Forcats 重新排序不适用于 ggplot
Forcats reordering not working for ggplot
我有以下代码为我的数据绘制一个简单的棒棒糖图表：
p <-
data %>% mutate(Activity_Name = fct_reorder(Activity_Name, count)) %>%
ggplot(aes(x = Activity_Name, y = count)) +
geom_segment(aes(
x = Activity_Name,
xend = Activity_Name,
y = 0,
yend = count
),
color = "skyblue") +
geom_point(color = "#F2F7F2",
size = 5,
alpha = 0.6) +
theme_light() +
scale_y_log10() +
coord_flip()
我想按 Activity Name 的计数降序排列。尽管我已将其包含在代码中，但下面的代码会生成以下图表：
[![在此处输入图片描述][1]][1]
我做错了什么，为什么会失败？我的 dput 分享如下：
D放这里
structure(list(Day = c("01-01-2021", "01-01-2021", "01-01-2021",
"01-01-2021", "01-01-2021", "01-01-2021", "01-01-2021", "01-01-2021",
"01-01-2021", "01-01-2021", "01-01-2021", "01-01-2021", "01-01-2021",
"01-01-2021", "01-01-2021", "01-01-2021", "01-01-2021", "01-01-2021",
"01-01-2021", "01-01-2021", "01-01-2021", "01-01-2021", "01-01-2021",
"01-01-2021", "01-02-2021", "01-02-2021", "01-02-2021", "01-02-2021",
"01-02-2021", "01-02-2021", "01-02-2021", "01-02-2021", "01-02-2021",
"01-02-2021", "01-02-2021", "01-02-2021", "01-02-2021", "01-02-2021",
"01-02-2021", "01-02-2021", "01-02-2021", "01-02-2021", "01-02-2021",
"01-02-2021", "01-02-2021", "01-02-2021", "01-02-2021", "01-02-2021",
"01-03-2021", "01-03-2021", "01-03-2021", "01-03-2021", "01-03-2021",
"01-03-2021", "01-03-2021", "01-03-2021", "01-03-2021", "01-03-2021",
"01-03-2021", "01-03-2021", "01-03-2021", "01-03-2021", "01-03-2021",
"01-03-2021", "01-03-2021", "01-03-2021", "01-03-2021", "01-03-2021",
"01-03-2021", "01-03-2021", "01-03-2021", "01-03-2021", "01-04-2021",
"01-04-2021", "01-04-2021", "01-04-2021", "01-04-2021", "01-04-2021",
"01-04-2021", "01-04-2021", "01-04-2021", "01-04-2021", "01-04-2021",
"01-04-2021", "01-04-2021", "01-04-2021", "01-04-2021", "01-04-2021",
"01-04-2021", "01-04-2021", "01-04-2021", "01-04-2021", "01-04-2021",
"01-04-2021", "01-04-2021", "01-04-2021", "01-05-2021", "01-05-2021",
"01-05-2021", "01-05-2021", "01-05-2021", "01-05-2021", "01-05-2021",
"01-05-2021", "01-05-2021", "01-05-2021", "01-05-2021", "01-05-2021",
"01-05-2021", "01-05-2021", "01-05-2021", "01-05-2021", "01-05-2021",
"01-05-2021", "01-05-2021", "01-05-2021", "01-05-2021", "01-05-2021",
"01-05-2021", "01-05-2021", "01-06-2021", "01-06-2021", "01-06-2021",
"01-06-2021", "01-06-2021", "01-06-2021", "01-06-2021", "01-06-2021",
"01-06-2021", "01-06-2021", "01-06-2021", "01-06-2021", "01-06-2021",
"01-06-2021", "01-06-2021", "01-06-2021", "01-06-2021", "01-06-2021",
"01-06-2021", "01-06-2021", "01-06-2021", "01-06-2021", "01-06-2021",
"01-06-2021", "01-07-2021", "01-07-2021", "01-07-2021", "01-07-2021",
"01-07-2021", "01-07-2021", "01-07-2021", "01-07-2021", "01-07-2021",
"01-07-2021", "01-07-2021", "01-07-2021", "01-07-2021", "01-07-2021",
"01-07-2021", "01-07-2021", "01-07-2021", "01-07-2021", "01-07-2021",
"01-07-2021", "01-07-2021", "01-07-2021", "01-07-2021", "01-07-2021",
"01-08-2021", "01-08-2021", "01-08-2021", "01-08-2021", "01-08-2021",
"01-08-2021", "01-08-2021", "01-08-2021", "01-08-2021", "01-08-2021",
"01-08-2021", "01-08-2021", "01-08-2021", "01-08-2021", "01-08-2021",
"01-08-2021", "01-08-2021", "01-08-2021", "01-08-2021", "01-08-2021",
"01-08-2021", "01-08-2021", "01-08-2021", "01-08-2021", "01-09-2021",
