA NA NA
2 ACCT 2~ ACCT NA -~ 17 235 7.2% 23 217 10.6% 29 258 11.2%
3 ACCT 2~ ACCT 2251~ 11 235 4.7% 6 217 2.8% 18 258 7%
4 ACCT 2~ ACCT 2251~ 224 235 95.3% 210 217 96.8% 240 258 93%
5 ACCT 2~ ACCT 1051~ 1 235 0.4% 1 217 0.5% NA NA NA
6 ACCT 2~ ACCT 2251~ NA NA NA 1 217 0.5% NA NA NA
7 ACCT 2~ ACCT 1051~ NA NA NA NA NA NA NA NA NA
# ... with 6 more variables: path_count_20203 <int>,pre_drop_count_20203 <int>,freq_20203 <chr>,path_count_20213 <int>,pre_drop_count_20213 <int>,# freq_20213 <chr>
>
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