Как преобразовать количество в проценты?

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Как преобразовать количество в проценты?

Post author:admin
Запись опубликована:13 апреля, 2023
Post category:Вопросы по программированию

#r #dataframe

#r #фрейм данных

Вопрос:

Я действительно новичок в R, и это, вероятно, действительно основной вопрос. Пожалуйста, посмотрите мой пример кода. Я хотел бы представить процент людей, выполняющих еженедельную работу в течение 24-часового периода времени. Как я могу изменить ось y на проценты вместо итогов?

Я пробовал этот код, но я не уверен в нем:

 df2 <- df3 %>% 
  group_by(day,time) %>% 
  summarise(Total=sum(value)) 
df2$Pct <- df2$Total/ sum(df2$Total)

df2<-structure(list(`Day of the week` = structure(c(1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 
    6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
    6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
    6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
    6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
    6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
    6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 
    7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
    7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
    7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
    7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
    7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
    7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L), .Label = c("Monday", 
    "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"
    ), class = "factor"), time = c(4, 4.25, 4.5, 4.75, 5, 5.25, 5.5, 
    5.75, 6, 6.25, 6.5, 6.75, 7, 7.25, 7.5, 7.75, 8, 8.25, 8.5, 8.75, 
    9, 9.25, 9.5, 9.75, 10, 10.25, 10.5, 10.75, 11, 11.25, 11.5, 
    11.75, 12, 12.25, 12.5, 12.75, 13, 13.25, 13.5, 13.75, 14, 14.25, 
    14.5, 14.75, 15, 15.25, 15.5, 15.75, 16, 16.25, 16.5, 16.75, 
    17, 17.25, 17.5, 17.75, 18, 18.25, 18.5, 18.75, 19, 19.25, 19.5, 
    19.75, 20, 20.25, 20.5, 20.75, 21, 21.25, 21.5, 21.75, 22, 22.25, 
    22.5, 22.75, 23, 23.25, 23.5, 23.75, 24, 24.25, 24.5, 24.75, 
    25, 25.25, 25.5, 25.75, 26, 26.25, 26.5, 26.75, 27, 27.25, 27.5, 
    27.75, 4, 4.25, 4.5, 4.75, 5, 5.25, 5.5, 5.75, 6, 6.25, 6.5, 
    6.75, 7, 7.25, 7.5, 7.75, 8, 8.25, 8.5, 8.75, 9, 9.25, 9.5, 9.75, 
    10, 10.25, 10.5, 10.75, 11, 11.25, 11.5, 11.75, 12, 12.25, 12.5, 
    12.75, 13, 13.25, 13.5, 13.75, 14, 14.25, 14.5, 14.75, 15, 15.25, 
    15.5, 15.75, 16, 16.25, 16.5, 16.75, 17, 17.25, 17.5, 17.75, 
    18, 18.25, 18.5, 18.75, 19, 19.25, 19.5, 19.75, 20, 20.25, 20.5, 
    20.75, 21, 21.25, 21.5, 21.75, 22, 22.25, 22.5, 22.75, 23, 23.25, 
    23.5, 23.75, 24, 24.25, 24.5, 24.75, 25, 25.25, 25.5, 25.75, 
    26, 26.25, 26.5, 26.75, 27, 27.25, 27.5, 27.75, 4, 4.25, 4.5, 
    4.75, 5, 5.25, 5.5, 5.75, 6, 6.25, 6.5, 6.75, 7, 7.25, 7.5, 7.75, 
    8, 8.25, 8.5, 8.75, 9, 9.25, 9.5, 9.75, 10, 10.25, 10.5, 10.75, 
    11, 11.25, 11.5, 11.75, 12, 12.25, 12.5, 12.75, 13, 13.25, 13.5, 
    13.75, 14, 14.25, 14.5, 14.75, 15, 15.25, 15.5, 15.75, 16, 16.25, 