"01-09-2021", "01-09-2021", "01-09-2021", "01-09-2021", "01-09-2021",
"01-09-2021", "01-09-2021", "01-09-2021", "01-09-2021", "01-09-2021",
"01-09-2021", "01-09-2021", "01-09-2021", "01-09-2021", "01-09-2021",
"01-09-2021", "01-09-2021", "01-09-2021", "01-09-2021", "01-09-2021",
"01-09-2021", "01-09-2021", "01-09-2021", "01-10-2021", "01-10-2021",
"01-10-2021", "01-10-2021", "01-10-2021", "01-10-2021", "01-10-2021",
"01-10-2021", "01-10-2021", "01-10-2021", "01-10-2021", "01-10-2021",
"01-10-2021", "01-10-2021", "01-10-2021", "01-10-2021", "01-10-2021",
"01-10-2021", "01-10-2021", "01-10-2021", "01-10-2021", "01-10-2021",
"01-10-2021", "01-10-2021", "01-11-2021", "01-11-2021", "01-11-2021",
"01-11-2021", "01-11-2021", "01-11-2021", "01-11-2021", "01-11-2021",
"01-11-2021", "01-11-2021", "01-11-2021", "01-11-2021", "01-11-2021",
"01-11-2021", "01-11-2021", "01-11-2021", "01-11-2021", "01-11-2021",
"01-11-2021", "01-11-2021", "01-11-2021", "01-11-2021", "01-11-2021",
"01-11-2021", "01-12-2021", "01-12-2021", "01-12-2021", "01-12-2021",
"01-12-2021", "01-12-2021", "01-12-2021", "01-12-2021", "01-12-2021",
"01-12-2021", "01-12-2021", "01-12-2021", "01-12-2021", "01-12-2021",
"01-12-2021", "01-12-2021", "01-12-2021", "01-12-2021", "01-12-2021",
"01-12-2021", "01-12-2021", "01-12-2021", "01-12-2021", "01-12-2021",
"01-13-2021", "01-13-2021", "01-13-2021", "01-13-2021", "01-13-2021",
"01-13-2021", "01-13-2021", "01-13-2021", "01-13-2021", "01-13-2021",
"01-13-2021", "01-13-2021", "01-13-2021", "01-13-2021", "01-13-2021",
"01-13-2021", "01-13-2021", "01-13-2021", "01-13-2021", "01-13-2021",
"01-13-2021", "01-13-2021", "01-13-2021", "01-13-2021", "01-14-2021",
"01-14-2021", "01-14-2021", "01-14-2021", "01-14-2021", "01-14-2021",
"01-14-2021", "01-14-2021", "01-14-2021", "01-14-2021", "01-14-2021",
"01-14-2021", "01-14-2021", "01-14-2021", "01-14-2021", "01-14-2021",
"01-14-2021", "01-14-2021", "01-14-2021", "01-14-2021", "01-14-2021",
"01-14-2021", "01-14-2021", "01-14-2021", "01-15-2021", "01-15-2021",
"01-15-2021", "01-15-2021", "01-15-2021", "01-15-2021", "01-15-2021",
"01-15-2021", "01-15-2021", "01-15-2021", "01-15-2021", "01-15-2021",
"01-15-2021", "01-15-2021", "01-15-2021", "01-15-2021", "01-15-2021",
"01-15-2021", "01-15-2021", "01-15-2021", "01-15-2021", "01-15-2021",
"01-15-2021", "01-15-2021"), Hour = c("00:00", "01:00", "02:00",
"03:00", "04:00", "05:00", "06:00", "07:00", "08:00", "09:00",
"10:00", "11:00", "12:00", "13:00", "14:00", "15:00", "16:00",
"17:00", "18:00", "19:00", "20:00", "21:00", "22:00", "23:00",
"00:00", "01:00", "02:00", "03:00", "04:00", "05:00", "06:00",
"07:00", "08:00", "09:00", "10:00", "11:00", "12:00", "13:00",
"14:00", "15:00", "16:00", "17:00", "18:00", "19:00", "20:00",
"21:00", "22:00", "23:00", "00:00", "01:00", "02:00", "03:00",
"04:00", "05:00", "06:00", "07:00", "08:00", "09:00", "10:00",
"11:00", "12:00", "13:00", "14:00", "15:00", "16:00", "17:00",
"18:00", "19:00", "20:00", "21:00", "22:00", "23:00", "00:00",
"01:00", "02:00", "03:00", "04:00", "05:00", "06:00", "07:00",
"08:00", "09:00", "10:00", "11:00", "12:00", "13:00", "14:00",
"15:00", "16:00", "17:00", "18:00", "19:00", "20:00", "21:00",
"22:00", "23:00", "00:00", "01:00", "02:00", "03:00", "04:00",
"05:00", "06:00", "07:00", "08:00", "09:00", "10:00", "11:00",
"12:00", "13:00", "14:00", "15:00", "16:00", "17:00", "18:00",
"19:00", "20:00", "21:00", "22:00", "23:00", "00:00", "01:00",
"02:00", "03:00", "04:00", "05:00", "06:00", "07:00", "08:00",
"09:00", "10:00", "11:00", "12:00", "13:00", "14:00", "15:00",
"16:00", "17:00", "18:00", "19:00", "20:00", "21:00", "22:00",
"23:00", "00:00", "01:00", "02:00", "03:00", "04:00", "05:00",
"06:00", "07:00", "08:00", "09:00", "10:00", "11:00", "12:00",
"13:00", "14:00", "15:00", "16:00", "17:00", "18:00", "19:00",
"20:00", "21:00", "22:00", "23:00", "00:00", "01:00", "02:00",
"03:00", "04:00", "05:00", "06:00", "07:00", "08:00", "09:00",
"10:00", "11:00", "12:00", "13:00", "14:00", "15:00", "16:00",
"17:00", "18:00", "19:00", "20:00", "21:00", "22:00", "23:00",
"00:00", "01:00", "02:00", "03:00", "04:00", "05:00", "06:00",
"07:00", "08:00", "09:00", "10:00", "11:00", "12:00", "13:00",
"14:00", "15:00", "16:00", "17:00", "18:00", "19:00", "20:00",
"21:00", "22:00", "23:00", "00:00", "01:00", "02:00", "03:00",
"04:00", "05:00", "06:00", "07:00", "08:00", "09:00", "10:00",
"11:00", "12:00", "13:00", "14:00", "15:00", "16:00", "17:00",
"18:00", "19:00", "20:00", "21:00", "22:00", "23:00", "00:00",
"01:00", "02:00", "03:00", "04:00", "05:00", "06:00", "07:00",
"08:00", "09:00", "10:00", "11:00", "12:00", "13:00", "14:00",
"15:00", "16:00", "17:00", "18:00", "19:00", "20:00", "21:00",
"22:00", "23:00", "00:00", "01:00", "02:00", "03:00", "04:00",
"05:00", "06:00", "07:00", "08:00", "09:00", "10:00", "11:00",
"12:00", "13:00", "14:00", "15:00", "16:00", "17:00", "18:00",
"19:00", "20:00", "21:00", "22:00", "23:00", "00:00", "01:00",
"02:00", "03:00", "04:00", "05:00", "06:00", "07:00", "08:00",
"09:00", "10:00", "11:00", "12:00", "13:00", "14:00", "15:00",
"16:00", "17:00", "18:00", "19:00", "20:00", "21:00", "22:00",
"23:00", "00:00", "01:00", "02:00", "03:00", "04:00", "05:00",
"06:00", "07:00", "08:00", "09:00", "10:00", "11:00", "12:00",
"13:00", "14:00", "15:00", "16:00", "17:00", "18:00", "19:00",
"20:00", "21:00", "22:00", "23:00", "00:00", "01:00", "02:00",
"03:00", "04:00", "05:00", "06:00", "07:00", "08:00", "09:00",
"10:00", "11:00", "12:00", "13:00", "14:00", "15:00", "16:00",
"17:00", "18:00", "19:00", "20:00", "21:00", "22:00", "23:00"
), Activity = c("1", "1", "1", "1", "1", "1", "1", "1", "23",
"2", "23", "23", "23", "23", "8", "8", "15", "15", "23", "23",
"23", "2", "23", "23", "1", "1", "1", "1", "1", "1", "1", "10",
"23", "10", "23", "23", "23", "23", "23", "8", "8", "23", "23",
"23", "23", "23", "23", "7", "1", "1", "1", "1", "1", "1", "1",
"1", "1", "23", "23", "23", "23", "23", "23", "8", "4", "4",
"15", "15", "15", "2", "2", "23", "7", "1", "1", "1", "1", "1",
"1", "15", "15", "15", "23", "23", "23", "23", "23", "23", "7.7",
"7.7", "7.7", "7.7", "2", "15", "15", "15", "1", "1", "1", "1",
"1", "1", "1", "15", "15", "15", "23", "23", "23", "23", "23",
"23", "23", "15", "15", "23", "17.1", "17.1", "23", "23", "23",
"4", "4", "1", "1", "1", "1", "15", "15", "23", "23", "23", "23",
"23", "8", "8", "8", "8", "15", "2", "15", "15", "23", "1", "1",
"1", "1", "1", "1", "1", "1", "15", "15", "14", "14", "14", "14",
"14", "11", "11", "11", "11", "15", "15", "15", "15", "15", "1",
"1", "1", "1", "1", "1", "1", "1", "1", "7.5", "7.5", "7.5",
"7.5", "7.5", "7.5", "22", "22", "22", "22", "22", "7.5", "7.5",
"7.5", "7.5", "1", "1", "1", "1", "1", "1", "1", "1", "1", "22",
"22", "7.5", "7.5", "7.5", "7.5", "7.5", "16", "8", "8", "15",
"15", "2", "2", "7.5", "7.5", "1", "1", "1", "1", "1", "1", "1",
"1", "15", "15", "15", "15", "15", "2", "15", "16", "19", "19",
"19", "19", "2", "15", "15", "15", "1", "1", "1", "1", "1", "1",
"1", "1", "1", "5", "5", "16", "16", "16", "1", "1", "1", "1",
"15", "17", "17", "8", "8", "17", "17", "17", "1", "1", "1",
"1", "1", "1", "2", "10", "10", "5", "5", "5", "5", "15", "15",
"23", "23", "23", "23", "23", "23", "16", "1", "1", "1", "1",
"1", "1", "1", "1", "1", "5", "5", "5", "5", "2", "5", "5", "22",
"22", "22", "22", "2", "17", "17", "17", "1", "1", "1", "1",
"1", "1", "1", "19", "19", "19", "19", "19", "15", "2", "1",
"1", "1", "7.5", "7.5", "7.5", "2", "23", "23", "1", "1", "1",
"1", "1", "1", "1", "1", "1", "2", "19", "5", "5", "2", "5",
"5", "5", "5", "16", "16", "7.5", "2", "23", "23", "23"), Activity_Name = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 12L, 10L, 12L, 12L, 12L, 12L, 18L,
18L, 5L, 5L, 12L, 12L, 12L, 10L, 12L, 12L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 2L, 12L, 2L, 12L, 12L, 12L, 12L, 12L, 18L, 18L, 12L,
12L, 12L, 12L, 12L, 12L, 15L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 12L, 12L, 12L, 12L, 12L, 12L, 18L, 13L, 13L, 5L, 5L, 5L,
10L, 10L, 12L, 15L, 1L, 1L, 1L, 1L, 1L, 1L, 5L, 5L, 5L, 12L,
12L, 12L, 12L, 12L, 12L, 17L, 17L, 17L, 17L, 10L, 5L, 5L, 5L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 5L, 5L, 5L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 5L, 5L, 12L, 8L, 8L, 12L, 12L, 12L, 13L, 13L, 1L, 1L,
1L, 1L, 5L, 5L, 12L, 12L, 12L, 12L, 12L, 18L, 18L, 18L, 18L,
5L, 10L, 5L, 5L, 12L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 5L, 5L,
4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 16L, 16L, 16L, 16L, 16L, 16L, 11L,
11L, 11L, 11L, 11L, 16L, 16L, 16L, 16L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 11L, 11L, 16L, 16L, 16L, 16L, 16L, 6L, 18L, 18L,
5L, 5L, 10L, 10L, 16L, 16L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 5L,
5L, 5L, 5L, 5L, 10L, 5L, 6L, 9L, 9L, 9L, 9L, 10L, 5L, 5L, 5L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 14L, 14L, 6L, 6L, 6L, 1L,
1L, 1L, 1L, 5L, 7L, 7L, 18L, 18L, 7L, 7L, 7L, 1L, 1L, 1L, 1L,
1L, 1L, 10L, 2L, 2L, 14L, 14L, 14L, 14L, 5L, 5L, 12L, 12L, 12L,
12L, 12L, 12L, 6L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 14L, 14L,
14L, 14L, 10L, 14L, 14L, 11L, 11L, 11L, 11L, 10L, 7L, 7L, 7L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 9L, 9L, 9L, 9L, 9L, 5L, 10L, 1L,
1L, 1L, 16L, 16L, 16L, 10L, 12L, 12L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 10L, 9L, 14L, 14L, 10L, 14L, 14L, 14L, 14L, 6L, 6L,
16L, 10L, 12L, 12L, 12L), .Label = c("Sleeping", "Internet Browsing",
"IRL Social Time", "Travelling", "Waste/Down Time", "Terrace Time",
"Other Productive Activities", "TV", "Sports & Exercise", "Eating",
"Shopping", "Coding", "Online Meetings", "Studying", "Audiobook",
"Sundaram Playing", "Walking", "Netflix"), class = "factor"),
count = c(122L, 122L, 122L, 122L, 122L, 122L, 122L, 122L,
