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我想在一张图中绘制 3 种不同的入住模式:a.) 当男性和女性都在工作时; b.) 只有男性工作; c.) 只有女性工作。
我使用 facet
创建了 3 个不同的 data.frames
第一个data.frame的结构(男性和女性都在工作)是:
structure(list(time = c("04:00", "04:15", "04:30", "04:45", "05:00",
"05:15", "05:30", "05:45", "06:00", "06:15", "06:30", "06:45",
"07:00", "07:15", "07:30", "07:45", "08:00", "08:15", "08:30",
"08:45", "09:00", "09:15", "09:30", "09:45", "10:00", "10:15",
"10:30", "10:45", "11:00", "11:15"), day = c("Monday", "Monday",
"Monday", "Monday", "Monday", "Monday", "Monday", "Monday", "Monday",
"Monday", "Monday", "Monday", "Monday", "Monday", "Monday", "Monday",
"Monday", "Monday", "Monday", "Monday", "Monday", "Monday", "Monday",
"Monday", "Monday", "Monday", "Monday", "Monday", "Monday", "Monday"
), variable = 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), .Label = c("Shifts on Monday", "Shifts on Tuesday",
"Shifts on Wednesday", "Shifts on Thursday", "Shifts on Friday",
"Shifts on Saturday", "Shifts on Sunday"), class = "factor"),
value = c(102, 110, 116, 120, 148, 152, 188, 204, 318, 348,
418, 442, 752, 816, 1064, 1144, 1836, 1942, 2402, 2524, 3240,
3324, 3486, 3520, 3594, 3592, 3596, 3568, 3594, 3626), size_f = 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), .Label = c("Monday",
"Tuesday", "Wednesday", "Thursday", "Friday", "Saturday",
"Sunday"), class = "factor")), row.names = c(NA, 30L), class = "data.frame")
dput(head(melted_WkSTiWeekM , 30))
structure(list(time = c("04:00", "04:15", "04:30", "04:45", "05:00",
"05:15", "05:30", "05:45", "06:00", "06:15", "06:30", "06:45",
"07:00", "07:15", "07:30", "07:45", "08:00", "08:15", "08:30",
"08:45", "09:00", "09:15", "09:30", "09:45", "10:00", "10:15",
"10:30", "10:45", "11:00", "11:15"), day = c("Monday", "Monday",
"Monday", "Monday", "Monday", "Monday", "Monday", "Monday", "Monday",
"Monday", "Monday", "Monday", "Monday", "Monday", "Monday", "Monday",
"Monday", "Monday", "Monday", "Monday", "Monday", "Monday", "Monday",
"Monday", "Monday", "Monday", "Monday", "Monday", "Monday", "Monday"
), variable = 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), .Label = c("Shifts on Monday", "Shifts on Tuesday",
"Shifts on Wednesday", "Shifts on Thursday", "Shifts on Friday",
"Shifts on Saturday", "Shifts on Sunday"), class = "factor"),
value = c(56, 58, 64, 68, 84, 84, 104, 114, 172, 196, 224,
238, 410, 442, 560, 604, 930, 968, 1188, 1230, 1576, 1620,
1692, 1706, 1740, 1746, 1752, 1740, 1736, 1756), size_f = 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), .Label = c("Monday",
"Tuesday", "Wednesday", "Thursday", "Friday", "Saturday",
"Sunday"), class = "factor")), row.names = c(NA, 30L), class = "data.frame")
structure(list(time = c("04:00", "04:15", "04:30", "04:45", "05:00",
"05:15", "05:30", "05:45", "06:00", "06:15", "06:30", "06:45",
"07:00", "07:15", "07:30", "07:45", "08:00", "08:15", "08:30",
"08:45", "09:00", "09:15", "09:30", "09:45", "10:00", "10:15",
"10:30", "10:45", "11:00", "11:15"), day = c("Monday", "Monday",
"Monday", "Monday", "Monday", "Monday", "Monday", "Monday", "Monday",
"Monday", "Monday", "Monday", "Monday", "Monday", "Monday", "Monday",
