在 R 中绘制时间序列事件图表
Plotting a time series event chart in R
我在一段时间（5 年）内监控了多个对象（几千个，具有不同的 ID）。每个对象可能在每个日历日采用几种状态之一：它可以没有事件，它可以采用 10 种不同的事件状态之一，或者它可以退役（即不再有状态更改）。我正在努力可视化这些数据。
我设想的是一组水平线，每条水平线对应一个单独的对象。没有任何事件的日子将用灰色（或白色）小点标记，有事件的日子将用彩色点表示，颜色与事件类型匹配，退役事件用标记和黑点标记为之间的每一天退役日期和期末。
.....xxxx....xx.......DDDDDDD
.oo.x.qqqq.......xx....qqqqq.
......pppp.pp..######........
等，其中符号将被彩色点（线）替换
我如何在 R 中创建这样的图表？
我也对如何更好地可视化此类数据的任何其他想法持开放态度
因此，从 2009 年 1 月 1 日到 2014 年 12 月 31 日期间的数据看起来像这样
ObjID|EventStartDate|EventEndDate|EventType|
00001|2010-01-10 |2010-01-13 | 01 | - event type 1, last for 4 days
00001|2010-03-30 |2010-04-05 | 03 | - event type 3, last for 6 days
00001|2012-06-30 |2012-06-30 | 0D | - decommission
00011|2009-07-15 |2009-08-10 | 08 |
00011|2010-11-15 |2010-11-16 | 01 |
00011|2012-06-30 |2012-07-11 | 05 |
00011|2013-02-07 |2013-02-09 | 05 |
01023|2011-11-11 |2011-11-21 | 07 |
...等等
您可以每天为每个事件绘制一个点，但是如果您涵盖那么多时间，您将拥有一个相当大的图表。如果您想这样做，这是一种方法。我将您的示例数据放入名为 dat 的 data.frame 中，日期采用 POSIXct 格式。
# calculate how many days each event lasts
dat$n_days <- with(dat,
difftime(EventEndDate, EventStartDate, units='days'))+1
# new data frame with 1 row per event day
row_rep <- unlist(mapply(rep, 1:nrow(dat), dat$n_days))
dat2 <- dat[row_rep,]
# add column for discrete event day
dat2$t_plus <- unlist(mapply(seq, 1, dat$n_days)) - 1
dat2$EventDay <- with(dat2, as.Date(EventStartDate) + t_plus)
# plot
library(ggplot2)
ggplot(dat2, aes(y=factor(ObjID), x=EventDay, color=EventType)) +
geom_point(shape=21) +
labs(title='Events by Date', y='Object ID') +
theme_bw() + theme(legend.position='bottom')
生成此图表（您可以使用各种相关的 ggplot 参数微调如何根据绘制的形状和颜色来表示事件）
dat2 看起来像这样：
> dat2
ObjID EventStartDate EventEndDate EventType n_days t_plus EventDay
1 1 2010-01-10 2010-01-13 01 4 days 0 2010-01-10
1.1 1 2010-01-10 2010-01-13 01 4 days 1 2010-01-11
1.2 1 2010-01-10 2010-01-13 01 4 days 2 2010-01-12
1.3 1 2010-01-10 2010-01-13 01 4 days 3 2010-01-13
2 1 2010-03-30 2010-04-05 03 7 days 0 2010-03-30
2.1 1 2010-03-30 2010-04-05 03 7 days 1 2010-03-31
2.2 1 2010-03-30 2010-04-05 03 7 days 2 2010-04-01
2.3 1 2010-03-30 2010-04-05 03 7 days 3 2010-04-02
2.4 1 2010-03-30 2010-04-05 03 7 days 4 2010-04-03
2.5 1 2010-03-30 2010-04-05 03 7 days 5 2010-04-04
2.6 1 2010-03-30 2010-04-05 03 7 days 6 2010-04-05
3 1 2012-06-30 2012-06-30 0D 1 days 0 2012-06-30
4 11 2009-07-15 2009-08-10 08 27 days 0 2009-07-15
4.1 11 2009-07-15 2009-08-10 08 27 days 1 2009-07-16
4.2 11 2009-07-15 2009-08-10 08 27 days 2 2009-07-17
4.3 11 2009-07-15 2009-08-10 08 27 days 3 2009-07-18
4.4 11 2009-07-15 2009-08-10 08 27 days 4 2009-07-19
4.5 11 2009-07-15 2009-08-10 08 27 days 5 2009-07-20
4.6 11 2009-07-15 2009-08-10 08 27 days 6 2009-07-21
4.7 11 2009-07-15 2009-08-10 08 27 days 7 2009-07-22
4.8 11 2009-07-15 2009-08-10 08 27 days 8 2009-07-23