63L, 18L, 63L, 63L, 63L, 63L, 13L, 13L, 43L, 43L, 63L, 63L,
63L, 18L, 63L, 63L, 122L, 122L, 122L, 122L, 122L, 122L, 122L,
4L, 63L, 4L, 63L, 63L, 63L, 63L, 63L, 13L, 13L, 63L, 63L,
63L, 63L, 63L, 63L, 2L, 122L, 122L, 122L, 122L, 122L, 122L,
122L, 122L, 122L, 63L, 63L, 63L, 63L, 63L, 63L, 13L, 4L,
4L, 43L, 43L, 43L, 18L, 18L, 63L, 2L, 122L, 122L, 122L, 122L,
122L, 122L, 43L, 43L, 43L, 63L, 63L, 63L, 63L, 63L, 63L,
4L, 4L, 4L, 4L, 18L, 43L, 43L, 43L, 122L, 122L, 122L, 122L,
122L, 122L, 122L, 43L, 43L, 43L, 63L, 63L, 63L, 63L, 63L,
63L, 63L, 43L, 43L, 63L, 2L, 2L, 63L, 63L, 63L, 4L, 4L, 122L,
122L, 122L, 122L, 43L, 43L, 63L, 63L, 63L, 63L, 63L, 13L,
13L, 13L, 13L, 43L, 18L, 43L, 43L, 63L, 122L, 122L, 122L,
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-360L), groups = structure(list(Activity = c("1", "10", "11",
"14", "15", "16", "17", "17.1", "19", "2", "22", "23", "4", "5",
"7", "7.5", "7.7", "8"), .rows = structure(list(c(1L, 2L, 3L,
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"tbl", "data.frame"))
试试这个。 count的数据类型有问题，改成dataframe可以缓解问题：
#Data
data <- as.data.frame(data)
#Plot
data %>%
arrange(count,Activity_Name) %>%
mutate(Activity_Name=as.character(Activity_Name)) %>%
mutate(Activity_Name=factor(Activity_Name,levels = unique(Activity_Name),
ordered = T)) %>%
ggplot(aes(x = Activity_Name, y = count)) +
geom_segment(aes(
x = Activity_Name,
xend = Activity_Name,
y = 0,
yend = count
),
color = "skyblue") +
geom_point(color = "blue",
size = 5,
alpha = 0.6) +
theme_light() +
scale_y_log10() +
coord_flip()
输出（我改变了可重现图的颜色）：
这是因为您的数据是分组的，所以 mutate 中的 fct_reorder 试图在组内而不是整个数据框内工作。只需添加一个 ungroup 它应该是所需的输出
输出的第 2 行显示数据已分组
data
# # A tibble: 360 x 5
# # Groups: Activity [18]
# Day Hour Activity Activity_Name count
# <chr> <chr> <chr> <fct> <int>
# 1 01-01-2021 00:00 1 Sleeping 122
# 2 01-01-2021 01:00 1 Sleeping 122
# 3 01-01-2021 02:00 1 Sleeping 122
# 4 01-01-2021 03:00 1 Sleeping 122
# 5 01-01-2021 04:00 1 Sleeping 122
# 6 01-01-2021 05:00 1 Sleeping 122
# 7 01-01-2021 06:00 1 Sleeping 122
# 8 01-01-2021 07:00 1 Sleeping 122
# 9 01-01-2021 08:00 23 Coding 63
# 10 01-01-2021 09:00 2 Eating 18
# # … with 350 more rows
添加取消分组：
data %>%
ungroup %>%
mutate(Activity_Name = fct_reorder(Activity_Name, count)) %>%
ggplot(aes(x = Activity_Name, y = count)) +
geom_segment(aes(
x = Activity_Name,
xend = Activity_Name,
y = 0,
yend = count
),
color = "skyblue") +
geom_point(color = "#F2F7F2",
size = 5,
alpha = 0.6) +
theme_light() +
scale_y_log10() +
coord_flip()
我有以下代码为我的数据绘制一个简单的棒棒糖图表：
p <-
data %>% mutate(Activity_Name = fct_reorder(Activity_Name, count)) %>%
ggplot(aes(x = Activity_Name, y = count)) +
geom_segment(aes(
x = Activity_Name,
xend = Activity_Name,
y = 0,
yend = count
),
color = "skyblue") +
geom_point(color = "#F2F7F2",
size = 5,
alpha = 0.6) +
theme_light() +
scale_y_log10() +
coord_flip()
我想按 Activity Name 的计数降序排列。尽管我已将其包含在代码中，但下面的代码会生成以下图表：
[![在此处输入图片描述][1]][1]
我做错了什么，为什么会失败？我的 dput 分享如下：
D放这里
structure(list(Day = c("01-01-2021", "01-01-2021", "01-01-2021",
"01-01-2021", "01-01-2021", "01-01-2021", "01-01-2021", "01-01-2021",
"01-01-2021", "01-01-2021", "01-01-2021", "01-01-2021", "01-01-2021",
"01-01-2021", "01-01-2021", "01-01-2021", "01-01-2021", "01-01-2021",
"01-01-2021", "01-01-2021", "01-01-2021", "01-01-2021", "01-01-2021",
