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首页 > 解决方案 > 在R中将多列除以一列时出错

r - 在R中将多列除以一列时出错

问题描述

这是我正在使用的数据示例：

> head(tableresults)
   ACTIVITY_X ACTIVITY_Y ACTIVITY_Z Vigilance Head-up Grazing Browsing Moving Grooming Resting
1:         40         47         62         0      41       0        0      0        0       0
2:         60         74         95         0      72       0        0      0        5       0
3:         62         63         88         0      80       0        0      0        0       0
4:         60         56         82         0      80       0        0      0        0       0
5:         66         61         90         0      80       0        0      0        0       0
6:         60         53         80         0      80       0        0      0        0       0
   Fleeing Total    Event winning_cluster
1:       0    41  Head-up        cluster2
2:       0    80 Grooming        cluster4
3:       0    80  Head-up        cluster4
4:       0    80  Head-up        cluster4
5:       0    80  Head-up        cluster4
6:       0    80  Head-up        cluster4
>

我只是想将列Vigilance, Head-up, Grazing, Browsing, Moving,Grooming中Resting的值除以 column 中的值Total。我正在使用以下命令，但收到一条错误消息。所有列的行数相同：

> tableresults[,4:11] / tableresults[,12]
Error in Ops.data.frame(tableresults[, 4:11], tableresults[, 12]) : 
  ‘/’ only defined for equally-sized data frames

难道我做错了什么？任何输入表示赞赏！

我在下面的评论之一中提供了完整的数据集：

> dput(tableresults)
structure(list(ACTIVITY_X = c(40L, 60L, 62L, 60L, 66L, 60L, 57L, 
54L, 52L, 93L, 80L, 14L, 61L, 51L, 40L, 20L, 21L, 5L, 53L, 48L, 
73L, 73L, 21L, 29L, 63L, 59L, 57L, 51L, 53L, 67L, 72L, 74L, 70L, 
60L, 74L, 85L, 77L, 68L, 58L, 80L, 34L, 45L, 34L, 60L, 75L, 62L, 
66L, 51L, 53L, 48L, 62L, 62L, 57L, 5L, 1L, 12L, 23L, 5L, 4L, 
0L, 13L, 45L, 44L, 31L, 68L, 88L, 43L, 70L, 18L, 83L, 71L, 67L, 
75L, 74L, 49L, 90L, 44L, 64L, 57L, 22L, 29L, 52L, 37L, 32L, 120L, 
45L, 22L, 54L, 30L, 9L, 27L, 14L, 3L, 29L, 12L, 61L, 60L, 29L, 
15L, 7L, 6L, 0L, 2L, 0L, 4L, 1L, 7L, 0L, 0L, 0L, 0L, 0L, 1L, 
23L, 49L, 46L, 8L, 31L, 45L, 60L, 37L, 61L, 52L, 51L, 38L, 86L, 
60L, 41L, 43L, 40L, 42L, 42L, 48L, 64L, 71L, 59L, 0L, 27L, 12L, 
3L, 0L, 0L, 8L, 21L, 6L, 2L, 7L, 4L, 3L, 3L, 46L, 46L, 59L, 53L, 
37L, 44L, 39L, 49L, 37L, 47L, 17L, 36L, 32L, 33L, 26L, 12L, 8L, 
31L, 35L, 27L, 27L, 24L, 17L, 35L, 39L, 28L, 54L, 5L, 0L, 0L, 
0L, 0L, 17L, 22L, 25L, 12L, 0L, 5L, 41L, 51L, 66L, 39L, 32L, 
53L, 43L, 40L, 44L, 45L, 48L, 51L, 41L, 45L, 39L, 46L, 59L, 31L, 
5L, 24L, 18L, 5L, 15L, 13L, 0L, 26L, 0L), ACTIVITY_Y = c(47L, 
74L, 63L, 56L, 61L, 53L, 40L, 41L, 49L, 32L, 54L, 13L, 99L, 130L, 
38L, 14L, 6L, 5L, 94L, 96L, 38L, 43L, 29L, 47L, 66L, 47L, 38L, 
31L, 36L, 35L, 38L, 72L, 54L, 44L, 45L, 51L, 80L, 48L, 39L, 85L, 
42L, 39L, 37L, 75L, 36L, 45L, 32L, 35L, 41L, 26L, 99L, 163L, 
124L, 0L, 0L, 24L, 37L, 0L, 6L, 0L, 29L, 29L, 26L, 27L, 54L, 
147L, 82L, 98L, 12L, 83L, 97L, 104L, 128L, 81L, 42L, 102L, 60L, 
79L, 58L, 15L, 14L, 75L, 75L, 40L, 130L, 40L, 13L, 54L, 42L, 
7L, 10L, 3L, 0L, 15L, 8L, 75L, 55L, 26L, 18L, 1L, 13L, 0L, 0L, 
0L, 1L, 0L, 4L, 0L, 0L, 0L, 0L, 0L, 0L, 17L, 45L, 38L, 10L, 31L, 
52L, 36L, 65L, 97L, 45L, 59L, 49L, 92L, 51L, 34L, 21L, 20L, 29L, 
28L, 22L, 32L, 30L, 86L, 0L, 15L, 7L, 4L, 0L, 0L, 0L, 11L, 3L, 
0L, 1L, 3L, 1L, 0L, 72L, 62L, 98L, 55L, 26L, 39L, 28L, 81L, 20L, 
52L, 12L, 48L, 24L, 40L, 30L, 5L, 6L, 40L, 37L, 33L, 26L, 17L, 
14L, 39L, 27L, 28L, 67L, 0L, 0L, 0L, 0L, 0L, 10L, 12L, 14L, 7L, 
0L, 2L, 39L, 67L, 74L, 28L, 23L, 57L, 34L, 36L, 36L, 37L, 46L, 
43L, 73L, 65L, 31L, 64L, 128L, 17L, 3L, 12L, 17L, 0L, 9L, 7L, 
0L, 17L, 0L), ACTIVITY_Z = c(62L, 95L, 88L, 82L, 90L, 80L, 70L, 
68L, 71L, 98L, 97L, 19L, 116L, 140L, 55L, 24L, 22L, 7L, 108L, 
107L, 82L, 85L, 36L, 55L, 91L, 75L, 69L, 60L, 64L, 76L, 81L, 
103L, 88L, 74L, 87L, 99L, 111L, 83L, 70L, 117L, 54L, 60L, 50L, 
96L, 83L, 77L, 73L, 62L, 67L, 55L, 117L, 174L, 136L, 5L, 1L, 
27L, 44L, 5L, 7L, 0L, 32L, 54L, 51L, 41L, 87L, 171L, 93L, 120L, 
22L, 117L, 120L, 124L, 148L, 110L, 65L, 136L, 74L, 102L, 81L, 
27L, 32L, 91L, 84L, 51L, 177L, 60L, 26L, 76L, 52L, 11L, 29L, 
14L, 3L, 33L, 14L, 97L, 81L, 39L, 23L, 7L, 14L, 0L, 2L, 0L, 4L, 
1L, 8L, 0L, 0L, 0L, 0L, 0L, 1L, 29L, 67L, 60L, 13L, 44L, 69L, 
70L, 75L, 115L, 69L, 78L, 62L, 126L, 79L, 53L, 48L, 45L, 51L, 
50L, 53L, 72L, 77L, 104L, 0L, 31L, 14L, 5L, 0L, 0L, 8L, 24L, 
7L, 2L, 7L, 5L, 3L, 3L, 85L, 77L, 114L, 76L, 45L, 59L, 48L, 95L, 
42L, 70L, 21L, 60L, 40L, 52L, 40L, 13L, 10L, 51L, 51L, 43L, 37L, 
29L, 22L, 52L, 47L, 40L, 86L, 5L, 0L, 0L, 0L, 0L, 20L, 25L, 29L, 
14L, 0L, 5L, 57L, 84L, 99L, 48L, 39L, 78L, 55L, 54L, 57L, 58L, 
66L, 67L, 84L, 79L, 50L, 79L, 141L, 35L, 6L, 27L, 25L, 5L, 17L, 
15L, 0L, 31L, 0L), Vigilance = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 
12L, 8L, 0L, 3L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 5L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 49L, 0L, 5L, 0L, 11L, 44L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 30L, 57L, 65L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 18L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 24L, 44L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 8L, 5L, 27L, 7L, 0L, 59L, 19L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 12L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 22L, 0L, 15L, 0L, 
0L, 18L, 22L, 26L, 0L, 10L, 39L), `Head-up` = c(41L, 72L, 80L, 
80L, 80L, 80L, 80L, 61L, 47L, 13L, 34L, 34L, 80L, 80L, 80L, 80L, 
65L, 0L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 0L, 0L, 
4L, 0L, 12L, 0L, 14L, 9L, 10L, 0L, 8L, 15L, 5L, 16L, 5L, 0L, 
5L, 20L, 52L, 39L, 0L, 11L, 16L, 7L, 9L, 15L, 6L, 9L, 18L, 5L, 
3L, 22L, 14L, 4L, 8L, 0L, 7L, 11L, 0L, 15L, 80L, 65L, 21L, 0L, 
3L, 0L, 4L, 2L, 23L, 4L, 10L, 13L, 7L, 0L, 63L, 80L, 62L, 80L, 
80L, 80L, 2L, 4L, 8L, 3L, 20L, 9L, 3L, 53L, 80L, 80L, 80L, 80L, 
80L, 80L, 80L, 80L, 80L, 80L, 80L, 19L, 0L, 24L, 3L, 18L, 80L, 
80L, 80L, 75L, 16L, 0L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
80L, 80L, 80L, 8L, 24L, 20L, 15L, 30L, 34L, 29L, 41L, 21L, 45L, 
46L, 12L, 80L, 80L, 61L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 77L, 
73L, 80L, 80L, 80L, 80L, 80L, 68L, 80L, 80L, 80L, 80L, 80L, 75L, 
77L, 46L, 80L, 65L, 74L, 80L, 62L, 46L, 27L, 26L, 31L, 28L), 
    Grazing = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 22L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 61L, 75L, 
    5L, 0L, 62L, 61L, 64L, 28L, 15L, 52L, 34L, 44L, 75L, 29L, 
    24L, 80L, 52L, 0L, 0L, 0L, 0L, 44L, 39L, 73L, 35L, 3L, 74L, 
    68L, 62L, 59L, 31L, 56L, 66L, 73L, 72L, 70L, 27L, 16L, 14L, 
    0L, 0L, 8L, 19L, 80L, 77L, 80L, 65L, 75L, 57L, 66L, 43L, 
    42L, 47L, 79L, 0L, 0L, 0L, 0L, 0L, 0L, 69L, 76L, 58L, 75L, 
    47L, 21L, 47L, 5L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 6L, 12L, 43L, 0L, 0L, 0L, 0L, 16L, 26L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 55L, 47L, 56L, 56L, 29L, 19L, 
    44L, 39L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 9L, 5L, 4L, 5L), Browsing = c(0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 11L, 9L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 14L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 25L, 0L, 0L), Moving = c(0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 7L, 25L, 26L, 43L, 27L, 0L, 0L, 0L, 0L, 15L, 62L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 71L, 58L, 6L, 0L, 0L, 43L, 37L, 
    16L, 30L, 21L, 0L, 0L, 0L, 0L, 7L, 0L, 0L, 8L, 23L, 0L, 16L, 
    0L, 11L, 18L, 0L, 0L, 0L, 16L, 46L, 0L, 0L, 0L, 0L, 0L, 28L, 
    23L, 9L, 0L, 0L, 0L, 12L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 24L, 
    20L, 13L, 1L, 13L, 0L, 0L, 0L, 0L, 0L, 4L, 0L, 0L, 0L, 0L, 
    15L, 18L, 13L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    23L, 63L, 15L, 0L, 19L, 0L, 0L, 0L, 5L, 37L, 4L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 2L, 4L, 0L, 2L, 0L, 0L, 0L, 
    0L, 14L, 19L, 57L, 0L, 0L, 19L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 10L, 16L, 13L, 8L), Grooming = c(0L, 
    5L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 0L, 
    18L, 0L, 0L, 0L, 0L, 35L, 51L, 0L, 16L, 46L, 28L, 27L, 0L, 
    0L, 0L, 0L, 5L, 0L, 0L, 3L, 0L, 0L, 0L, 2L, 0L, 3L, 0L, 10L, 
    18L, 0L, 0L, 0L, 0L, 7L, 5L, 0L, 0L, 0L, 11L, 3L, 0L, 10L, 
    3L, 0L, 0L, 0L, 4L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 0L, 
    33L, 0L, 3L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    18L, 17L, 7L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 5L, 7L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 3L, 7L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 5L, 3L, 12L, 
    0L, 0L, 6L, 0L, 0L, 7L, 4L, 2L, 13L, 0L), Resting = c(0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L), Fleeing = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), Total = c(41L, 
    80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
    80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
    80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
