问题
I've been practicing and learning wrangling R data frames with columns that contain lubridate data types, such as an example problem in my other question.
Now, I am trying to do the equivalent of joining two data frames, but joining them by whether one timestamp in one data frame falls within an interval in the other data frame. For example:
This is df1:
> glimpse(df1)
Observations: 6,160
Variables: 4
$ upload_id <int> 2, 2, 2, 2, 2, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, ...
$ site_id <int> 2, 2, 2, 2, 2, 4, 4, 7, 7, 7, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, ...
$ segment_id <int> 1, 2, 3, 4, 5, 1, 2, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, ...
$ interval <S4: Interval> 2015-04-12 UTC--2015-04-19 UTC, 2015-04-19 UTC--201...
Where there is a bunch of lubridate time intervals each with a corresponding unique combination of upload_id, site_id, and segment_id.
And this is df2:
> glimpse(df2)
Observations: 32,385
Variables: 3
$ sequence_id <int> 2047, 2067, 2069, 2072, 2075, 2081, 2086, 2091, 2096, 2104,...
$ upload_id <int> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 5, 5,...
$ taken <dttm> 2015-04-11 23:09:59, 2015-04-15 19:17:10, 2015-04-16 07:42...
Where there is a series of timestamps in column taken with corresponding unique combinations of sequence_id and upload_id.
Essentially, I want to left_join(df2, df1) where the needed by argument considers two things: (1) the shared upload_id column; and (2) whether taken in df2 falls within interval in df1. This is because for any given taken, it might fall %within% multiple intervals, and vice versa, so I want to use upload_id as a unique identifier for each taken so that each taken in df2 will be matched to only one other row in df1. After the join operation, I expect the new data frame to have six columns: sequence_id, taken, upload_id, site_id, segment_id, and interval. How can this be done tidyly?
EDIT: A comment suggested that uploading .Rdata files may be untrustworthy and another stated that it's against the policy here. So I removed the .Rdata files, and I tried to take a 300-row subset of each data frame via dput(), here is df1:
structure(list(upload_id = c(1050L, 1582L, 2336L, 2665L, 1007L,
2148L, 275L, 2738L, 1501L, 64L, 2737L, 1547L, 2146L, 2596L, 457L,
2141L, 2790L, 362L, 2835L, 2741L, 575L, 914L, 2820L, 2572L, 2791L,
2157L, 1117L, 1535L, 2738L, 794L, 1335L, 2737L, 2570L, 1597L,
300L, 460L, 1701L, 2142L, 274L, 339L, 2109L, 500L, 2184L, 2837L,
1238L, 2837L, 2727L, 1175L, 1524L, 303L, 1714L, 1412L, 1894L,
340L, 1495L, 869L, 995L, 2438L, 1974L, 2762L, 205L, 1581L, 1527L,
2818L, 1617L, 2537L, 1956L, 638L, 1808L, 2151L, 771L, 2709L,
2185L, 2015L, 2511L, 1163L, 2557L, 1377L, 2213L, 2560L, 1417L,
1934L, 1860L, 2772L, 2614L, 2698L, 421L, 2609L, 1418L, 2355L,
463L, 2697L, 347L, 1531L, 1427L, 2548L, 2218L, 2781L, 1962L,
396L, 234L, 2846L, 4L, 2742L, 2838L, 1676L, 1635L, 2810L, 1990L,
2514L, 2809L, 1354L, 2668L, 2737L, 1606L, 764L, 1176L, 1442L,
519L, 2584L, 1021L, 352L, 2314L, 2662L, 1368L, 1043L, 2207L,
2792L, 684L, 1806L, 2743L, 2557L, 1971L, 1510L, 418L, 1866L,
1569L, 1717L, 1992L, 1629L, 2189L, 316L, 2030L, 2840L, 2307L,
1506L, 1962L, 1249L, 2791L, 670L, 592L, 236L, 2781L, 793L, 2790L,
2640L, 2517L, 855L, 626L, 1303L, 2241L, 1541L, 910L, 155L, 1617L,
29L, 916L, 732L, 2006L, 2742L, 2788L, 2830L, 2664L, 1455L, 1062L,
937L, 1543L, 781L, 737L, 901L, 2633L, 194L, 1000L, 1170L, 1567L,
2826L, 73L, 801L, 970L, 1327L, 2688L, 1538L, 2306L, 2170L, 1977L,
2367L, 186L, 1990L, 2606L, 2000L, 2818L, 396L, 696L, 630L, 2835L,
2067L, 1540L, 51L, 511L, 2587L, 2737L, 1961L, 594L, 1867L, 1042L,
116L, 1532L, 760L, 2662L, 2814L, 2585L, 2596L, 2837L, 1870L,
1971L, 73L, 2595L, 1955L, 692L, 2062L, 2742L, 2084L, 1098L, 2205L,
1404L, 2627L, 809L, 2684L, 2570L, 322L, 2605L, 2016L, 2782L,
54L, 2254L, 1165L, 655L, 532L, 732L, 534L, 2664L, 1880L, 1444L,
1920L, 477L, 2728L, 2640L, 1434L, 100L, 2587L, 1545L, 250L, 282L,
1756L, 940L, 2826L, 1005L, 2835L, 2152L, 203L, 1970L, 579L, 1234L,
2682L, 1050L, 2594L, 199L, 945L, 758L, 1262L, 796L, 2156L, 921L,
1961L, 817L, 486L, 982L, 394L, 1928L, 2237L, 2570L, 2144L, 2386L,
325L, 2729L, 2685L, 901L, 2042L, 141L, 2248L), site_id = c(184L,
278L, 73L, 364L, 231L, 244L, 72L, 364L, 74L, 52L, 350L, 248L,
223L, 306L, 117L, 223L, 350L, 115L, 357L, 295L, 113L, 74L, 350L,
348L, 364L, 267L, 74L, 248L, 364L, 198L, 73L, 350L, 347L, 260L,
103L, 134L, 271L, 223L, 72L, 120L, 73L, 145L, 214L, 350L, 74L,
350L, 361L, 227L, 160L, 73L, 73L, 237L, 292L, 110L, 267L, 205L,
230L, 74L, 306L, 295L, 47L, 261L, 44L, 357L, 280L, 355L, 199L,
119L, 160L, 73L, 186L, 348L, 214L, 295L, 348L, 160L, 306L, 74L,
191L, 350L, 73L, 191L, 191L, 364L, 306L, 364L, 74L, 73L, 74L,
74L, 155L, 350L, 54L, 248L, 260L, 114L, 241L, 360L, 292L, 31L,
36L, 73L, 7L, 360L, 364L, 74L, 262L, 361L, 292L, 350L, 360L,
256L, 73L, 350L, 280L, 184L, 44L, 258L, 146L, 347L, 217L, 44L,
113L, 357L, 191L, 233L, 245L, 360L, 156L, 293L, 360L, 306L, 292L,
226L, 74L, 36L, 73L, 73L, 199L, 244L, 241L, 110L, 295L, 361L,
248L, 251L, 292L, 113L, 364L, 74L, 160L, 105L, 360L, 202L, 350L,
306L, 351L, 201L, 160L, 247L, 320L, 248L, 213L, 54L, 280L, 41L,
198L, 187L, 74L, 360L, 357L, 287L, 350L, 44L, 234L, 105L, 248L,
200L, 174L, 198L, 73L, 54L, 217L, 236L, 277L, 361L, 63L, 194L,
160L, 73L, 361L, 248L, 320L, 74L, 293L, 73L, 68L, 292L, 350L,
199L, 357L, 31L, 166L, 165L, 357L, 312L, 248L, 42L, 148L, 350L,
350L, 147L, 116L, 248L, 174L, 47L, 226L, 74L, 357L, 73L, 348L,
306L, 350L, 293L, 292L, 63L, 348L, 298L, 174L, 316L, 360L, 312L,
227L, 319L, 237L, 350L, 160L, 348L, 347L, 108L, 306L, 293L, 361L,
54L, 74L, 74L, 73L, 56L, 187L, 74L, 350L, 199L, 74L, 271L, 56L,
360L, 306L, 226L, 72L, 350L, 248L, 90L, 91L, 74L, 44L, 361L,
217L, 357L, 73L, 55L, 191L, 73L, 226L, 347L, 184L, 357L, 95L,
218L, 196L, 249L, 197L, 74L, 74L, 147L, 199L, 145L, 217L, 136L,
295L, 73L, 347L, 223L, 113L, 47L, 350L, 350L, 198L, 310L, 23L,
74L), segment_id = c(3L, 1L, 1L, 1L, 1L, 2L, 1L, 5L, 1L, 1L,
7L, 1L, 2L, 7L, 1L, 1L, 3L, 3L, 7L, 1L, 2L, 1L, 8L, 2L, 11L,
1L, 1L, 3L, 6L, 1L, 1L, 8L, 2L, 2L, 4L, 5L, 3L, 1L, 1L, 1L, 1L,
3L, 1L, 17L, 1L, 3L, 4L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 3L, 3L,
5L, 1L, 1L, 2L, 1L, 1L, 2L, 7L, 4L, 2L, 3L, 1L, 1L, 1L, 3L, 3L,
1L, 6L, 2L, 2L, 5L, 1L, 2L, 5L, 1L, 2L, 3L, 2L, 4L, 3L, 1L, 1L,
2L, 1L, 4L, 13L, 3L, 2L, 1L, 2L, 3L, 6L, 5L, 5L, 3L, 1L, 2L,
7L, 10L, 1L, 1L, 1L, 7L, 4L, 2L, 2L, 1L, 9L, 1L, 1L, 1L, 10L,
3L, 4L, 6L, 1L, 4L, 9L, 1L, 1L, 1L, 10L, 2L, 1L, 4L, 4L, 1L,
1L, 1L, 1L, 1L, 1L, 8L, 1L, 1L, 1L, 7L, 15L, 2L, 8L, 7L, 3L,
6L, 1L, 1L, 1L, 8L, 1L, 23L, 4L, 3L, 2L, 2L, 2L, 2L, 4L, 1L,