"01-01-2021", "01-02-2021", "01-02-2021", "01-02-2021", "01-02-2021",
"01-02-2021", "01-02-2021", "01-02-2021", "01-02-2021", "01-02-2021",
"01-02-2021", "01-02-2021", "01-02-2021", "01-02-2021", "01-02-2021",
"01-02-2021", "01-02-2021", "01-02-2021", "01-02-2021", "01-02-2021",
"01-02-2021", "01-02-2021", "01-02-2021", "01-02-2021", "01-02-2021",
"01-03-2021", "01-03-2021", "01-03-2021", "01-03-2021", "01-03-2021",
"01-03-2021", "01-03-2021", "01-03-2021", "01-03-2021", "01-03-2021",
"01-03-2021", "01-03-2021", "01-03-2021", "01-03-2021", "01-03-2021",
"01-03-2021", "01-03-2021", "01-03-2021", "01-03-2021", "01-03-2021",
"01-03-2021", "01-03-2021", "01-03-2021", "01-03-2021", "01-04-2021",
"01-04-2021", "01-04-2021", "01-04-2021", "01-04-2021", "01-04-2021",
"01-04-2021", "01-04-2021", "01-04-2021", "01-04-2021", "01-04-2021",
"01-04-2021", "01-04-2021", "01-04-2021", "01-04-2021", "01-04-2021",
"01-04-2021", "01-04-2021", "01-04-2021", "01-04-2021", "01-04-2021",
"01-04-2021", "01-04-2021", "01-04-2021", "01-05-2021", "01-05-2021",
"01-05-2021", "01-05-2021", "01-05-2021", "01-05-2021", "01-05-2021",
"01-05-2021", "01-05-2021", "01-05-2021", "01-05-2021", "01-05-2021",
"01-05-2021", "01-05-2021", "01-05-2021", "01-05-2021", "01-05-2021",
"01-05-2021", "01-05-2021", "01-05-2021", "01-05-2021", "01-05-2021",
"01-05-2021", "01-05-2021", "01-06-2021", "01-06-2021", "01-06-2021",
"01-06-2021", "01-06-2021", "01-06-2021", "01-06-2021", "01-06-2021",
"01-06-2021", "01-06-2021", "01-06-2021", "01-06-2021", "01-06-2021",
"01-06-2021", "01-06-2021", "01-06-2021", "01-06-2021", "01-06-2021",
"01-06-2021", "01-06-2021", "01-06-2021", "01-06-2021", "01-06-2021",
"01-06-2021", "01-07-2021", "01-07-2021", "01-07-2021", "01-07-2021",
"01-07-2021", "01-07-2021", "01-07-2021", "01-07-2021", "01-07-2021",
"01-07-2021", "01-07-2021", "01-07-2021", "01-07-2021", "01-07-2021",
"01-07-2021", "01-07-2021", "01-07-2021", "01-07-2021", "01-07-2021",
"01-07-2021", "01-07-2021", "01-07-2021", "01-07-2021", "01-07-2021",
"01-08-2021", "01-08-2021", "01-08-2021", "01-08-2021", "01-08-2021",
"01-08-2021", "01-08-2021", "01-08-2021", "01-08-2021", "01-08-2021",
"01-08-2021", "01-08-2021", "01-08-2021", "01-08-2021", "01-08-2021",
"01-08-2021", "01-08-2021", "01-08-2021", "01-08-2021", "01-08-2021",
"01-08-2021", "01-08-2021", "01-08-2021", "01-08-2021", "01-09-2021",
"01-09-2021", "01-09-2021", "01-09-2021", "01-09-2021", "01-09-2021",
"01-09-2021", "01-09-2021", "01-09-2021", "01-09-2021", "01-09-2021",
"01-09-2021", "01-09-2021", "01-09-2021", "01-09-2021", "01-09-2021",
"01-09-2021", "01-09-2021", "01-09-2021", "01-09-2021", "01-09-2021",
"01-09-2021", "01-09-2021", "01-09-2021", "01-10-2021", "01-10-2021",
"01-10-2021", "01-10-2021", "01-10-2021", "01-10-2021", "01-10-2021",
"01-10-2021", "01-10-2021", "01-10-2021", "01-10-2021", "01-10-2021",
"01-10-2021", "01-10-2021", "01-10-2021", "01-10-2021", "01-10-2021",
"01-10-2021", "01-10-2021", "01-10-2021", "01-10-2021", "01-10-2021",
"01-10-2021", "01-10-2021", "01-11-2021", "01-11-2021", "01-11-2021",
"01-11-2021", "01-11-2021", "01-11-2021", "01-11-2021", "01-11-2021",
"01-11-2021", "01-11-2021", "01-11-2021", "01-11-2021", "01-11-2021",