    80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
    80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
    80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
    80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
    80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
    80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
    80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
    80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
    80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
    80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
    80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
    80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
    80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
    80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 
    80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L, 80L), Event = c("Head-up", 
    "Grooming", "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", 
    "Vigilance", "Moving", "Moving", "Moving", "Moving", "Head-up", 
    "Head-up", "Head-up", "Head-up", "Moving", "Moving", "Head-up", 
    "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", 
    "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", 
    "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", 
    "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", 
    "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", 
    "Head-up", "Head-up", "Head-up", "Head-up", "Grazing", "Grazing", 
    "Moving", "Moving", "Grazing", "Grazing", "Grazing", "Moving", 
    "Moving", "Grazing", "Grazing", "Grazing", "Grazing", "Grooming", 
    "Grooming", "Grazing", "Grazing", "Grooming", "Grooming", 
    "Grooming", "Vigilance", "Grazing", "Grazing", "Grazing", 
    "Grazing", "Vigilance", "Grazing", "Grazing", "Grazing", 
    "Grazing", "Moving", "Grazing", "Grazing", "Grazing", "Grazing", 
    "Grazing", "Moving", "Vigilance", "Vigilance", "Vigilance", 
    "Head-up", "Grazing", "Grazing", "Grazing", "Grazing", "Grazing", 
    "Grazing", "Grazing", "Grazing", "Grazing", "Grazing", "Grazing", 
    "Grazing", "Grazing", "Moving", "Head-up", "Vigilance", "Head-up", 
    "Head-up", "Head-up", "Grazing", "Grazing", "Grazing", "Grazing", 
    "Grazing", "Grooming", "Grazing", "Moving", "Head-up", "Head-up", 
    "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", 
    "Head-up", "Head-up", "Head-up", "Moving", "Moving", "Vigilance", 
    "Vigilance", "Grazing", "Head-up", "Head-up", "Head-up", 
    "Moving", "Moving", "Grazing", "Head-up", "Head-up", "Head-up", 
    "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", 
    "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", 
    "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", 
    "Head-up", "Head-up", "Head-up", "Grazing", "Grazing", "Grazing", 
    "Grazing", "Grazing", "Vigilance", "Grazing", "Grazing", 
    "Vigilance", "Vigilance", "Moving", "Moving", "Head-up", 
    "Head-up", "Moving", "Head-up", "Head-up", "Head-up", "Head-up", 
    "Head-up", "Head-up", "Head-up", "Grooming", "Grooming", 
    "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", "Vigilance", 
    "Head-up", "Head-up", "Head-up", "Head-up", "Head-up", "Grooming", 
    "Grooming", "Vigilance", "Head-up", "Vigilance", "Grooming", 
    "Head-up", "Vigilance", "Vigilance", "Vigilance", "Browsing", 
    "Moving", "Vigilance"), winning_cluster = c("cluster2", "cluster4", 
    "cluster4", "cluster4", "cluster4", "cluster4", "cluster4", 
    "cluster4", "cluster4", "cluster3", "cluster3", "cluster1", 
    "cluster3", "cluster3", "cluster2", "cluster1", "cluster1", 
    "cluster1", "cluster3", "cluster3", "cluster4", "cluster4", 
    "cluster2", "cluster2", "cluster4", "cluster4", "cluster4", 
