我在test中有一个由route_id分组的纬度/经度列表。我的目标是在单独的数据框obs中将观察结果附加到每个组的末尾 - 匹配列为route_id。怎么会在R中这样做呢？
> test
route_id start_lon start_lat
1 2 37.3387 55.7278
2 2 37.3377 55.7281
3 2 37.3358 55.7285
4 2 37.3359 55.7286
5 2 37.3449 55.7356
6 2 37.3394 55.7403
7 3 37.3387 55.7278
8 3 37.3377 55.7281
9 3 37.3321 55.7293
10 3 37.3360 55.7346
11 3 37.3309 55.7451
12 6 37.3387 55.7278
13 6 37.3377 55.7281
14 6 37.3384 55.7324
15 6 37.3389 55.7343
16 6 37.3521 55.7294
17 6 37.3537 55.7233
18 6 37.3722 55.7237
19 6 37.3734 55.7235
20 6 37.3999 55.7424
21 6 37.3992 55.7432
22 6 37.3565 55.7765
23 6 37.3564 55.7761
24 6 37.3555 55.7765
25 6 37.3514 55.7761
26 6 37.3500 55.7766
27 6 37.3447 55.7726
> obs
route_id end_lon end_lat
6 2 37.3382 55.7401
11 3 37.3313 55.7463
27 6 37.3389 55.7691
dput(test)
structure(list(route_id = c(2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L,
3L, 3L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L), start_lon = c(37.3387, 37.3377, 37.3358, 37.3359, 37.3449,
37.3394, 37.3387, 37.3377, 37.3321, 37.336, 37.3309, 37.3387,
37.3377, 37.3384, 37.3389, 37.3521, 37.3537, 37.3722, 37.3734,
37.3999, 37.3992, 37.3565, 37.3564, 37.3555, 37.3514, 37.35,
37.3447), start_lat = c(55.7278, 55.7281, 55.7285, 55.7286, 55.7356,
55.7403, 55.7278, 55.7281, 55.7293, 55.7346, 55.7451, 55.7278,
55.7281, 55.7324, 55.7343, 55.7294, 55.7233, 55.7237, 55.7235,
55.7424, 55.7432, 55.7765, 55.7761, 55.7765, 55.7761, 55.7766,
55.7726)), .Names = c("route_id", "start_lon", "start_lat"), row.names = c(NA,
27L), class = "data.frame")
dput(obs)
structure(list(route_id = c(2L, 3L, 6L), end_lon = c(37.3382,
37.3313, 37.3389), end_lat = c(55.7401, 55.7463, 55.7691)), .Names = c("route_id",
"end_lon", "end_lat"), row.names = c(6L, 11L, 27L), class = "data.frame")
答案 0 :(得分：0)
我们可以将它们放在list中，与rbindlist绑定，然后在＆＃39; route_id＆＃39;上执行order。
library(data.table)
rbindlist(list(test, obs))[order(route_id)]
# route_id start_lon start_lat
# 1: 2 37.3387 55.7278
# 2: 2 37.3377 55.7281
# 3: 2 37.3358 55.7285
# 4: 2 37.3359 55.7286
# 5: 2 37.3449 55.7356
# 6: 2 37.3394 55.7403
# 7: 2 37.3382 55.7401
# 8: 3 37.3387 55.7278
# 9: 3 37.3377 55.7281
#10: 3 37.3321 55.7293
#11: 3 37.3360 55.7346
#12: 3 37.3309 55.7451
#13: 3 37.3313 55.7463
#14: 6 37.3387 55.7278
#15: 6 37.3377 55.7281
#16: 6 37.3384 55.7324
#17: 6 37.3389 55.7343
#18: 6 37.3521 55.7294
#19: 6 37.3537 55.7233
#20: 6 37.3722 55.7237
#21: 6 37.3734 55.7235
#22: 6 37.3999 55.7424
#23: 6 37.3992 55.7432
#24: 6 37.3565 55.7765
#25: 6 37.3564 55.7761
#26: 6 37.3555 55.7765
#27: 6 37.3514 55.7761
#28: 6 37.3500 55.7766
#29: 6 37.3447 55.7726
#30: 6 37.3389 55.7691