"01-11-2021", "01-11-2021", "01-11-2021", "01-11-2021", "01-11-2021",
"01-11-2021", "01-11-2021", "01-11-2021", "01-11-2021", "01-11-2021",
"01-11-2021", "01-12-2021", "01-12-2021", "01-12-2021", "01-12-2021",
"01-12-2021", "01-12-2021", "01-12-2021", "01-12-2021", "01-12-2021",
"01-12-2021", "01-12-2021", "01-12-2021", "01-12-2021", "01-12-2021",
"01-12-2021", "01-12-2021", "01-12-2021", "01-12-2021", "01-12-2021",
"01-12-2021", "01-12-2021", "01-12-2021", "01-12-2021", "01-12-2021",
"01-13-2021", "01-13-2021", "01-13-2021", "01-13-2021", "01-13-2021",
"01-13-2021", "01-13-2021", "01-13-2021", "01-13-2021", "01-13-2021",
"01-13-2021", "01-13-2021", "01-13-2021", "01-13-2021", "01-13-2021",
"01-13-2021", "01-13-2021", "01-13-2021", "01-13-2021", "01-13-2021",
"01-13-2021", "01-13-2021", "01-13-2021", "01-13-2021", "01-14-2021",
"01-14-2021", "01-14-2021", "01-14-2021", "01-14-2021", "01-14-2021",
"01-14-2021", "01-14-2021", "01-14-2021", "01-14-2021", "01-14-2021",
"01-14-2021", "01-14-2021", "01-14-2021", "01-14-2021", "01-14-2021",
"01-14-2021", "01-14-2021", "01-14-2021", "01-14-2021", "01-14-2021",
"01-14-2021", "01-14-2021", "01-14-2021", "01-15-2021", "01-15-2021",
"01-15-2021", "01-15-2021", "01-15-2021", "01-15-2021", "01-15-2021",
"01-15-2021", "01-15-2021", "01-15-2021", "01-15-2021", "01-15-2021",
"01-15-2021", "01-15-2021", "01-15-2021", "01-15-2021", "01-15-2021",
"01-15-2021", "01-15-2021", "01-15-2021", "01-15-2021", "01-15-2021",
"01-15-2021", "01-15-2021"), Hour = c("00:00", "01:00", "02:00",
"03:00", "04:00", "05:00", "06:00", "07:00", "08:00", "09:00",
"10:00", "11:00", "12:00", "13:00", "14:00", "15:00", "16:00",
"17:00", "18:00", "19:00", "20:00", "21:00", "22:00", "23:00",
"00:00", "01:00", "02:00", "03:00", "04:00", "05:00", "06:00",
"07:00", "08:00", "09:00", "10:00", "11:00", "12:00", "13:00",
"14:00", "15:00", "16:00", "17:00", "18:00", "19:00", "20:00",
"21:00", "22:00", "23:00", "00:00", "01:00", "02:00", "03:00",
"04:00", "05:00", "06:00", "07:00", "08:00", "09:00", "10:00",
"11:00", "12:00", "13:00", "14:00", "15:00", "16:00", "17:00",
"18:00", "19:00", "20:00", "21:00", "22:00", "23:00", "00:00",
"01:00", "02:00", "03:00", "04:00", "05:00", "06:00", "07:00",
"08:00", "09:00", "10:00", "11:00", "12:00", "13:00", "14:00",
"15:00", "16:00", "17:00", "18:00", "19:00", "20:00", "21:00",
"22:00", "23:00", "00:00", "01:00", "02:00", "03:00", "04:00",
"05:00", "06:00", "07:00", "08:00", "09:00", "10:00", "11:00",
"12:00", "13:00", "14:00", "15:00", "16:00", "17:00", "18:00",
"19:00", "20:00", "21:00", "22:00", "23:00", "00:00", "01:00",
"02:00", "03:00", "04:00", "05:00", "06:00", "07:00", "08:00",
"09:00", "10:00", "11:00", "12:00", "13:00", "14:00", "15:00",
"16:00", "17:00", "18:00", "19:00", "20:00", "21:00", "22:00",
"23:00", "00:00", "01:00", "02:00", "03:00", "04:00", "05:00",
"06:00", "07:00", "08:00", "09:00", "10:00", "11:00", "12:00",
"13:00", "14:00", "15:00", "16:00", "17:00", "18:00", "19:00",
"20:00", "21:00", "22:00", "23:00", "00:00", "01:00", "02:00",
"03:00", "04:00", "05:00", "06:00", "07:00", "08:00", "09:00",
"10:00", "11:00", "12:00", "13:00", "14:00", "15:00", "16:00",
"17:00", "18:00", "19:00", "20:00", "21:00", "22:00", "23:00",
"00:00", "01:00", "02:00", "03:00", "04:00", "05:00", "06:00",