    "cluster2", "cluster2", "cluster4", "cluster4", "cluster3", 
    "cluster4", "cluster4", "cluster4", "cluster3", "cluster3", 
    "cluster4", "cluster4", "cluster3", "cluster2", "cluster2", 
    "cluster2", "cluster4", "cluster4", "cluster4", "cluster4", 
    "cluster2", "cluster4", "cluster2", "cluster3", "cluster3", 
    "cluster3", "cluster1", "cluster1", "cluster1", "cluster2", 
    "cluster1", "cluster1", "cluster1", "cluster2", "cluster2", 
    "cluster2", "cluster2", "cluster4", "cluster3", "cluster4", 
    "cluster3", "cluster1", "cluster3", "cluster3", "cluster3", 
    "cluster3", "cluster3", "cluster2", "cluster3", "cluster4", 
    "cluster4", "cluster4", "cluster1", "cluster2", "cluster4", 
    "cluster4", "cluster2", "cluster3", "cluster2", "cluster1", 
    "cluster4", "cluster2", "cluster1", "cluster1", "cluster1", 
    "cluster1", "cluster2", "cluster1", "cluster4", "cluster4", 
    "cluster2", "cluster1", "cluster1", "cluster1", "cluster1", 
    "cluster1", "cluster1", "cluster1", "cluster1", "cluster1", 
    "cluster1", "cluster1", "cluster1", "cluster1", "cluster1", 
    "cluster1", "cluster2", "cluster2", "cluster2", "cluster1", 
    "cluster2", "cluster2", "cluster4", "cluster4", "cluster3", 
    "cluster4", "cluster4", "cluster2", "cluster3", "cluster4", 
    "cluster2", "cluster2", "cluster2", "cluster2", "cluster2", 
    "cluster2", "cluster4", "cluster4", "cluster4", "cluster1", 
    "cluster2", "cluster1", "cluster1", "cluster1", "cluster1", 
    "cluster1", "cluster1", "cluster1", "cluster1", "cluster1", 
    "cluster1", "cluster1", "cluster1", "cluster4", "cluster4", 
    "cluster3", "cluster4", "cluster2", "cluster2", "cluster2", 
    "cluster4", "cluster2", "cluster2", "cluster1", "cluster2", 
    "cluster2", "cluster2", "cluster2", "cluster1", "cluster1", 
    "cluster2", "cluster2", "cluster2", "cluster2", "cluster2", 
    "cluster1", "cluster2", "cluster2", "cluster2", "cluster4", 
    "cluster1", "cluster1", "cluster1", "cluster1", "cluster1", 
    "cluster1", "cluster1", "cluster1", "cluster1", "cluster1", 
    "cluster1", "cluster2", "cluster4", "cluster3", "cluster2", 
    "cluster2", "cluster4", "cluster2", "cluster2", "cluster2", 
    "cluster2", "cluster2", "cluster4", "cluster4", "cluster4", 
    "cluster2", "cluster4", "cluster3", "cluster2", "cluster1", 
    "cluster1", "cluster1", "cluster1", "cluster1", "cluster1", 
    "cluster1", "cluster2", "cluster1")), row.names = c(NA, -215L
), class = c("data.table", "data.frame"), .internal.selfref = <pointer: 0x0000000002541ef0>)```

标签： rdataframe

解决方案

您可以使用mutate_at修改这些字段，如下所示：

> library(dplyr)
> tableresults <- tableresults %>%
  mutate_at(.vars = vars(Vigilance:Fleeing),
            .funs = funs(. / Total)) 
>  head(tableresults)
  ACTIVITY_X ACTIVITY_Y ACTIVITY_Z Vigilance Head-up Grazing Browsing Moving Grooming
1         40         47         62         0     1.0       0        0      0   0.0000
2         60         74         95         0     0.9       0        0      0   0.0625
3         62         63         88         0     1.0       0        0      0   0.0000
4         60         56         82         0     1.0       0        0      0   0.0000
5         66         61         90         0     1.0       0        0      0   0.0000
6         60         53         80         0     1.0       0        0      0   0.0000
  Resting Fleeing Total    Event winning_cluster
1       0       0    41  Head-up        cluster2
2       0       0    80 Grooming        cluster4
3       0       0    80  Head-up        cluster4
4       0       0    80  Head-up        cluster4
5       0       0    80  Head-up        cluster4
6       0       0    80  Head-up        cluster4

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