如何基於R中的多列聚合一個數據框？

Question

我在問題末尾有以下 df （ dput() ）：

          link person   type      ID1   bin
1311752 793482 514677   departure 347 36900
1020897  66154 514677   arrival   379 36900
1376554 858880 514679   departure 374 42300
1374956 858880 514679   arrival   374 46800
1567933 992830 514680   arrival   140 31500
1568804 992830 514680   departure 140 32400
726546   87723 514681   departure  42 25200
726547  481929 514681   arrival   233 27900
723875  481929 514681   departure 233 45000
1396595  87723 514681   arrival    42 45900

我想要的是創建一個新的 df，在這里我可以看到哪個person從（ type=="departure" ）哪個區域（ ID1 ）到（ type=="arrival" ）哪個區域（ ID1 ）以及在哪個出發bin 。

從上面示例的最后 4 行可以看出，同一person可能有多個arrival和departure 。 因此，重要的是，將彼此最接近的兩者結合起來（因此是最小的 delta bin ）。

因此，新的 df 應如下所示：

person  departure   arrival bin
514677  347         379     36900
514679  374         374     42300
514681  42          233     25200
514681  233         42      45000
...

如您所見，人514681在 42 和 233 之間來回移動。

我想你可以說我想根據person聚合數據。 我不太確定如何做到這一點，並且很樂意提供幫助！

structure(list(link = c("793482", "66154", "858880", "858880", 
"992830", "992830", "858880", "858880", "514143", "87723", "481929", 
"481929", "87723", "87723", "964586", "87723", "1013453", "pt_8591034", 
"973606", "pt_8591034", "481929", "481929", "87723", "87723", 
"399738", "399738", "87723", "738635", "481929", "738635", "481929", 
"738635", "301867", "89053", "92917", "92917", "981899", "981899", 
"89053", "92917", "89053", "89053", "699715", "699715", "89053", 
"452176", "738635", "452176", "738635", "641738", "712438", "699715", 
"215822", "621953", "634264", "362138", "634264", "634264", "763815", 
"763815", "631191", "631191", "763815", "763815", "634264", "634264", 
"10826", "10826", "634264", "999977", "1046826", "1046826", "634264", 
"999977", "848815", "848815", "999977", "999977", "848815", "848815", 
"999977", "261239", "993653", "287772", "763815", "763815", "287772", 
"494898", "824071", "594222", "494898", "494898", "452642", "452642", 
"494898", "494898", "452642", "494898", "787840", "442285"), 
    person = c(514677L, 514677L, 514679L, 514679L, 514680L, 514680L, 
    514680L, 514680L, 514680L, 514681L, 514681L, 514681L, 514681L, 
    514682L, 514682L, 514683L, 514683L, 514684L, 514684L, 514684L, 
    514684L, 514684L, 514684L, 514685L, 514685L, 514685L, 514685L, 
    514688L, 514688L, 514688L, 514688L, 514690L, 514690L, 514707L, 
    514707L, 514707L, 514707L, 514707L, 514707L, 514708L, 514708L, 
    514709L, 514709L, 514709L, 514709L, 514710L, 514710L, 514710L, 
    514710L, 514711L, 514711L, 514733L, 514733L, 514757L, 514757L, 
    514757L, 514757L, 514759L, 514759L, 514759L, 514759L, 514759L, 
    514759L, 514759L, 514759L, 514760L, 514760L, 514760L, 514760L, 
    514774L, 514774L, 514774L, 514774L, 514774L, 514774L, 514774L, 
    514774L, 514774L, 514774L, 514774L, 514774L, 514782L, 514782L, 
    514786L, 514786L, 514786L, 514786L, 514802L, 514802L, 514802L, 
    514802L, 514803L, 514803L, 514803L, 514803L, 514803L, 514803L, 
    514804L, 514804L, 514805L), type = c("departure", "arrival", 
    "departure", "arrival", "arrival", "departure", "arrival", 
    "departure", "arrival", "departure", "arrival", "departure", 
    "arrival", "departure", "arrival", "departure", "arrival", 
    "arrival", "departure", "departure", "arrival", "departure", 
    "arrival", "departure", "arrival", "departure", "arrival", 
    "departure", "arrival", "departure", "arrival", "departure", 
    "arrival", "departure", "arrival", "departure", "arrival", 
    "departure", "arrival", "departure", "arrival", "departure", 
    "arrival", "departure", "arrival", "departure", "arrival", 
    "arrival", "departure", "departure", "arrival", "departure", 
    "arrival", "departure", "arrival", "departure", "arrival", 
    "departure", "arrival", "departure", "arrival", "departure", 
    "arrival", "departure", "arrival", "departure", "arrival", 
    "departure", "arrival", "departure", "arrival", "departure", 
    "arrival", "departure", "arrival", "departure", "arrival", 
    "departure", "arrival", "departure", "arrival", "departure", 
    "arrival", "departure", "arrival", "departure", "arrival", 
    "departure", "arrival", "departure", "arrival", "departure", 
    "arrival", "departure", "arrival", "departure", "arrival", 
    "departure", "arrival", "departure"), ID1 = c(347L, 379L, 
    374L, 374L, 140L, 140L, 374L, 374L, 401L, 42L, 233L, 233L, 
    42L, 42L, 496L, 42L, 235L, 172L, 231L, 172L, 233L, 233L, 
    42L, 42L, 267L, 267L, 42L, 58L, 233L, 58L, 233L, 58L, 292L, 
    96L, 264L, 264L, 26L, 26L, 96L, 264L, 96L, 96L, 266L, 266L, 
    96L, 57L, 58L, 57L, 58L, 123L, 55L, 266L, 77L, 412L, 407L, 
    410L, 407L, 407L, 297L, 297L, 169L, 169L, 297L, 297L, 407L, 
    407L, 566L, 566L, 407L, 403L, 380L, 380L, 407L, 403L, 436L, 
    436L, 403L, 403L, 436L, 436L, 403L, 545L, 324L, 448L, 297L, 
    297L, 448L, 209L, 152L, 205L, 209L, 209L, 204L, 204L, 209L, 
    209L, 204L, 209L, 383L, 181L), bin = c(36900, 36900, 42300, 
    46800, 31500, 32400, 34200, 61200, 72000, 25200, 27900, 45000, 
    45900, 27900, 31500, 30600, 33300, 56700, 56700, 60300, 61200, 
    63900, 65700, 28800, 32400, 75600, 77400, 24300, 26100, 45900, 
    47700, 51300, 53100, 27900, 31500, 36900, 38700, 41400, 42300, 
    62100, 63900, 15300, 16200, 45900, 47700, 35100, 35100, 67500, 
    67500, 63900, 65700, 45900, 46800, 63000, 64800, 90000, 90900, 
    27000, 28800, 45000, 46800, 63000, 67500, 68400, 72000, 48600, 
    50400, 53100, 55800, 37800, 38700, 40500, 41400, 47700, 48600, 
    51300, 52200, 62100, 63000, 63900, 64800, 22500, 24300, 19800, 
    20700, 54000, 57600, 21600, 22500, 55800, 56700, 36900, 38700, 
    51300, 52200, 62100, 63900, 30600, 34200, 33300)), row.names = c(1311752L, 
1020897L, 1376554L, 1374956L, 1567933L, 1568804L, 1378922L, 1378604L, 
796332L, 1396610L, 726547L, 723875L, 1396595L, 1398179L, 1513826L, 
1396821L, 27568L, 1607272L, 1542798L, 1606758L, 721147L, 720198L, 
1397549L, 1398033L, 621908L, 626763L, 1397225L, 1184210L, 729418L, 
1185149L, 728038L, 1183207L, 465692L, 1426554L, 1460666L, 1457289L, 
1551709L, 1550925L, 1429217L, 1461183L, 1427235L, 1428930L, 1117203L, 
1119814L, 1431191L, 683362L, 1183236L, 684338L, 1184602L, 990483L, 
1142535L, 1125893L, 288323L, 947577L, 966966L, 544664L, 969372L, 
964351L, 1230180L, 1231933L, 960341L, 960438L, 1238195L, 1241438L, 
965853L, 964667L, 105034L, 106179L, 966724L, 1586724L, 72120L, 
76232L, 969048L, 1587092L, 1360314L, 1361152L, 1585499L, 1586919L, 
1361549L, 1359631L, 1587109L, 378600L, 1573640L, 428095L, 1236840L, 
1235995L, 430374L, 757402L, 1331227L, 916001L, 760182L, 757620L, 
686066L, 685765L, 759010L, 760140L, 687455L, 758617L, 1287055L, 
676520L), class = "data.frame")

Answer 1

使用dplyr ，這可能是這樣的：

library(dplyr)
data %>% 
  group_by(person) %>% 
  summarize(departure = ID1[type == "departure"][1],
            arrival = ID1[type == "arrival"][1],
            bin = bin[type == "departure"][1])

這是一個試圖滿足附加邏輯的改進版本。 由於問題不太清楚，我很確定它還不是 100% 沒問題。

data %>%
  arrange(person, bin) %>%
  group_by(person) %>%
  mutate(pair = rep(row_number(), each = 2, length.out = n())) %>%
  group_by(person, pair) %>%
  summarize(departure = ID1[type == "departure"][1],
            arrival = ID1[type == "arrival"][1],
            bin = bin[type == "departure"][1])

Answer 2

在基礎 R 中，我們可以拆分數據並僅保留超過 1 行的人/箱組合（意味着有到達和離開），然后提取數據。

splitdata <- split(df,with(df,paste0(person,bin)))
splitdata <- splitdata[sapply(splitdata,nrow)>1]

do.call(rbind,
    lapply(splitdata, function(x) 
        data.frame(
            person = x[1,2], 
            departure = x$ID1[x$type == "departure"],
            arrival = x$ID1[x$type == "arrival"],
            bin = x[1,5])))

output：

            person departure arrival   bin
51467736900 514677       347     379 36900
51468456700 514684       231     172 56700
51471035100 514710        57      58 35100
51471067500 514710        58      57 67500