"07:00", "08:00", "09:00", "10:00", "11:00", "12:00", "13:00",
"14:00", "15:00", "16:00", "17:00", "18:00", "19:00", "20:00",
"21:00", "22:00", "23:00", "00:00", "01:00", "02:00", "03:00",
"04:00", "05:00", "06:00", "07:00", "08:00", "09:00", "10:00",
"11:00", "12:00", "13:00", "14:00", "15:00", "16:00", "17:00",
"18:00", "19:00", "20:00", "21:00", "22:00", "23:00", "00:00",
"01:00", "02:00", "03:00", "04:00", "05:00", "06:00", "07:00",
"08:00", "09:00", "10:00", "11:00", "12:00", "13:00", "14:00",
"15:00", "16:00", "17:00", "18:00", "19:00", "20:00", "21:00",
"22:00", "23:00", "00:00", "01:00", "02:00", "03:00", "04:00",
"05:00", "06:00", "07:00", "08:00", "09:00", "10:00", "11:00",
"12:00", "13:00", "14:00", "15:00", "16:00", "17:00", "18:00",
"19:00", "20:00", "21:00", "22:00", "23:00", "00:00", "01:00",
"02:00", "03:00", "04:00", "05:00", "06:00", "07:00", "08:00",
"09:00", "10:00", "11:00", "12:00", "13:00", "14:00", "15:00",
"16:00", "17:00", "18:00", "19:00", "20:00", "21:00", "22:00",
"23:00", "00:00", "01:00", "02:00", "03:00", "04:00", "05:00",
"06:00", "07:00", "08:00", "09:00", "10:00", "11:00", "12:00",
"13:00", "14:00", "15:00", "16:00", "17:00", "18:00", "19:00",
"20:00", "21:00", "22:00", "23:00", "00:00", "01:00", "02:00",
"03:00", "04:00", "05:00", "06:00", "07:00", "08:00", "09:00",
"10:00", "11:00", "12:00", "13:00", "14:00", "15:00", "16:00",
"17:00", "18:00", "19:00", "20:00", "21:00", "22:00", "23:00"
), Activity = c("1", "1", "1", "1", "1", "1", "1", "1", "23",
"2", "23", "23", "23", "23", "8", "8", "15", "15", "23", "23",
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"5", "5", "5", "16", "16", "7.5", "2", "23", "23", "23"), Activity_Name = structure(c(1L,
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试试这个。 count的数据类型有问题，改成dataframe可以缓解问题：
#Data
data <- as.data.frame(data)
#Plot
data %>%
arrange(count,Activity_Name) %>%
mutate(Activity_Name=as.character(Activity_Name)) %>%
mutate(Activity_Name=factor(Activity_Name,levels = unique(Activity_Name),
ordered = T)) %>%
ggplot(aes(x = Activity_Name, y = count)) +
geom_segment(aes(
x = Activity_Name,
xend = Activity_Name,
y = 0,
yend = count
),
color = "skyblue") +
geom_point(color = "blue",
size = 5,
alpha = 0.6) +
theme_light() +
scale_y_log10() +
coord_flip()
输出（我改变了可重现图的颜色）：
这是因为您的数据是分组的，所以 mutate 中的 fct_reorder 试图在组内而不是整个数据框内工作。只需添加一个 ungroup 它应该是所需的输出
输出的第 2 行显示数据已分组
data
# # A tibble: 360 x 5
# # Groups: Activity [18]
# Day Hour Activity Activity_Name count
# <chr> <chr> <chr> <fct> <int>
# 1 01-01-2021 00:00 1 Sleeping 122
# 2 01-01-2021 01:00 1 Sleeping 122
# 3 01-01-2021 02:00 1 Sleeping 122
# 4 01-01-2021 03:00 1 Sleeping 122
# 5 01-01-2021 04:00 1 Sleeping 122
# 6 01-01-2021 05:00 1 Sleeping 122
# 7 01-01-2021 06:00 1 Sleeping 122
# 8 01-01-2021 07:00 1 Sleeping 122
# 9 01-01-2021 08:00 23 Coding 63
# 10 01-01-2021 09:00 2 Eating 18
# # … with 350 more rows
添加取消分组：
data %>%
ungroup %>%
mutate(Activity_Name = fct_reorder(Activity_Name, count)) %>%
ggplot(aes(x = Activity_Name, y = count)) +
geom_segment(aes(
x = Activity_Name,
xend = Activity_Name,
y = 0,
yend = count
),
color = "skyblue") +
geom_point(color = "#F2F7F2",
size = 5,
alpha = 0.6) +
theme_light() +
scale_y_log10() +
coord_flip()