Question

让我们考虑以下示例：

set.seed(5)

df <- data.frame(CATEGORY = rep(c("A", "B", "C", "D"), each = 2),
                 SUBCATEGORY = paste0(rep(c("A", "B", "C", "D"), each = 2), 1:2),
                 COUNT = sample(1:1000, size = 8, replace = TRUE),
                 SUBCOUNT = sample(1:200, size = 8, replace = TRUE),
                 stringsAsFactors = FALSE)

df$SUBCOUNT_PCT <- paste0(formatC(df$SUBCOUNT/df$COUNT * 100, digits = 2, format = 'f'), "%")

> df
  CATEGORY SUBCATEGORY COUNT SUBCOUNT SUBCOUNT_PCT
1        A          A1   201      192       95.52%
2        A          A2   686       23        3.35%
3        B          B1   917       55        6.00%
4        B          B2   285       99       34.74%
5        C          C1   105       64       60.95%
6        C          C2   702      112       15.95%
7        D          D1   528       53       10.04%
8        D          D2   808       41        5.07%

我想为CATEGORY创建汇总COUNT和SUBCOUNT的行，如下所示：

  CATEGORY SUBCATEGORY COUNT SUBCOUNT SUBCOUNT_PCT
1        A       TOTAL   887      215       24.24%   
2        A          A1   201      192       95.52%
3        A          A2   686       23        3.35%
4        B       TOTAL  1202      154       12.81%
5        B          B1   917       55        6.00%
6        B          B2   285       99       34.74%
7        C       TOTAL   807      176       21.81%  
8        C          C1   105       64       60.95%
9        C          C2   702      112       10.04%
10       D       TOTAL  1336       94        7.04%
11       D          D1   528       53       10.04%
12       D          D2   808       41        5.07%

有没有办法在不必遍历每个CATEGORY的情况下执行此操作？

Answer 1

使用dplyr汇总数据，然后绑定回原始数据

library(dplyr)

df %>%
  group_by(CATEGORY) %>%
  summarize(SUBCATEGORY = "TOTAL",
            COUNT = sum(COUNT),
            SUBCOUNT = sum(SUBCOUNT),
            SUBCOUNT_PCT = sprintf("%.2f%%", SUBCOUNT / COUNT * 100)) %>%
  bind_rows(., df) %>%
  arrange(CATEGORY)

# A tibble: 12 x 5
   CATEGORY SUBCATEGORY COUNT SUBCOUNT SUBCOUNT_PCT
      <chr>       <chr> <int>    <int>        <chr>
 1        A       TOTAL   887      215       24.24%
 2        A          A1   201      192       95.52%
 3        A          A2   686       23        3.35%
 4        B       TOTAL  1202      154       12.81%
 5        B          B1   917       55        6.00%
 6        B          B2   285       99       34.74%
 7        C       TOTAL   807      176       21.81%
 8        C          C1   105       64       60.95%
 9        C          C2   702      112       15.95%
10        D       TOTAL  1336       94        7.04%
11        D          D1   528       53       10.04%
12        D          D2   808       41        5.07%

根据另一列的值创建总行

1 个答案: