在ggplot中的x轴上显示工作日和时间-Showweekdaysandtimesonthex-axisinggplot

作者：x08308926 | 来源：互联网 | 2023-08-07 17:58

Ihaveadatasetwithevents.Theseeventshaveastarttimeandaduration.Iwanttocreateascat

I have a dataset with events. These events have a start time and a duration. I want to create a scatter plot with the start time on the x-axis and the duration on the y-axis, but I want to alter the x-axis so that it displays the course of a week. That is, I want the x-axis to start on Monday 00:00 and run through Sunday 23:59.

我有一个包含事件的数据集。这些事件具有开始时间和持续时间。我想创建一个散点图，其中x轴为开始时间，y轴为持续时间，但我想改变x轴，以便显示一周的过程。也就是说，我希望x轴在星期一00:00开始，并在星期日23:59运行。

All the solutions I've found online show me how to perform group-by-and-sum over weekdays, which is not what I want to do. I want to plot all data points individually, I simply want to reduce the date-axis to weekday and time.

我在网上找到的所有解决方案都告诉我如何在工作日逐个进行分组，这不是我想要做的。我想单独绘制所有数据点，我只想将日期轴减少到工作日和时间。

Any suggestions?

有什么建议么？

1 个解决方案

#1

This does what you need. What it does is to create a new variable by putting every observation in one week, and then generate a scatter plot in a necessary format.

这可以满足您的需求。它的作用是通过将每个观察放在一周内来创建一个新变量，然后以必要的格式生成散点图。

library(lubridate)
library(dplyr)

set.seed(1)
tmp <- data.frame(st_time = mdy("01-01-2018") + minutes(sample(1e5, size = 100))) 
tmp <- tmp %>% 
    mutate(st_week = floor_date(st_time, unit = 'week')) %>% # calculate the start of week
    mutate(st_time_inweek = st_time - st_week) %>% # calculate the time elapsed from the start of the week
    mutate(st_time_all_in_Oneweek= st_week[1] + st_time_inweek) %>% # put every obs in one week
    mutate(duration = runif(100, 0, 100)) # generate a random duration variable

This is how to generate the plot. The part "%a %H:%M:%S" could be just "%a" as the time portion is not informative.

这是如何生成图。部分“％a％H：％M：％S”可能只是“％a”，因为时间部分不提供信息。

library(ggplot2)
ggplot(tmp) + aes(x = st_time_all_in_oneweek, y = duration) +
    geom_point() + scale_x_datetime(date_labels = "%a %H:%M:%S", date_breaks = "1 day")

With "%a" the plot look like this:

使用“％a”时，情节如下所示：

enter image description here