    16.5, 16.75, 17, 17.25, 17.5, 17.75, 18, 18.25, 18.5, 18.75, 
    19, 19.25, 19.5, 19.75, 20, 20.25, 20.5, 20.75, 21, 21.25, 21.5, 
    21.75, 22, 22.25, 22.5, 22.75, 23, 23.25, 23.5, 23.75, 24, 24.25, 
    24.5, 24.75, 25, 25.25, 25.5, 25.75, 26, 26.25, 26.5, 26.75, 
    27, 27.25, 27.5, 27.75, 4, 4.25, 4.5, 4.75, 5, 5.25, 5.5, 5.75, 
    6, 6.25, 6.5, 6.75, 7, 7.25, 7.5, 7.75, 8, 8.25, 8.5, 8.75, 9, 
    9.25, 9.5, 9.75, 10, 10.25, 10.5, 10.75, 11, 11.25, 11.5, 11.75, 
    12, 12.25, 12.5, 12.75, 13, 13.25, 13.5, 13.75, 14, 14.25, 14.5, 
    14.75, 15, 15.25, 15.5, 15.75, 16, 16.25, 16.5, 16.75, 17, 17.25, 
    17.5, 17.75, 18, 18.25, 18.5, 18.75, 19, 19.25, 19.5, 19.75, 
    20, 20.25, 20.5, 20.75, 21, 21.25, 21.5, 21.75, 22, 22.25, 22.5, 
    22.75, 23, 23.25, 23.5, 23.75, 24, 24.25, 24.5, 24.75, 25, 25.25, 
    25.5, 25.75, 26, 26.25, 26.5, 26.75, 27, 27.25, 27.5, 27.75, 
    4, 4.25, 4.5, 4.75, 5, 5.25, 5.5, 5.75, 6, 6.25, 6.5, 6.75, 7, 
    7.25, 7.5, 7.75, 8, 8.25, 8.5, 8.75, 9, 9.25, 9.5, 9.75, 10, 
    10.25, 10.5, 10.75, 11, 11.25, 11.5, 11.75, 12, 12.25, 12.5, 
    12.75, 13, 13.25, 13.5, 13.75, 14, 14.25, 14.5, 14.75, 15, 15.25, 
    15.5, 15.75, 16, 16.25, 16.5, 16.75, 17, 17.25, 17.5, 17.75, 
    18, 18.25, 18.5, 18.75, 19, 19.25, 19.5, 19.75, 20, 20.25, 20.5, 
    20.75, 21, 21.25, 21.5, 21.75, 22, 22.25, 22.5, 22.75, 23, 23.25, 
    23.5, 23.75, 24, 24.25, 24.5, 24.75, 25, 25.25, 25.5, 25.75, 
    26, 26.25, 26.5, 26.75, 27, 27.25, 27.5, 27.75, 4, 4.25, 4.5, 
    4.75, 5, 5.25, 5.5, 5.75, 6, 6.25, 6.5, 6.75, 7, 7.25, 7.5, 7.75, 
    8, 8.25, 8.5, 8.75, 9, 9.25, 9.5, 9.75, 10, 10.25, 10.5, 10.75, 
    11, 11.25, 11.5, 11.75, 12, 12.25, 12.5, 12.75, 13, 13.25, 13.5, 
    13.75, 14, 14.25, 14.5, 14.75, 15, 15.25, 15.5, 15.75, 16, 16.25, 
    16.5, 16.75, 17, 17.25, 17.5, 17.75, 18, 18.25, 18.5, 18.75, 
    19, 19.25, 19.5, 19.75, 20, 20.25, 20.5, 20.75, 21, 21.25, 21.5, 
    21.75, 22, 22.25, 22.5, 22.75, 23, 23.25, 23.5, 23.75, 24, 24.25, 
    24.5, 24.75, 25, 25.25, 25.5, 25.75, 26, 26.25, 26.5, 26.75, 
    27, 27.25, 27.5, 27.75, 4, 4.25, 4.5, 4.75, 5, 5.25, 5.5, 5.75, 
    6, 6.25, 6.5, 6.75, 7, 7.25, 7.5, 7.75, 8, 8.25, 8.5, 8.75, 9, 
    9.25, 9.5, 9.75, 10, 10.25, 10.5, 10.75, 11, 11.25, 11.5, 11.75, 
    12, 12.25, 12.5, 12.75, 13, 13.25, 13.5, 13.75, 14, 14.25, 14.5, 
    14.75, 15, 15.25, 15.5, 15.75, 16, 16.25, 16.5, 16.75, 17, 17.25, 
    17.5, 17.75, 18, 18.25, 18.5, 18.75, 19, 19.25, 19.5, 19.75, 
    20, 20.25, 20.5, 20.75, 21, 21.25, 21.5, 21.75, 22, 22.25, 22.5, 
    22.75, 23, 23.25, 23.5, 23.75, 24, 24.25, 24.5, 24.75, 25, 25.25, 
    25.5, 25.75, 26, 26.25, 26.5, 26.75, 27, 27.25, 27.5, 27.75), 
        Total = c(6, 6, 6, 6, 7, 8, 10, 11, 19, 22, 27, 28, 44, 47, 
        56, 59, 100, 106, 135, 136, 173, 184, 191, 197, 200, 199, 
        203, 201, 198, 199, 202, 202, 193, 189, 182, 183, 155, 153, 
        153, 157, 183, 185, 185, 185, 185, 182, 173, 172, 158, 158, 
        140, 139, 125, 118, 108, 101, 68, 66, 54, 50, 37, 38, 32, 
        30, 26, 26, 26, 25, 24, 23, 23, 23, 25, 23, 21, 20, 15, 14, 
        14, 15, 11, 11, 10, 10, 10, 9, 9, 9, 10, 10, 10, 10, 10, 
