Question

我正在制作车站自行车可用性的时间序列图。到目前为止，我能够以10分钟的间隔绘制可用性。请注意created_at.x采用POSIXct格式。

> head(Pershing, n =20)
       id status available_bike_count available_dock_count        created_at.x station_summary_id citibike_station_id latitude longitude
41473 293 Active                    2                   57 2015-10-01 05:20:08              82792                 519 40.75188  -73.9777
41474 293 Active                    3                   56 2015-10-01 09:20:10              82816                 519 40.75188  -73.9777
41475 293 Active                    4                   52 2015-10-01 12:00:06              82832                 519 40.75188  -73.9777
41476 293 Active                    3                   56 2015-10-01 04:50:06              82789                 519 40.75188  -73.9777
41477 293 Active                    3                   56 2015-10-01 06:30:08              82799                 519 40.75188  -73.9777
41478 293 Active                    2                   57 2015-10-01 05:10:07              82791                 519 40.75188  -73.9777
41479 293 Active                    9                   47 2015-10-01 12:40:06              82836                 519 40.75188  -73.9777
41480 293 Active                    2                   57 2015-10-01 07:10:06              82803                 519 40.75188  -73.9777
41481 293 Active                    1                   57 2015-10-01 00:00:12              82760                 519 40.75188  -73.9777
41482 293 Active                    3                   56 2015-10-01 05:00:07              82790                 519 40.75188  -73.9777
41483 293 Active                    1                   56 2015-10-01 02:50:07              82777                 519 40.75188  -73.9777
41484 293 Active                    3                   56 2015-10-01 08:40:06              82812                 519 40.75188  -73.9777
41485 293 Active                   49                    7 2015-10-01 22:50:07              82897                 519 40.75188  -73.9777
41486 293 Active                   11                   44 2015-10-01 16:40:07              82860                 519 40.75188  -73.9777
41487 293 Active                    3                   54 2015-10-01 01:40:06              82770                 519 40.75188  -73.9777
41488 293 Active                    5                   52 2015-10-01 11:10:07              82827                 519 40.75188  -73.9777
41489 293 Active                    9                   47 2015-10-01 18:40:13              82872                 519 40.75188  -73.9777
41490 293 Active                    8                   48 2015-10-01 12:20:08              82834                 519 40.75188  -73.9777
41491 293 Active                    2                   56 2015-10-01 00:40:06              82764                 519 40.75188  -73.9777
41492 293 Active                    4                   52 2015-10-01 12:50:06              82837                 519 40.75188  -73.9777

ggplot(data=Pershing,aes(x= created_at.x, y=available_bike_count)) + 
  geom_point(colour="red") + 
  ylab("Available Bikes") + 
  xlab("time")

我想添加显示时间范围的垂直线（实际上是条形）。时间范围应从Pershing_trucks$stoptime开始，到Pershing_trucks$starttime

结束

> Pershing_trucks
        X bikeid end.station.id start.station.id diff.time
10   2785  19911            359              519       930
12   3052  23301            359              519      1406
14   3496  23818            359              519      1164
15   3778  23185            359              519      1515
17   3795  21630            359              519      1563
21   5046  22144            359              519       884
22   5063  19132            359              519      1396
24   5461  22994            359              519      1574
25   5861  22176            359              519      1394
27   5956  14716            359              519      1932
32   6341  18099            359              519      1267
33   6415  19432            359              519      1143
34   6763  17121            359              519       827
35   6800  22616            359              519      1693
38   7694  20754            359              519      1690
39   8224  15323            359              519      2465
40   8626  23472            359              519      1046
43   8903  19348            359              519      1724
45   8952  24236            359              519      1289
49   9664  24246            359              519      2723
50   9729  18330            359              519      2030
51   9730  18330            359              519      2438
55  10460  22067            359              519      1069
56  10461  22067            359              519      1635
59  11906  22430            359              519       617
62  12310  17727            359              519      1749
64  12557  15174            359              519      1280
65  12568  24123            359              519      2843
72  13572  20687            359              519      1541
77  15530  22913            359              519      1052
80  15863  16252            359              519       893
82  16901  24265            359              519      3316
85  17731  23792            359              519       751
87  19130  17144            359              519      2162
89  21064  15553            359              519      1817
91  21572  22077            359              519       719
92  21789  19456            359              519      3313
95  22822  19639            359              519      1837
98  24345  20860            359              519      1682
102 25520  17632            359              519      1553
112 28679  20514            359              519      3297
120 30827  19110            359              519      3118
121 31258  16744            359              519      3081
               stoptime           starttime             midtime
10  2015-10-01 08:30:16 2015-10-01 08:45:46 2015-10-01 08:38:01
12  2015-10-01 08:20:30 2015-10-01 08:43:56 2015-10-01 08:32:13
14  2015-10-01 06:23:14 2015-10-01 06:42:38 2015-10-01 06:32:56
15  2015-10-01 07:04:10 2015-10-01 07:29:25 2015-10-01 07:16:47
17  2015-10-01 07:40:59 2015-10-01 08:07:02 2015-10-01 07:54:00
21  2015-10-01 06:51:46 2015-10-01 07:06:30 2015-10-01 06:59:08
22  2015-10-01 07:43:37 2015-10-01 08:06:53 2015-10-01 07:55:15
24  2015-10-01 06:20:39 2015-10-01 06:46:53 2015-10-01 06:33:46
25  2015-10-01 06:46:05 2015-10-01 07:09:19 2015-10-01 06:57:42
27  2015-10-01 08:12:16 2015-10-01 08:44:28 2015-10-01 08:28:22
32  2015-10-01 06:23:19 2015-10-01 06:44:26 2015-10-01 06:33:52
33  2015-10-01 06:25:58 2015-10-01 06:45:01 2015-10-01 06:35:29
34  2015-10-01 06:33:12 2015-10-01 06:46:59 2015-10-01 06:40:05
35  2015-10-01 07:23:30 2015-10-01 07:51:43 2015-10-01 07:37:36
38  2015-10-01 06:41:24 2015-10-01 07:09:34 2015-10-01 06:55:29
39  2015-10-01 06:52:20 2015-10-01 07:33:25 2015-10-01 07:12:52
40  2015-10-01 06:47:52 2015-10-01 07:05:18 2015-10-01 06:56:35
43  2015-10-01 07:37:51 2015-10-01 08:06:35 2015-10-01 07:52:13
45  2015-10-01 06:48:08 2015-10-01 07:09:37 2015-10-01 06:58:52
49  2015-10-01 07:01:33 2015-10-01 07:46:56 2015-10-01 07:24:14
50  2015-10-01 07:00:07 2015-10-01 07:33:57 2015-10-01 07:17:02
51  2015-10-01 07:55:18 2015-10-01 08:35:56 2015-10-01 08:15:37
55  2015-10-01 07:30:05 2015-10-01 07:47:54 2015-10-01 07:38:59
56  2015-10-01 08:16:32 2015-10-01 08:43:47 2015-10-01 08:30:09
59  2015-10-01 07:17:48 2015-10-01 07:28:05 2015-10-01 07:22:56
62  2015-10-01 07:25:07 2015-10-01 07:54:16 2015-10-01 07:39:41
64  2015-10-01 07:25:30 2015-10-01 07:46:50 2015-10-01 07:36:10
65  2015-10-01 09:34:44 2015-10-01 10:22:07 2015-10-01 09:58:25
72  2015-10-01 08:40:39 2015-10-01 09:06:20 2015-10-01 08:53:29
77  2015-10-01 07:47:57 2015-10-01 08:05:29 2015-10-01 07:56:43
80  2015-10-01 08:49:59 2015-10-01 09:04:52 2015-10-01 08:57:25
82  2015-10-01 08:59:52 2015-10-01 09:55:08 2015-10-01 09:27:30
85  2015-10-01 07:51:10 2015-10-01 08:03:41 2015-10-01 07:57:25
87  2015-10-01 08:06:23 2015-10-01 08:42:25 2015-10-01 08:24:24
89  2015-10-01 08:15:09 2015-10-01 08:45:26 2015-10-01 08:30:17
91  2015-10-01 08:50:32 2015-10-01 09:02:31 2015-10-01 08:56:31
92  2015-10-01 08:53:47 2015-10-01 09:49:00 2015-10-01 09:21:23
95  2015-10-01 08:20:05 2015-10-01 08:50:42 2015-10-01 08:35:23
98  2015-10-01 08:34:41 2015-10-01 09:02:43 2015-10-01 08:48:42
102 2015-10-01 08:37:07 2015-10-01 09:03:00 2015-10-01 08:50:03
112 2015-10-01 08:51:15 2015-10-01 09:46:12 2015-10-01 09:18:43
120 2015-10-01 08:56:43 2015-10-01 09:48:41 2015-10-01 09:22:42
121 2015-10-01 09:43:33 2015-10-01 10:34:54 2015-10-01 10:09:13

> dput(Pershing_trucks)
structure(list(X = c(2785L, 3052L, 3496L, 3778L, 3795L, 5046L, 
5063L, 5461L, 5861L, 5956L, 6341L, 6415L, 6763L, 6800L, 7694L, 
8224L, 8626L, 8903L, 8952L, 9664L, 9729L, 9730L, 10460L, 10461L, 
11906L, 12310L, 12557L, 12568L, 13572L, 15530L, 15863L, 16901L, 
17731L, 19130L, 21064L, 21572L, 21789L, 22822L, 24345L, 25520L, 
28679L, 30827L, 31258L), bikeid = c(19911L, 23301L, 23818L, 23185L, 
21630L, 22144L, 19132L, 22994L, 22176L, 14716L, 18099L, 19432L, 
17121L, 22616L, 20754L, 15323L, 23472L, 19348L, 24236L, 24246L, 
18330L, 18330L, 22067L, 22067L, 22430L, 17727L, 15174L, 24123L, 
20687L, 22913L, 16252L, 24265L, 23792L, 17144L, 15553L, 22077L, 
19456L, 19639L, 20860L, 17632L, 20514L, 19110L, 16744L), end.station.id = c(359L, 
359L, 359L, 359L, 359L, 359L, 359L, 359L, 359L, 359L, 359L, 359L, 
359L, 359L, 359L, 359L, 359L, 359L, 359L, 359L, 359L, 359L, 359L, 
359L, 359L, 359L, 359L, 359L, 359L, 359L, 359L, 359L, 359L, 359L, 
359L, 359L, 359L, 359L, 359L, 359L, 359L, 359L, 359L), start.station.id = c(519L, 
519L, 519L, 519L, 519L, 519L, 519L, 519L, 519L, 519L, 519L, 519L, 
519L, 519L, 519L, 519L, 519L, 519L, 519L, 519L, 519L, 519L, 519L, 
519L, 519L, 519L, 519L, 519L, 519L, 519L, 519L, 519L, 519L, 519L, 
519L, 519L, 519L, 519L, 519L, 519L, 519L, 519L, 519L), diff.time = c(930L, 
1406L, 1164L, 1515L, 1563L, 884L, 1396L, 1574L, 1394L, 1932L, 
1267L, 1143L, 827L, 1693L, 1690L, 2465L, 1046L, 1724L, 1289L, 
2723L, 2030L, 2438L, 1069L, 1635L, 617L, 1749L, 1280L, 2843L, 
1541L, 1052L, 893L, 3316L, 751L, 2162L, 1817L, 719L, 3313L, 1837L, 
1682L, 1553L, 3297L, 3118L, 3081L), stoptime = structure(c(1443706216, 
1443705630, 1443698594, 1443701050, 1443703259, 1443700306, 1443703417, 
1443698439, 1443699965, 1443705136, 1443698599, 1443698758, 1443699192, 
1443702210, 1443699684, 1443700340, 1443700072, 1443703071, 1443700088, 
1443700893, 1443700807, 1443704118, 1443702605, 1443705392, 1443701868, 
1443702307, 1443702330, 1443710084, 1443706839, 1443703677, 1443707399, 
1443707992, 1443703870, 1443704783, 1443705309, 1443707432, 1443707627, 
1443705605, 1443706481, 1443706627, 1443707475, 1443707803, 1443710613
), class = c("POSIXct", "POSIXt"), tzone = "EST"), starttime = structure(c(1443707146, 
1443707036, 1443699758, 1443702565, 1443704822, 1443701190, 1443704813, 
1443700013, 1443701359, 1443707068, 1443699866, 1443699901, 1443700019, 
1443703903, 1443701374, 1443702805, 1443701118, 1443704795, 1443701377, 
1443703616, 1443702837, 1443706556, 1443703674, 1443707027, 1443702485, 
1443704056, 1443703610, 1443712927, 1443708380, 1443704729, 1443708292, 
1443711308, 1443704621, 1443706945, 1443707126, 1443708151, 1443710940, 
1443707442, 1443708163, 1443708180, 1443710772, 1443710921, 1443713694
), class = c("POSIXct", "POSIXt"), tzone = "EST"), midtime = structure(c(1443706681, 
1443706333, 1443699176, 1443701807.5, 1443704040.5, 1443700748, 
1443704115, 1443699226, 1443700662, 1443706102, 1443699232.5, 
1443699329.5, 1443699605.5, 1443703056.5, 1443700529, 1443701572.5, 
1443700595, 1443703933, 1443700732.5, 1443702254.5, 1443701822, 
1443705337, 1443703139.5, 1443706209.5, 1443702176.5, 1443703181.5, 
1443702970, 1443711505.5, 1443707609.5, 1443704203, 1443707845.5, 
1443709650, 1443704245.5, 1443705864, 1443706217.5, 1443707791.5, 
1443709283.5, 1443706523.5, 1443707322, 1443707403.5, 1443709123.5, 
1443709362, 1443712153.5), class = c("POSIXct", "POSIXt"), tzone = "")), .Names = c("X", 
"bikeid", "end.station.id", "start.station.id", "diff.time", 
"stoptime", "starttime", "midtime"), row.names = c(10L, 12L, 
14L, 15L, 17L, 21L, 22L, 24L, 25L, 27L, 32L, 33L, 34L, 35L, 38L, 
39L, 40L, 43L, 45L, 49L, 50L, 51L, 55L, 56L, 59L, 62L, 64L, 65L, 
72L, 77L, 80L, 82L, 85L, 87L, 89L, 91L, 92L, 95L, 98L, 102L, 
112L, 120L, 121L), class = "data.frame")