"Monday", "Monday", "Monday", "Monday", "Monday", "Monday", "Monday",
"Monday", "Monday", "Monday", "Monday", "Monday", "Monday", "Monday"
), variable = 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), .Label = c("Shifts on Monday", "Shifts on Tuesday",
"Shifts on Wednesday", "Shifts on Thursday", "Shifts on Friday",
"Shifts on Saturday", "Shifts on Sunday"), class = "factor"),
value = c(46, 52, 52, 52, 64, 68, 84, 90, 146, 152, 194,
204, 342, 374, 504, 540, 906, 974, 1214, 1294, 1664, 1704,
1794, 1814, 1854, 1846, 1844, 1828, 1858, 1870), size_f = 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), .Label = c("Monday",
"Tuesday", "Wednesday", "Thursday", "Friday", "Saturday",
"Sunday"), class = "factor")), row.names = c(NA, 30L), class = "data.frame")
melted_WkSTiWeekAll=cbind(melted_WkSTiWeek,melted_WkSTiWeekM,melted_WkSTiWeekF)
structure(list(time = c("04:00", "04:15", "04:30", "04:45", "05:00"
), day = c("Monday", "Monday", "Monday", "Monday", "Monday"),
variable = structure(c(1L, 1L, 1L, 1L, 1L), .Label = c("Shifts on Monday",
"Shifts on Tuesday", "Shifts on Wednesday", "Shifts on Thursday",
"Shifts on Friday", "Shifts on Saturday", "Shifts on Sunday"
), class = "factor"), value = c(102, 110, 116, 120, 148),
size_f = structure(c(1L, 1L, 1L, 1L, 1L), .Label = c("Monday",
"Tuesday", "Wednesday", "Thursday", "Friday", "Saturday",
"Sunday"), class = "factor"), time = c("04:00", "04:15",
"04:30", "04:45", "05:00"), day = c("Monday", "Monday", "Monday",
"Monday", "Monday"), variable = structure(c(1L, 1L, 1L, 1L,
1L), .Label = c("Shifts on Monday", "Shifts on Tuesday",
"Shifts on Wednesday", "Shifts on Thursday", "Shifts on Friday",
"Shifts on Saturday", "Shifts on Sunday"), class = "factor"),
value = c(56, 58, 64, 68, 84), size_f = structure(c(1L, 1L,
1L, 1L, 1L), .Label = c("Monday", "Tuesday", "Wednesday",
"Thursday", "Friday", "Saturday", "Sunday"), class = "factor"),
time = c("04:00", "04:15", "04:30", "04:45", "05:00"), day = c("Monday",
"Monday", "Monday", "Monday", "Monday"), variable = structure(c(1L,
1L, 1L, 1L, 1L), .Label = c("Shifts on Monday", "Shifts on Tuesday",
"Shifts on Wednesday", "Shifts on Thursday", "Shifts on Friday",
"Shifts on Saturday", "Shifts on Sunday"), class = "factor"),
value = c(46, 52, 52, 52, 64), size_f = structure(c(1L, 1L,
1L, 1L, 1L), .Label = c("Monday", "Tuesday", "Wednesday",
"Thursday", "Friday", "Saturday", "Sunday"), class = "factor")), row.names = c(NA,
5L), class = "data.frame")
time, day, variable and size_f
是相似的。
facet
下面的情节
最佳答案
您可以这样做,但将您的数据帧合并在一起并将它们标记为 All
, Male
, 和 Female
因此。然后您可以在您的 ggplot
中使用该标签进行分组(着色)功能。
使用 geom_bar
和 position = "identity"
您将在彼此的顶部放置条形广告以消除条形之间的空间(以模仿密度图外观)width
设置为 1
. alpha
可用于更改 fill
的透明度颜色。
为了获得一周中每一天的单独图,我们使用 facet_wrap(~day)
.
library(tidyverse)
melted_WkSTiWeekAll <- bind_rows(list(All=melted_WkSTiWeek,
Male=melted_WkSTiWeekM,
Female=melted_WkSTiWeekF),
.id = 'source')
ggplot(melted_WkSTiWeekAll, aes(x=time, y=value, fill=source)) +
geom_bar(stat="identity", position = "identity", alpha=.3, width=1) +
facet_wrap(~day)
facet
因为提供的数据只有星期一的条目。
关于r - 如何叠加多个图,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/56383936/
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