        10, 9, 9, 8, 8, 8, 8, 10, 10, 14, 15, 20, 20, 27, 27, 45, 
        47, 59, 62, 104, 110, 137, 140, 179, 186, 202, 203, 206, 
        209, 209, 210, 205, 207, 211, 210, 200, 199, 194, 197, 169, 
        166, 176, 180, 193, 196, 197, 197, 192, 190, 180, 176, 162, 
        162, 153, 148, 124, 122, 106, 97, 64, 61, 57, 54, 38, 37, 
        38, 34, 32, 33, 31, 28, 24, 24, 22, 21, 20, 20, 17, 16, 13, 
        12, 10, 10, 9, 9, 8, 8, 8, 7, 8, 9, 9, 8, 8, 8, 8, 7, 7, 
        8, 7, 7, 7, 7, 10, 11, 14, 16, 22, 24, 27, 28, 45, 48, 63, 
        66, 104, 116, 141, 145, 191, 198, 209, 210, 215, 216, 218, 
        216, 216, 218, 221, 221, 206, 204, 194, 194, 180, 179, 184, 
        186, 206, 209, 208, 207, 204, 203, 196, 194, 179, 182, 168, 
        164, 131, 127, 115, 106, 66, 60, 57, 52, 39, 36, 36, 33, 
        32, 31, 29, 29, 22, 21, 18, 17, 16, 15, 14, 14, 12, 12, 12, 
        11, 9, 9, 8, 8, 7, 7, 7, 6, 6, 6, 6, 6, 6, 5, 5, 5, 5, 5, 
        5, 5, 7, 7, 9, 9, 18, 20, 21, 21, 38, 39, 58, 61, 108, 116, 
        138, 141, 179, 185, 196, 196, 200, 205, 205, 201, 202, 204, 
        204, 202, 191, 188, 184, 188, 170, 172, 180, 178, 190, 191, 
        196, 195, 193, 194, 184, 180, 165, 166, 150, 149, 128, 123, 
        108, 99, 66, 66, 60, 55, 36, 36, 33, 34, 35, 35, 31, 31, 
        22, 22, 22, 22, 17, 17, 15, 14, 12, 12, 11, 10, 10, 10, 10, 
        10, 9, 8, 8, 8, 8, 8, 8, 7, 7, 7, 7, 7, 6, 6, 7, 7, 8, 8, 
        12, 12, 21, 21, 25, 27, 43, 44, 56, 59, 100, 110, 129, 132, 
        166, 172, 187, 189, 189, 191, 193, 192, 188, 194, 193, 192, 
        173, 173, 172, 176, 159, 154, 157, 163, 166, 167, 170, 169, 
        162, 161, 157, 156, 141, 142, 130, 125, 92, 91, 73, 68, 46, 
        47, 40, 35, 24, 23, 21, 19, 20, 20, 20, 21, 19, 19, 17, 17, 
        20, 19, 18, 18, 11, 11, 12, 11, 10, 10, 10, 10, 9, 7, 7, 
        7, 6, 6, 7, 7, 7, 7, 7, 6, 5, 6, 7, 7, 10, 9, 11, 12, 13, 
        14, 14, 15, 20, 20, 20, 21, 26, 26, 28, 29, 32, 33, 40, 40, 
        38, 37, 43, 43, 44, 43, 43, 44, 43, 41, 40, 39, 39, 40, 39, 
        38, 37, 37, 39, 41, 33, 34, 37, 36, 34, 34, 35, 33, 28, 28, 
        24, 24, 19, 19, 19, 18, 18, 19, 17, 15, 15, 15, 15, 15, 14, 
        14, 15, 15, 14, 13, 13, 13, 12, 11, 10, 9, 8, 8, 8, 6, 4, 
        4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 6, 7, 8, 8, 
        7, 8, 8, 9, 14, 14, 15, 16, 18, 18, 17, 16, 18, 18, 20, 20, 
        21, 22, 25, 25, 30, 30, 29, 28, 25, 24, 23, 23, 22, 21, 21, 
        21, 20, 21, 23, 23, 23, 22, 21, 23, 19, 18, 19, 18, 19, 19, 
        21, 21, 16, 17, 16, 16, 17, 17, 19, 19, 19, 19, 20, 20, 15, 
        15, 17, 17, 18, 17, 16, 16, 13, 12, 12, 12, 11, 11, 10, 10, 
        9, 9, 9, 9, 9, 8, 8, 8, 8, 8, 8, 8)), row.names = c(NA, -672L
    ), class = c("grouped_df", "tbl_df", "tbl", "data.frame"), groups = structure(list(
        day = structure(1:7, .Label = c("Monday", "Tuesday", "Wednesday", 
        "Thursday", "Friday", "Saturday", "Sunday"), class = "factor"), 
        .rows = list(1:96, 97:192, 193:288, 289:384, 385:480, 481:576, 
            577:672)), row.names = c(NA, -7L), class = c("tbl_df", 
    "tbl", "data.frame"), .drop = TRUE))

