Как я могу преобразовать пользовательскую строковую переменную `dayHour` в формат даты? - PullRequest
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Как я могу преобразовать пользовательскую строковую переменную `dayHour` в формат даты?

1 голос
/ 16 апреля 2019

У меня есть набор данных (оригинал намного больше): 

hourly <- structure(list(day = c("Thu", "Thu", "Thu", "Thu", "Thu", "Thu", 
"Thu", "Thu", "Thu", "Thu", "Thu", "Thu", "Thu", "Thu", "Thu", 
"Thu", "Thu", "Thu", "Thu", "Thu", "Thu", "Thu", "Thu", "Thu", 
"Fri", "Fri", "Fri", "Fri", "Fri", "Fri", "Fri", "Fri", "Fri", 
"Fri", "Fri", "Fri", "Fri", "Fri", "Fri", "Fri", "Fri", "Fri", 
"Fri", "Fri", "Fri", "Fri", "Fri", "Fri", "Sat", "Sat", "Sat", 
"Sat", "Sat", "Sat", "Sat", "Sat", "Sat", "Sat", "Sat", "Sat", 
"Sat", "Sat", "Sat", "Sat", "Sat", "Sat", "Sat", "Sat", "Sat", 
"Sat", "Sat", "Sat", "Sun", "Sun", "Sun", "Sun", "Sun", "Sun", 
"Sun", "Sun", "Sun", "Sun", "Sun", "Sun", "Sun", "Sun", "Sun", 
"Sun", "Sun", "Sun", "Sun", "Sun", "Sun", "Sun", "Sun", "Sun", 
"Mon", "Mon", "Mon", "Mon", "Mon", "Mon", "Mon", "Mon", "Mon", 
"Mon", "Mon", "Mon", "Mon", "Mon", "Mon", "Mon", "Mon", "Mon", 
"Mon", "Mon", "Mon", "Mon", "Mon", "Mon", "Tue", "Tue", "Tue", 
"Tue", "Tue", "Tue", "Tue", "Tue", "Tue", "Tue", "Tue", "Tue", 
"Tue", "Tue", "Tue", "Tue", "Tue", "Tue", "Tue", "Tue", "Tue", 
"Tue", "Tue", "Tue", "Wed", "Wed", "Wed", "Wed", "Wed", "Wed", 
"Wed", "Wed", "Wed", "Wed", "Wed", "Wed", "Wed", "Wed", "Wed", 
"Wed", "Wed", "Wed", "Wed", "Wed", "Wed", "Wed", "Wed", "Wed", 
"Thu", "Thu", "Thu", "Thu", "Thu", "Thu", "Thu", "Thu", "Thu", 
"Thu", "Thu", "Thu", "Thu", "Thu", "Thu", "Thu", "Thu", "Thu", 
"Thu", "Thu", "Thu", "Thu", "Thu", "Thu", "Fri", "Fri", "Fri", 
"Fri", "Fri", "Fri", "Fri", "Fri", "Fri", "Fri", "Fri", "Fri", 
"Fri", "Fri", "Fri", "Fri", "Fri", "Fri", "Fri", "Fri", "Fri", 
"Fri", "Fri", "Fri", "Sat", "Sat", "Sat", "Sat", "Sat", "Sat", 
"Sat", "Sat", "Sat", "Sat", "Sat", "Sat", "Sat", "Sat", "Sat", 
"Sat", "Sat", "Sat", "Sat", "Sat", "Sat", "Sat", "Sat", "Sat", 
"Sun", "Sun", "Sun", "Sun", "Sun", "Sun", "Sun", "Sun", "Sun", 
"Sun", "Sun", "Sun", "Sun", "Sun", "Sun", "Sun", "Sun", "Sun", 
"Sun", "Sun", "Sun", "Sun", "Sun", "Sun", "Mon", "Mon", "Mon", 
"Mon", "Mon", "Mon", "Mon", "Mon", "Mon", "Mon", "Mon", "Mon", 
"Mon", "Mon", "Mon", "Mon", "Mon", "Mon", "Mon", "Mon", "Mon", 
"Mon", "Mon", "Mon", "Tue", "Tue", "Tue", "Tue", "Tue", "Tue", 
"Tue", "Tue", "Tue", "Tue", "Tue", "Tue", "Tue", "Tue", "Tue", 
"Tue", "Tue", "Tue", "Tue", "Tue", "Tue", "Tue", "Tue", "Tue", 
"Wed", "Wed", "Wed", "Wed", "Wed", "Wed", "Wed", "Wed", "Wed", 
"Wed", "Wed", "Wed", "Wed", "Wed", "Wed", "Wed", "Wed", "Wed", 
"Wed", "Wed", "Wed", "Wed", "Wed", "Wed", "Thu", "Thu", "Thu", 
"Thu", "Thu", "Thu", "Thu", "Thu", "Thu", "Thu", "Thu", "Thu", 
"Thu", "Thu", "Thu", "Thu", "Thu", "Thu", "Thu", "Thu", "Thu", 
"Thu", "Thu", "Thu", "Fri", "Fri", "Fri", "Fri", "Fri", "Fri", 
"Fri", "Fri", "Fri", "Fri", "Fri", "Fri", "Fri", "Fri", "Fri", 
"Fri", "Fri", "Fri", "Fri", "Fri", "Fri", "Fri", "Fri", "Fri", 
"Sat", "Sat", "Sat", "Sat", "Sat", "Sat", "Sat", "Sat", "Sat", 
"Sat", "Sat", "Sat", "Sat", "Sat", "Sat", "Sat", "Sat", "Sat", 
"Sat", "Sat", "Sat", "Sat", "Sat", "Sat", "Sun", "Sun", "Sun", 
"Sun", "Sun", "Sun", "Sun", "Sun", "Sun", "Sun", "Sun", "Sun", 
"Sun", "Sun", "Sun", "Sun", "Sun", "Sun", "Sun", "Sun", "Sun", 
"Sun", "Sun", "Sun", "Mon", "Mon", "Mon", "Mon", "Mon", "Mon", 
"Mon", "Mon", "Mon", "Mon", "Mon", "Mon", "Mon", "Mon", "Mon", 
"Mon", "Mon", "Mon", "Mon", "Mon", "Mon", "Mon", "Tue", "Tue", 
"Tue", "Tue", "Tue", "Tue", "Tue", "Tue", "Tue", "Tue", "Tue", 
"Tue", "Tue", "Tue", "Tue", "Tue", "Tue", "Tue", "Tue", "Tue", 
"Tue", "Tue", "Tue", "Tue", "Wed", "Wed", "Wed", "Wed", "Wed", 
"Wed", "Wed", "Wed", "Wed", "Wed", "Wed", "Wed", "Wed", "Wed", 
"Wed", "Wed", "Wed", "Wed", "Wed", "Wed", "Wed", "Wed"), hour = c(0L, 
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L, 
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 
18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 
8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 
21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 
12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L, 
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L, 
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 
18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 
8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 
21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 
12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L, 
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L, 
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 
18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 
8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 
21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 
12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L, 
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L, 
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 
18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 
8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 
21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 
12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L, 
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L, 
