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r - 如何根据条件和上面的行来操作行的值？

转载 作者：行者123 更新时间：2023-12-02 19:23:42 25 4
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我有一个 df，我想按链接对其进行分组，并按时间对其进行排序。然后，每次 type == 'vehicle Leaves Traffic' 时，count 列中的单元格应在前一行中的单元格值的基础上添加 +1。如果type == '车辆进入交通'，则应从前一行中扣除 1。

需要澄清的是，不应更改前一行的值，而是应基于前一行的值更改该行的值。

这是我的方法，但我得到的只是 0、1 和 2。我预计某些链接会有更高的值。

parking_min <- cars %>% 
  group_by(link)%>% 
  dplyr::mutate(count = if_else(type == 'vehicle leaves traffic', lag(count, n=1,order_by=time)+1,lag(count))) %>%
  dplyr::mutate(count = if_else(type == 'vehicle enters traffic',lag(count, n=1, order_by=time)-1,lag(count)))

这是我的数据:

structure(list(time = c("23707.0", "31209.0", "31210.0", "36230.0", 
"36231.0", "38925.0", "39583.0", "40198.0", "40818.0", "41974.0", 
"42895.0", "43099.0", "43683.0", "44645.0", "45730.0", "46785.0", 
"48846.0", "48905.0", "52790.0", "53829.0", "55021.0", "58240.0", 
"58635.0", "59682.0", "59683.0", "63740.0", "63776.0", "68607.0", 
"24607.0", "25218.0", "26442.0", "28004.0", "29884.0", "37750.0", 
"42623.0", "43965.0", "49426.0", "54925.0", "56688.0", "56689.0", 
"57738.0", "61900.0", "64221.0", "67065.0", "69404.0", "77454.0", 
"83588.0", "89601.0", "27452.0", "27743.0", "33598.0", "36297.0", 
"60604.0", "62940.0", "63184.0", "63250.0", "20911.0", "27013.0", 
"29815.0", "49550.0", "53991.0", "55620.0", "61200.0", "67672.0", 
"78558.0", "79245.0", "27006.0", "29085.0", "31411.0", "36747.0", 
"36877.0", "38434.0", "38807.0", "44607.0", "58068.0", "58800.0", 
"65236.0", "65431.0", "69013.0", "69072.0", "25609.0", "29520.0", 
"46559.0", "66916.0", "74904.0", "78407.0", "20445.0", "23938.0", 
"24017.0", "24281.0", "25283.0", "25873.0", "27137.0", "27342.0", 
"28790.0", "28910.0", "29241.0", "29345.0", "29465.0", "29525.0", 
"29909.0", "30719.0", "31092.0", "31356.0", "31786.0", "32829.0", 
"33966.0", "34175.0", "34545.0", "34888.0", "34977.0", "35775.0", 
"35950.0", "38409.0", "38636.0", "39259.0", "39527.0", "40256.0", 
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"42895.0", "43103.0", "43223.0", "43599.0", "44476.0", "44903.0", 
"44904.0", "45774.0", "45834.0", "45915.0", "46230.0", "46287.0", 
"46626.0", "47215.0", "48784.0", "50266.0", "50361.0", "50763.0", 
"52685.0", "52793.0", "54688.0", "55105.0", "56310.0", "57885.0", 
"58093.0", "58153.0", "59223.0", "60460.0", "60597.0", "60676.0", 
"61307.0", "61457.0", "61974.0", "62141.0", "62165.0", "62347.0", 
"62591.0", "64175.0", "64280.0", "65555.0", "65808.0", "66038.0", 
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"71069.0", "71741.0", "72121.0", "72292.0", "73236.0", "73775.0", 
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"29707.0", "30802.0", "31052.0", "33174.0", "34020.0", "36031.0", 
"36392.0", "38037.0", "40717.0", "42099.0", "43154.0", "44413.0", 
"44414.0", "44730.0", "44770.0", "46863.0", "46876.0", "48318.0", 
"48435.0", "48493.0", "48700.0", "51736.0", "51747.0", "51748.0", 
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"90207.0", "90208.0", "34426.0", "74433.0", "32354.0", "64161.0", 
"67914.0", "21864.0"), type = c("vehicle enters traffic", "vehicle leaves traffic", 
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"vehicle enters traffic", "vehicle enters traffic", "vehicle leaves traffic", 
"vehicle enters traffic", "vehicle enters traffic", "vehicle leaves traffic", 
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273444L, 273513L, 273515L, 274788L, 278257L, 281213L, 283103L, 
285741L, 288499L, 293964L, 294807L, 296677L, 299364L, 300811L, 
301489L, 304733L, 306468L, 307953L, 322532L, 322917L, 324007L, 
324134L, 329621L, 329788L, 331476L, 16560L, 79874L, 79878L, 198570L, 
198576L, 206594L, 227352L, 292291L, 33304L, 33809L, 37031L, 42365L, 
47741L, 53329L, 54310L, 55545L, 56255L, 62460L, 63930L, 75298L, 
79478L, 89112L, 90807L, 98845L, 111205L, 119068L, 126025L, 134327L, 
134337L, 136437L, 136711L, 149242L, 149320L, 158130L, 158789L, 
159131L, 160368L, 177328L, 177392L, 177394L, 179845L, 180260L, 
181812L, 183400L, 184268L, 184922L, 185978L, 191177L, 193860L, 
201573L, 202492L, 212365L, 240333L, 242817L, 246833L, 246834L, 
249842L, 250280L, 254468L, 262163L, 262164L, 263107L, 263117L, 
272463L, 274866L, 279549L, 282270L, 286442L, 286606L, 287265L, 
292441L, 293100L, 298081L, 308952L, 312468L, 312471L, 314309L, 
317028L, 334227L, 336208L, 17419L, 19144L, 55246L, 55251L, 70799L, 
73085L, 154041L, 172793L, 173296L, 175721L, 196355L, 206048L, 
209794L, 216742L, 274263L, 285199L, 287908L, 302276L, 330230L, 
330233L, 335274L, 335275L, 81402L, 308426L, 71000L, 255248L, 
280759L, 10158L), class = "data.frame")

可能的输出:

          time                   type vehicle_id link count
18798  23707.0 vehicle enters traffic    1267069   90     0 #start point
64777  31209.0 vehicle leaves traffic     810534   90     1 #+1
64783  31210.0 vehicle enters traffic     810534   90     0 #-1
90025  36230.0 vehicle leaves traffic      51825   90     1
90030  36231.0 vehicle enters traffic      51825   90     0
102868 38925.0 vehicle leaves traffic    1326473   90     1
105834 39583.0 vehicle leaves traffic    1199672   90     2 #here as well 1+1 =2
108690 40198.0 vehicle leaves traffic    1111105   90     3 #2+1 =3
111727 40818.0 vehicle enters traffic    1111105   90     2 #3-1 =2
118283 41974.0 vehicle leaves traffic     532654   90     3
124349 42895.0 vehicle enters traffic     532654   90     2
125700 43099.0 vehicle leaves traffic    1267069   90     3
129642 43683.0 vehicle enters traffic    1199672   90     2
135888 44645.0 vehicle leaves traffic    1398907   90     3
142577 45730.0 vehicle enters traffic    1398907   90     2
148772 46785.0 vehicle leaves traffic    1239391   90     3
161264 48846.0 vehicle enters traffic    1239391   90     2
161590 48905.0 vehicle enters traffic    1326473   90     1
182778 52790.0 vehicle leaves traffic      46491   90     2

最终我想找到每个链接的最大计数。但这可以在另一个步骤中完成，并且不需要成为解决方案的一部分，也许它有助于澄清问题。

最佳答案

我想这就是你想要的:

df %>%
    arrange(link, time) %>%
    group_by(link) %>%
    mutate(vehicles_entered_traffic = cumsum(type == "vehicle enters traffic")
           , vehicles_left_traffic = cumsum(type == "vehicle leaves traffic")
           , count = count[1] + vehicles_left_traffic - vehicles_entered_traffic)

关于r - 如何根据条件和上面的行来操作行的值？，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/62678318/

25 4 0
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