1. Если человек работает несколько раз по 15 минут в день, учитывается ли этот человек за каждую четверть часа? Если это так, то при суммировании за день в знаменателе получается количество 15-минутных интервалов, отработанных за день. Если вам нужен процент от people , а не приращения по времени, вы бы использовали максимальное значение Total за 7-дневный период. Пожалуйста, опишите, как следует вычислять знаменатель в процентах.

Ответ №1:

Диаграмма в другом ответе иллюстрирует процент людей, работающих с каждым 15-минутным шагом в день, учитывая общее количество 15-минутных приращений, отработанных в течение дня.

Если ось y должна представлять процент людей, работающих с любым 15-минутным интервалом в течение недели, знаменателем должно быть max(Total) , максимальное количество людей, работающих с любым 15-минутным интервалом в течение 7-дневного периода времени в данных.

Другим подходом было бы использовать максимальное значение по дням, чтобы в течение 15-минутного приращения наибольшее количество людей, работавших в этот день, отображалось на графике как 100%.

Суммируя данные, мы можем увидеть, как будут рассчитаны знаменатели.

 df2 %>% 
    group_by(`Day of the week`) %>% 
    summarise(.,max = max(Total))

… и вывод:

 `summarise()` ungrouping output (override with `.groups` argument)
# A tibble: 7 x 2
  `Day of the week`   max
  <fct>             <dbl>
1 Monday              203
2 Tuesday             211
3 Wednesday           221
4 Thursday            205
5 Friday              194
6 Saturday             44
7 Sunday               30

График, нормированный на максимальное количество работников в день, выглядит следующим образом, учитывая график, который был опубликован в исходном ответе:

 df2 %>% group_by(`Day of the week`) %>%
     mutate(Percent = Total / max(Total)) -> df3

ggplot(df3,aes(x=time,y=Percent,color=`Day of the week`)) 
     geom_line()  
     scale_y_continuous(labels = scales::percent)

… и вывод:

График, нормированный на максимальное количество работников за все дни, выглядит следующим образом.

 df2  %>% ungroup() %>%
     mutate(Percent = Total / max(Total)) -> df3

ggplot(df3,aes(x=time,y=Percent,color=`Day of the week`)) 
     geom_line()  
     scale_y_continuous(labels = scales::percent)

…и выходные данные, где мы можем четко видеть, что меньше людей работало по выходным.

Ответ №2:

Я бы предложил следующий подход. Если вы группируете по дням и времени, все проценты равны 1. Если сгруппировать по дням, вы получите это:

 library(dplyr)
library(ggplot2)

#Compute
f2 %>% group_by(`Day of the week`) %>% mutate(Percentage=Total/sum(Total)) -> f3
#Plot
ggplot(f3,aes(x=time,y=Percentage,color=`Day of the week`)) 
  geom_line() 
  scale_y_continuous(labels = scales::percent)

Вывод:

Вопрос:

Комментарии:

Ответ №1:

Ответ №2:

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