理想情况下，情节看起来像这样：

Answer 1

我认为这是一个相当复杂的问题。但是，我可以给你部分内容和解决它的想法。

这个想法是创建一个循环函数来创建这样的东西。它可能无法正常工作，但通过一些调整，它可能会。

vertBars <- lapply(seq_along(Pershing_trucks), function(x) {

             # Start with a vector that is empty
                 vertBars <- 0 

             # Add a ggplot call that creates a grey box with the desired 
             # start and stop times for a single line number "x"  
                 a <- geom_rect(data=Pershing_trucks, aes(xmin=stoptime[x],
                            xmax=starttime[x], ymin=-Inf, ymax=+Inf), fill='gray80',
                            alpha=0.02)                

             # Add the plot "a" to the empty vector you created. This will loop and
             # add all of the bars that you require without having to manually specify them
                vertBars <- vertBars + a

             # Return the vector "vertBars" that should be able to be added to your plot
                return(vertBars)

             }

此外，为这样的情节添加+ theme_bw()可能是个明智之举，因为它看起来更清晰。

Answer 2

您提出的问题非常简单，我们只需要在您的geom_rect数据中添加Pershing_trucks图层。

我不想打扰导入您的Pershing数据框，因此在从Pershing_trucks获取dput()数据后，我采样/模拟了Pershing数据像这样的框架：

Pershing = data.frame(
    created.at.x = sample(Pershing_trucks$starttime, 20),
    available_bike_count = rpois(20, 20)
)

让我们创建一个基本图，我们可以用不同的方式添加矩形：

persh_plot =
    ggplot(
        data = Pershing,
        aes(x = created.at.x, y = available_bike_count)
    ) +
    geom_point(color = "red") +
    ylab("Available Bikes") +
    xlab("time") + theme_bw()

我喜欢其他答案的geom_rect，但lapply是不必要的。此外，美学常数（如ymin = -Inf）应始终设置在aes()的外。我们还需要设置inherit.aes = FALSE以防止早期的x和y映射被继承：

persh_plot + geom_rect( data = Pershing_trucks, aes(xmin = stoptime, xmax = starttime), ymin = -Inf, ymax = Inf, fill = 'gray80', alpha = 0.2, inherit.aes = FALSE )

我不确定你想要展示什么 - 但是这里矩形的alpha透明度给出了相当好的重叠指示。请记住，我的Pershing数据与您的数据结构相似，但是会进行模拟。您可能希望在矩形图层之后添加geom_point()图层，使点位于顶部。

这并不能很好地匹配您想要的输出，所以这里有一个没有任何填充的轮廓矩形的版本，y min和max在0和20处就像你的情节一样。对我来说看起来很可怕，但对每个人来说都很糟糕：

persh_plot + geom_rect( data = Pershing_trucks, aes(xmin = stoptime, xmax = starttime), ymin = 0, ymax = 20, color = "black", fill = NA, size = 1, inherit.aes = FALSE ) + expand_limits(y = 0) # just to force y down to 0 with my simulated data

使用ggplot在POSIXct截距处添加垂直线

2 个答案: