R 将列分为两组。一个数字有小数，另一个只有绝对数

我有以下资料：

我想对这些数据求和（例如字母A-E）。对于绝对值，这很容易。然而，对于百分比，我需要考虑权重。因此，我想将具有小数位数（百分比）的列与不具有小数位数的列分开

百分比列应允许有绝对数和小数。但绝对值列中不允许有小数点

我该怎么做

DT <- structure(list(Letters = c("A", "B", "C", "D", "E"), Percentage = c(0.67, 
0.2, 0.4, 0.2, 0), Absolute_number = c(1000, 200, 0, -199, 1), 
    PercentageII = c(65.2, 1.2, 22.8, 4, 0), weights = c(2, 3, 
    3, 1, 8)), row.names = c(NA, -5L), class = c("tbl_df", "tbl", 
"data.frame"))

  Letters Percentage Absolute_number PercentageII weights
  <chr>        <dbl>           <dbl>        <dbl>   <dbl>
1 A             0.67            1000         65.2       2
2 B             0.2              200          1.2       3
3 C             0.4                0         22.8       3
4 D             0.2             -199          4         1
5 E             0                  1          0         8

---

DT使用
过滤器
：

DT1 <- Filter(function(x) is.character(x) || all(x %% 1 == 0), DT)
DT2 <- Filter(function(x) is.character(x) || any(x %% 1 != 0), DT)

DT1

# A tibble: 5 x 3
#  Letters Absolute_number weights
#  <chr>             <dbl>   <dbl>
#1 A                  1000       2
#2 B                   200       3
#3 C                     0       3
#4 D                  -199       1
#5 E                     1       8

DT2
# A tibble: 5 x 3
#  Letters Percentage PercentageII
#  <chr>        <dbl>        <dbl>
#1 A             0.67         65.2
#2 B             0.2           1.2
#3 C             0.4          22.8
#4 D             0.2           4  
#5 E             0             0  

DT1我已经添加了预期的输出。效果非常好！
DT1 <- Filter(function(x) is.character(x) || all(x %% 1 == 0), DT)
DT2 <- Filter(function(x) is.character(x) || any(x %% 1 != 0), DT)

DT1

# A tibble: 5 x 3
#  Letters Absolute_number weights
#  <chr>             <dbl>   <dbl>
#1 A                  1000       2
#2 B                   200       3
#3 C                     0       3
#4 D                  -199       1
#5 E                     1       8

DT2
# A tibble: 5 x 3
#  Letters Percentage PercentageII
#  <chr>        <dbl>        <dbl>
#1 A             0.67         65.2
#2 B             0.2           1.2
#3 C             0.4          22.8
#4 D             0.2           4  
#5 E             0             0