4.9 11 2009-07-15 2009-08-10 08 27 days 9 2009-07-24
4.10 11 2009-07-15 2009-08-10 08 27 days 10 2009-07-25
4.11 11 2009-07-15 2009-08-10 08 27 days 11 2009-07-26
4.12 11 2009-07-15 2009-08-10 08 27 days 12 2009-07-27
4.13 11 2009-07-15 2009-08-10 08 27 days 13 2009-07-28
4.14 11 2009-07-15 2009-08-10 08 27 days 14 2009-07-29
4.15 11 2009-07-15 2009-08-10 08 27 days 15 2009-07-30
4.16 11 2009-07-15 2009-08-10 08 27 days 16 2009-07-31
4.17 11 2009-07-15 2009-08-10 08 27 days 17 2009-08-01
4.18 11 2009-07-15 2009-08-10 08 27 days 18 2009-08-02
4.19 11 2009-07-15 2009-08-10 08 27 days 19 2009-08-03
4.20 11 2009-07-15 2009-08-10 08 27 days 20 2009-08-04
4.21 11 2009-07-15 2009-08-10 08 27 days 21 2009-08-05
4.22 11 2009-07-15 2009-08-10 08 27 days 22 2009-08-06
4.23 11 2009-07-15 2009-08-10 08 27 days 23 2009-08-07
4.24 11 2009-07-15 2009-08-10 08 27 days 24 2009-08-08
4.25 11 2009-07-15 2009-08-10 08 27 days 25 2009-08-09
4.26 11 2009-07-15 2009-08-10 08 27 days 26 2009-08-10
5 11 2010-11-15 2010-11-16 01 2 days 0 2010-11-15
5.1 11 2010-11-15 2010-11-16 01 2 days 1 2010-11-16
6 11 2012-06-30 2012-07-11 05 12 days 0 2012-06-30
6.1 11 2012-06-30 2012-07-11 05 12 days 1 2012-07-01
6.2 11 2012-06-30 2012-07-11 05 12 days 2 2012-07-02
6.3 11 2012-06-30 2012-07-11 05 12 days 3 2012-07-03
6.4 11 2012-06-30 2012-07-11 05 12 days 4 2012-07-04
6.5 11 2012-06-30 2012-07-11 05 12 days 5 2012-07-05
6.6 11 2012-06-30 2012-07-11 05 12 days 6 2012-07-06
6.7 11 2012-06-30 2012-07-11 05 12 days 7 2012-07-07
6.8 11 2012-06-30 2012-07-11 05 12 days 8 2012-07-08
6.9 11 2012-06-30 2012-07-11 05 12 days 9 2012-07-09
6.10 11 2012-06-30 2012-07-11 05 12 days 10 2012-07-10
6.11 11 2012-06-30 2012-07-11 05 12 days 11 2012-07-11
7 11 2013-02-07 2013-02-09 05 3 days 0 2013-02-07
7.1 11 2013-02-07 2013-02-09 05 3 days 1 2013-02-08
7.2 11 2013-02-07 2013-02-09 05 3 days 2 2013-02-09
8 1023 2011-11-11 2011-11-21 07 11 days 0 2011-11-11
8.1 1023 2011-11-11 2011-11-21 07 11 days 1 2011-11-12
8.2 1023 2011-11-11 2011-11-21 07 11 days 2 2011-11-13
8.3 1023 2011-11-11 2011-11-21 07 11 days 3 2011-11-14
8.4 1023 2011-11-11 2011-11-21 07 11 days 4 2011-11-15
8.5 1023 2011-11-11 2011-11-21 07 11 days 5 2011-11-16
8.6 1023 2011-11-11 2011-11-21 07 11 days 6 2011-11-17
8.7 1023 2011-11-11 2011-11-21 07 11 days 7 2011-11-18
8.8 1023 2011-11-11 2011-11-21 07 11 days 8 2011-11-19
8.9 1023 2011-11-11 2011-11-21 07 11 days 9 2011-11-20
8.10 1023 2011-11-11 2011-11-21 07 11 days 10 2011-11-21
我在一段时间（5 年）内监控了多个对象（几千个，具有不同的 ID）。每个对象可能在每个日历日采用几种状态之一：它可以没有事件，它可以采用 10 种不同的事件状态之一，或者它可以退役（即不再有状态更改）。我正在努力可视化这些数据。 我设想的是一组水平线，每条水平线对应一个单独的对象。没有任何事件的日子将用灰色（或白色）小点标记，有事件的日子将用彩色点表示，颜色与事件类型匹配，退役事件用标记和黑点标记为之间的每一天退役日期和期末。
.....xxxx....xx.......DDDDDDD
.oo.x.qqqq.......xx....qqqqq.
......pppp.pp..######........
等，其中符号将被彩色点（线）替换
我如何在 R 中创建这样的图表？ 我也对如何更好地可视化此类数据的任何其他想法持开放态度
因此，从 2009 年 1 月 1 日到 2014 年 12 月 31 日期间的数据看起来像这样
ObjID|EventStartDate|EventEndDate|EventType|
00001|2010-01-10 |2010-01-13 | 01 | - event type 1, last for 4 days
00001|2010-03-30 |2010-04-05 | 03 | - event type 3, last for 6 days
00001|2012-06-30 |2012-06-30 | 0D | - decommission
00011|2009-07-15 |2009-08-10 | 08 |
00011|2010-11-15 |2010-11-16 | 01 |
00011|2012-06-30 |2012-07-11 | 05 |
00011|2013-02-07 |2013-02-09 | 05 |
01023|2011-11-11 |2011-11-21 | 07 |
...等等
您可以每天为每个事件绘制一个点，但是如果您涵盖那么多时间，您将拥有一个相当大的图表。如果您想这样做，这是一种方法。我将您的示例数据放入名为 dat 的 data.frame 中，日期采用 POSIXct 格式。
# calculate how many days each event lasts
dat$n_days <- with(dat,
difftime(EventEndDate, EventStartDate, units='days'))+1
# new data frame with 1 row per event day
row_rep <- unlist(mapply(rep, 1:nrow(dat), dat$n_days))
dat2 <- dat[row_rep,]
# add column for discrete event day
dat2$t_plus <- unlist(mapply(seq, 1, dat$n_days)) - 1
dat2$EventDay <- with(dat2, as.Date(EventStartDate) + t_plus)
# plot
library(ggplot2)
ggplot(dat2, aes(y=factor(ObjID), x=EventDay, color=EventType)) +
geom_point(shape=21) +
labs(title='Events by Date', y='Object ID') +
theme_bw() + theme(legend.position='bottom')
生成此图表（您可以使用各种相关的 ggplot 参数微调如何根据绘制的形状和颜色来表示事件）
dat2 看起来像这样：
> dat2
ObjID EventStartDate EventEndDate EventType n_days t_plus EventDay
1 1 2010-01-10 2010-01-13 01 4 days 0 2010-01-10
1.1 1 2010-01-10 2010-01-13 01 4 days 1 2010-01-11
1.2 1 2010-01-10 2010-01-13 01 4 days 2 2010-01-12
1.3 1 2010-01-10 2010-01-13 01 4 days 3 2010-01-13
2 1 2010-03-30 2010-04-05 03 7 days 0 2010-03-30
2.1 1 2010-03-30 2010-04-05 03 7 days 1 2010-03-31
2.2 1 2010-03-30 2010-04-05 03 7 days 2 2010-04-01
2.3 1 2010-03-30 2010-04-05 03 7 days 3 2010-04-02
2.4 1 2010-03-30 2010-04-05 03 7 days 4 2010-04-03
2.5 1 2010-03-30 2010-04-05 03 7 days 5 2010-04-04
2.6 1 2010-03-30 2010-04-05 03 7 days 6 2010-04-05
3 1 2012-06-30 2012-06-30 0D 1 days 0 2012-06-30
4 11 2009-07-15 2009-08-10 08 27 days 0 2009-07-15
4.1 11 2009-07-15 2009-08-10 08 27 days 1 2009-07-16
4.2 11 2009-07-15 2009-08-10 08 27 days 2 2009-07-17
4.3 11 2009-07-15 2009-08-10 08 27 days 3 2009-07-18
4.4 11 2009-07-15 2009-08-10 08 27 days 4 2009-07-19
4.5 11 2009-07-15 2009-08-10 08 27 days 5 2009-07-20
4.6 11 2009-07-15 2009-08-10 08 27 days 6 2009-07-21
4.7 11 2009-07-15 2009-08-10 08 27 days 7 2009-07-22
4.8 11 2009-07-15 2009-08-10 08 27 days 8 2009-07-23
4.9 11 2009-07-15 2009-08-10 08 27 days 9 2009-07-24
4.10 11 2009-07-15 2009-08-10 08 27 days 10 2009-07-25
4.11 11 2009-07-15 2009-08-10 08 27 days 11 2009-07-26
4.12 11 2009-07-15 2009-08-10 08 27 days 12 2009-07-27
4.13 11 2009-07-15 2009-08-10 08 27 days 13 2009-07-28
4.14 11 2009-07-15 2009-08-10 08 27 days 14 2009-07-29
4.15 11 2009-07-15 2009-08-10 08 27 days 15 2009-07-30
4.16 11 2009-07-15 2009-08-10 08 27 days 16 2009-07-31
4.17 11 2009-07-15 2009-08-10 08 27 days 17 2009-08-01
4.18 11 2009-07-15 2009-08-10 08 27 days 18 2009-08-02
4.19 11 2009-07-15 2009-08-10 08 27 days 19 2009-08-03
4.20 11 2009-07-15 2009-08-10 08 27 days 20 2009-08-04
4.21 11 2009-07-15 2009-08-10 08 27 days 21 2009-08-05
4.22 11 2009-07-15 2009-08-10 08 27 days 22 2009-08-06
4.23 11 2009-07-15 2009-08-10 08 27 days 23 2009-08-07
4.24 11 2009-07-15 2009-08-10 08 27 days 24 2009-08-08
4.25 11 2009-07-15 2009-08-10 08 27 days 25 2009-08-09
4.26 11 2009-07-15 2009-08-10 08 27 days 26 2009-08-10
5 11 2010-11-15 2010-11-16 01 2 days 0 2010-11-15
5.1 11 2010-11-15 2010-11-16 01 2 days 1 2010-11-16
6 11 2012-06-30 2012-07-11 05 12 days 0 2012-06-30
6.1 11 2012-06-30 2012-07-11 05 12 days 1 2012-07-01
6.2 11 2012-06-30 2012-07-11 05 12 days 2 2012-07-02
6.3 11 2012-06-30 2012-07-11 05 12 days 3 2012-07-03
6.4 11 2012-06-30 2012-07-11 05 12 days 4 2012-07-04
6.5 11 2012-06-30 2012-07-11 05 12 days 5 2012-07-05
6.6 11 2012-06-30 2012-07-11 05 12 days 6 2012-07-06
6.7 11 2012-06-30 2012-07-11 05 12 days 7 2012-07-07
6.8 11 2012-06-30 2012-07-11 05 12 days 8 2012-07-08
6.9 11 2012-06-30 2012-07-11 05 12 days 9 2012-07-09
6.10 11 2012-06-30 2012-07-11 05 12 days 10 2012-07-10
6.11 11 2012-06-30 2012-07-11 05 12 days 11 2012-07-11
7 11 2013-02-07 2013-02-09 05 3 days 0 2013-02-07
7.1 11 2013-02-07 2013-02-09 05 3 days 1 2013-02-08
7.2 11 2013-02-07 2013-02-09 05 3 days 2 2013-02-09
8 1023 2011-11-11 2011-11-21 07 11 days 0 2011-11-11
8.1 1023 2011-11-11 2011-11-21 07 11 days 1 2011-11-12
8.2 1023 2011-11-11 2011-11-21 07 11 days 2 2011-11-13
8.3 1023 2011-11-11 2011-11-21 07 11 days 3 2011-11-14
8.4 1023 2011-11-11 2011-11-21 07 11 days 4 2011-11-15
8.5 1023 2011-11-11 2011-11-21 07 11 days 5 2011-11-16
8.6 1023 2011-11-11 2011-11-21 07 11 days 6 2011-11-17
8.7 1023 2011-11-11 2011-11-21 07 11 days 7 2011-11-18
8.8 1023 2011-11-11 2011-11-21 07 11 days 8 2011-11-19
8.9 1023 2011-11-11 2011-11-21 07 11 days 9 2011-11-20
8.10 1023 2011-11-11 2011-11-21 07 11 days 10 2011-11-21