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 
18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 6L, 7L, 8L, 
10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 
23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 
14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 
3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 
17L, 18L, 19L, 20L, 21L), totalCalls = c(30L, 28L, 15L, 21L, 
11L, 14L, 18L, 35L, 42L, 36L, 37L, 38L, 54L, 45L, 37L, 52L, 40L, 
66L, 84L, 69L, 75L, 51L, 39L, 38L, 25L, 21L, 18L, 20L, 7L, 14L, 
14L, 28L, 37L, 50L, 46L, 31L, 45L, 45L, 39L, 31L, 48L, 69L, 91L, 
117L, 74L, 66L, 60L, 37L, 20L, 31L, 15L, 26L, 18L, 12L, 21L, 
42L, 107L, 118L, 138L, 137L, 93L, 109L, 102L, 91L, 102L, 76L, 
76L, 70L, 68L, 74L, 55L, 54L, 28L, 19L, 23L, 12L, 16L, 12L, 18L, 
39L, 96L, 119L, 111L, 95L, 65L, 81L, 67L, 76L, 64L, 64L, 68L, 
71L, 54L, 65L, 51L, 41L, 30L, 16L, 12L, 11L, 13L, 16L, 20L, 41L, 
55L, 57L, 46L, 52L, 44L, 55L, 55L, 45L, 53L, 73L, 84L, 72L, 63L, 
74L, 52L, 39L, 32L, 27L, 21L, 11L, 15L, 14L, 17L, 36L, 43L, 68L, 
55L, 40L, 38L, 50L, 40L, 42L, 57L, 74L, 79L, 76L, 78L, 60L, 49L, 
40L, 17L, 24L, 14L, 15L, 10L, 14L, 18L, 31L, 46L, 45L, 37L, 37L, 
38L, 34L, 32L, 41L, 45L, 51L, 81L, 91L, 62L, 63L, 49L, 23L, 39L, 
30L, 17L, 16L, 9L, 9L, 17L, 33L, 36L, 47L, 44L, 43L, 41L, 56L, 
43L, 41L, 40L, 38L, 78L, 99L, 75L, 61L, 59L, 35L, 22L, 10L, 14L, 
14L, 18L, 12L, 11L, 27L, 65L, 50L, 59L, 42L, 51L, 37L, 53L, 30L, 
38L, 61L, 94L, 88L, 58L, 53L, 33L, 34L, 25L, 23L, 21L, 24L, 21L, 
6L, 28L, 42L, 102L, 135L, 133L, 114L, 109L, 103L, 84L, 100L, 
93L, 79L, 97L, 63L, 75L, 61L, 64L, 38L, 35L, 23L, 23L, 16L, 22L, 
17L, 25L, 53L, 86L, 116L, 99L, 102L, 85L, 73L, 80L, 69L, 69L, 
80L, 50L, 68L, 49L, 54L, 45L, 35L, 32L, 31L, 17L, 19L, 8L, 12L, 
15L, 27L, 57L, 44L, 58L, 50L, 44L, 43L, 40L, 34L, 43L, 57L, 89L, 
76L, 77L, 68L, 48L, 45L, 33L, 24L, 26L, 16L, 14L, 22L, 16L, 26L, 
47L, 43L, 54L, 50L, 37L, 41L, 47L, 39L, 45L, 62L, 82L, 66L, 54L, 
47L, 49L, 37L, 17L, 24L, 15L, 12L, 10L, 7L, 18L, 25L, 44L, 43L, 
38L, 36L, 50L, 39L, 64L, 55L, 50L, 45L, 73L, 75L, 60L, 45L, 46L, 
45L, 35L, 24L, 18L, 14L, 18L, 27L, 17L, 29L, 34L, 45L, 45L, 47L, 
55L, 34L, 55L, 52L, 47L, 51L, 93L, 76L, 52L, 67L, 44L, 37L, 24L, 
20L, 23L, 18L, 9L, 8L, 11L, 23L, 48L, 48L, 47L, 35L, 45L, 49L, 
45L, 52L, 65L, 36L, 97L, 107L, 67L, 62L, 58L, 33L, 28L, 23L, 
14L, 24L, 18L, 28L, 24L, 45L, 103L, 147L, 131L, 125L, 104L, 98L, 
94L, 83L, 98L, 87L, 82L, 84L, 69L, 58L, 61L, 42L, 33L, 29L, 19L, 
20L, 19L, 20L, 28L, 53L, 98L, 124L, 120L, 122L, 91L, 92L, 89L, 
88L, 63L, 91L, 77L, 74L, 57L, 67L, 55L, 40L, 30L, 16L, 17L, 14L, 
7L, 1L, 5L, 10L, 3L, 42L, 37L, 65L, 53L, 47L, 52L, 76L, 106L, 
91L, 70L, 71L, 62L, 52L, 24L, 12L, 14L, 17L, 10L, 20L, 21L, 30L, 
57L, 49L, 45L, 40L, 51L, 43L, 39L, 56L, 58L, 62L, 95L, 77L, 53L, 
54L, 49L, 31L, 23L, 27L, 16L, 8L, 10L, 14L, 32L, 36L, 50L, 37L, 
47L, 43L, 44L, 46L, 42L, 39L, 53L, 53L, 89L, 75L, 61L, 56L), 
    abandoned = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 2L, 0L, 0L, 0L, 1L, 
    4L, 10L, 34L, 13L, 1L, 2L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 
    0L, 1L, 2L, 4L, 10L, 0L, 1L, 3L, 3L, 8L, 1L, 2L, 4L, 3L, 
    5L, 3L, 3L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 5L, 4L, 6L, 0L, 
    0L, 2L, 0L, 2L, 0L, 0L, 0L, 1L, 1L, 1L, 3L, 3L, 1L, 0L, 1L, 
    0L, 0L, 1L, 1L, 0L, 1L, 4L, 1L, 2L, 1L, 1L, 0L, 1L, 0L, 0L, 
    3L, 0L, 0L, 2L, 1L, 0L, 3L, 2L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 
    3L, 1L, 1L, 1L, 1L, 2L, 0L, 1L, 5L, 4L, 0L, 5L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 3L, 1L, 1L, 0L, 1L, 0L, 
    1L, 1L, 0L, 2L, 7L, 0L, 4L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 2L, 1L, 0L, 0L, 4L, 2L, 0L, 0L, 5L, 19L, 
    9L, 3L, 5L, 1L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 5L, 1L, 1L, 
    4L, 2L, 1L, 3L, 1L, 1L, 0L, 3L, 4L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 4L, 2L, 6L, 1L, 3L, 5L, 8L, 17L, 
    1L, 11L, 0L, 2L, 1L, 4L, 0L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 
    0L, 4L, 4L, 1L, 9L, 4L, 4L, 2L, 1L, 0L, 5L, 0L, 2L, 1L, 0L, 
    1L, 1L, 0L, 1L, 0L, 0L, 2L, 0L, 0L, 0L, 1L, 0L, 3L, 2L, 0L, 
    0L, 1L, 0L, 0L, 0L, 3L, 0L, 1L, 1L, 0L, 0L, 1L, 2L, 1L, 0L, 
    0L, 0L, 0L, 1L, 2L, 1L, 2L, 1L, 0L, 0L, 1L, 2L, 2L, 2L, 4L, 
    1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 2L, 
    0L, 0L, 4L, 0L, 5L, 5L, 5L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 
    1L, 0L, 0L, 0L, 4L, 2L, 0L, 0L, 1L, 3L, 2L, 3L, 0L, 3L, 4L, 
    1L, 2L, 6L, 2L, 0L, 3L, 3L, 0L, 0L, 0L, 2L, 4L, 0L, 0L, 0L, 
    0L, 4L, 1L, 0L, 0L, 2L, 0L, 2L, 3L, 7L, 0L, 10L, 10L, 1L, 
    3L, 1L, 0L, 1L, 0L, 0L, 3L, 1L, 2L, 1L, 0L, 0L, 14L, 13L, 
    7L, 1L, 1L, 2L, 1L, 6L, 10L, 1L, 7L, 4L, 0L, 3L, 0L, 2L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 4L, 10L, 3L, 1L, 2L, 0L, 
    3L, 0L, 5L, 2L, 4L, 2L, 5L, 9L, 5L, 0L, 1L, 0L, 0L, 3L, 0L, 
    4L, 5L, 1L, 2L, 0L, 1L, 0L, 0L, 1L, 1L, 18L, 14L, 1L, 0L, 
    6L, 7L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 2L, 5L, 1L, 0L, 3L, 
    2L, 3L, 3L, 10L, 7L, 22L, 15L, 2L, 0L, 1L, 0L, 0L, 1L, 0L, 
    0L, 0L, 0L, 2L, 1L, 6L, 0L, 1L, 4L, 2L, 1L, 1L, 0L, 1L, 1L, 
    4L, 4L, 0L, 0L), answeredCalls = c(30L, 28L, 15L, 21L, 11L, 
    14L, 18L, 35L, 42L, 36L, 37L, 38L, 54L, 45L, 37L, 51L, 40L, 
    66L, 83L, 68L, 74L, 51L, 39L, 38L, 25L, 21L, 18L, 20L, 7L, 
    14L, 14L, 28L, 37L, 49L, 46L, 31L, 43L, 45L, 39L, 31L, 47L, 
    65L, 81L, 83L, 61L, 65L, 58L, 37L, 20L, 31L, 15L, 25L, 17L, 
    12L, 21L, 42L, 106L, 115L, 134L, 127L, 93L, 107L, 97L, 88L, 
    94L, 74L, 74L, 66L, 65L, 69L, 52L, 51L, 28L, 19L, 23L, 12L, 
    16L, 12L, 17L, 39L, 91L, 115L, 104L, 95L, 65L, 79L, 67L, 
    73L, 64L, 64L, 68L, 70L, 53L, 64L, 48L, 38L, 29L, 16L, 11L, 
    11L, 13L, 15L, 19L, 41L, 54L, 53L, 45L, 50L, 42L, 54L, 54L, 
    44L, 53L, 73L, 81L, 71L, 63L, 72L, 51L, 39L, 29L, 25L, 20L, 
    11L, 15L, 14L, 17L, 36L, 43L, 65L, 54L, 39L, 37L, 49L, 38L, 
    42L, 56L, 69L, 74L, 76L, 73L, 60L, 49L, 40L, 17L, 24L, 14L, 
    15L, 10L, 14L, 18L, 31L, 46L, 42L, 36L, 36L, 38L, 33L, 32L, 
    40L, 44L, 51L, 79L, 84L, 62L, 59L, 48L, 23L, 39L, 29L, 17L, 
    16L, 9L, 9L, 17L, 33L, 36L, 47L, 41L, 42L, 41L, 55L, 39L, 
    39L, 39L, 38L, 73L, 80L, 66L, 58L, 54L, 34L, 22L, 10L, 14L, 
    14L, 16L, 12L, 11L, 27L, 60L, 49L, 58L, 38L, 49L, 36L, 50L, 
    29L, 37L, 61L, 90L, 84L, 58L, 53L, 33L, 34L, 25L, 23L, 21L, 
    24L, 21L, 6L, 28L, 42L, 101L, 131L, 129L, 108L, 108L, 99L, 
    78L, 92L, 75L, 78L, 86L, 62L, 73L, 60L, 60L, 38L, 35L, 23L, 
    23L, 16L, 20L, 17L, 25L, 53L, 82L, 112L, 96L, 93L, 81L, 69L, 
    78L, 67L, 69L, 74L, 50L, 65L, 48L, 54L, 44L, 34L, 32L, 30L, 
    17L, 19L, 6L, 12L, 15L, 27L, 56L, 44L, 55L, 48L, 44L, 43L, 
    39L, 34L, 43L, 57L, 86L, 75L, 76L, 67L, 48L, 45L, 32L, 22L, 
    25L, 16L, 14L, 22L, 16L, 25L, 45L, 42L, 52L, 49L, 37L, 41L, 
    46L, 37L, 43L, 60L, 78L, 65L, 54L, 47L, 49L, 37L, 17L, 24L, 
    15L, 12L, 10L, 7L, 18L, 25L, 43L, 41L, 38L, 36L, 46L, 39L, 
    59L, 50L, 45L, 45L, 72L, 74L, 59L, 45L, 44L, 45L, 34L, 23L, 
    18L, 14L, 17L, 23L, 15L, 29L, 34L, 44L, 42L, 44L, 52L, 34L, 
    52L, 48L, 46L, 49L, 87L, 74L, 52L, 64L, 41L, 37L, 24L, 20L, 
    21L, 14L, 9L, 8L, 11L, 23L, 44L, 47L, 46L, 35L, 42L, 49L, 
    43L, 49L, 58L, 36L, 87L, 97L, 66L, 59L, 56L, 33L, 27L, 23L, 
    14L, 21L, 17L, 26L, 23L, 45L, 103L, 133L, 118L, 118L, 101L, 
    95L, 92L, 80L, 91L, 77L, 81L, 77L, 65L, 58L, 58L, 42L, 31L, 
    29L, 19L, 20L, 19L, 20L, 28L, 53L, 98L, 119L, 110L, 119L, 
    88L, 90L, 89L, 85L, 63L, 86L, 75L, 70L, 55L, 62L, 46L, 35L, 
    30L, 15L, 17L, 14L, 4L, 1L, 1L, 5L, 2L, 40L, 37L, 64L, 53L, 
    46L, 51L, 75L, 88L, 77L, 69L, 71L, 56L, 45L, 24L, 12L, 14L, 
    16L, 10L, 19L, 21L, 30L, 54L, 44L, 42L, 40L, 48L, 41L, 36L, 
    53L, 48L, 55L, 71L, 62L, 51L, 52L, 48L, 31L, 23L, 26L, 16L, 
    8L, 10L, 14L, 28L, 35L, 44L, 37L, 46L, 39L, 42L, 45L, 41L, 
    39L, 52L, 52L, 84L, 71L, 61L, 56L)), row.names = c(NA, 500L
), class = "data.frame")

Что я мутировал: 

hourly$hour <- ifelse(nchar(hourly$hour) == 1, paste0("0", hourly$hour), hourly$hour)

hourly <-
  hourly %>%
  group_by(hour, day) %>%
  summarise(
    offered = mean(totalCalls),
    answered = mean(answeredCalls),
    abandoned = mean(abandoned),
  ) %>%
  mutate(dayHour = paste(day, hour))

У меня проблема с организацией dayHour в правильном порядке дат по оси X: 

ggplot(hourly) +
    geom_line(aes(dayHour, offered, group = 1),
              colour = "red") +
    geom_line(aes(dayHour, answered, group = 1),
              colour = "forestgreen") +
    ggtitle("Hourly Call Volume") +
    theme(axis.text = element_text(angle = 90))

enter image description here

В данный момент он сортируется в алфавитном порядке (т. Е. Понедельник следует за пятницей, когда должна быть суббота и т. Д.).

У меня такой вопрос: как я могу получить значения dayHour, которые будут представлены как объекты даты и правильно отсортированы?

Идея состоит в том, что ось X представляет целую неделю (всего 168 часов), и я позже расскажу об этом графике, но пока мне нужно отсортировать его по фактическому порядку дня.

1 Ответ

1 голос
/ 16 апреля 2019

ggplot по умолчанию сортировка символов по алфавиту.Чтобы обойти это, укажите ось X в качестве коэффициента с упорядоченными уровнями: 

hourly <- hourly %>%
  group_by(hour, day) %>%
  summarise(
    offered = mean(totalCalls),
    answered = mean(answeredCalls),
    abandoned = mean(abandoned),
  ) %>% 
    arrange(factor(day,levels=c("Mon","Tue","Wed","Thu","Fri","Sat","Sun")),desc(day)) %>%
  mutate(dayHour = paste(day, hour))

hourly$dayHour <- factor(hourly$dayHour,levels=hourly$dayHour)

Это дает график, который вы хотите упорядочить по дням: enter image description here

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