1L, 3L, 2L, 5L, 1L, 1L, 6L, 5L, 1L, 12L, 2L, 2L, 1L, 1L, 3L,
1L, 2L, 1L, 2L, 5L, 2L, 1L, 6L, 4L, 2L, 1L, 1L, 1L, 3L, 1L, 1L,
2L, 1L, 4L, 5L, 5L, 7L, 4L, 17L, 1L, 2L, 2L, 1L, 1L, 1L, 3L,
1L, 18L, 4L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 8L, 6L, 2L, 1L,
6L, 1L, 1L, 2L, 1L, 1L, 10L, 1L, 1L, 1L, 2L, 10L, 1L, 15L, 4L,
4L, 3L, 4L, 12L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 11L, 1L, 1L, 2L,
2L, 2L, 7L, 3L, 1L, 2L, 4L, 2L, 2L, 1L, 2L, 16L, 2L, 4L, 1L,
2L, 1L, 1L, 2L, 14L, 1L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 6L,
1L, 1L, 3L, 1L, 2L, 1L, 7L, 2L, 1L, 2L, 2L, 15L, 6L, 1L, 1L,
1L), interval = new("Interval", .Data = c(604800, 86400, 86400,
259200, 604800, 604800, 604800, 604800, 86400, 86400, 604800,
604800, 518400, 604800, 86400, 604800, 604800, 604800, 604800,
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604800, 345600, 604800, 86400, 86400, 604800, 604800, 604800,
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259200, 86400, 86400, 86400, 518400, 86400, 86400, 604800, 604800,
259200, 345600, 604800, 604800, 604800, 604800, 172800, 604800,
604800, 259200, 604800, 86400, 86400, 604800, 604800, 604800,
86400, 172800, 604800, 86400, 604800, 604800, 604800, 172800,
432000, 604800, 518400, 345600, 518400, 86400, 86400, 604800,
604800, 604800, 604800, 172800, 604800, 86400, 604800, 518400,
86400, 604800, 604800, 518400, 172800, 259200, 86400, 86400),
start = structure(c(1463097600, 1479081600, 1499817600, 1511654400,
1464912000, 1493337600, 1440028800, 1514073600, 1478995200,
1438128000, 1507593600, 1475193600, 1491782400, 1507593600,
1445212800, 1487462400, 1505174400, 1445731200, 1519084800,
1515456000, 1449964800, 1463529600, 1508198400, 1504483200,
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1460073600, 1472860800, 1508198400, 1504483200, 1475798400,
1444348800, 1451692800, 1481587200, 1488153600, 1439769600,
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1470441600, 1505174400, 1510704000, 1469145600, 1478563200,
1444780800, 1483228800, 1475280000, 1485129600, 1444867200,
1477267200, 1462492800, 1464652800, 1503532800, 1488931200,
1516060800, 1441584000, 1475884800, 1479772800, 1519084800,
1478908800, 1505952000, 1486598400, 1444608000, 1485216000,
1493942400, 1459814400, 1505088000, 1494201600, 1488240000,
1504483200, 1469491200, 1506384000, 1474502400, 1495411200,
1506384000, 1475366400, 1487548800, 1485734400, 1512259200,
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1475193600, 1506038400, 1495411200, 1513036800, 1487548800,
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1479340800, 1494201600, 1444867200, 1488844800, 1517356800,
1495756800, 1477785600, 1488758400, 1468800000, 1514678400,
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1517270400, 1505779200, 1505606400, 1462147200, 1453852800,
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1516060800, 1491264000, 1475193600, 1437696000, 1449446400,
1503964800, 1514246400, 1487030400, 1452124800, 1485216000,
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1471651200, 1509408000, 1460592000, 1512345600, 1505692800,
1445040000, 1505174400, 1487030400, 1515542400, 1437868800,
1496620800, 1469577600, 1455235200, 1450224000, 1.458e+09,
1450828800, 1510012800, 1485388800, 1476835200, 1487894400,
1447977600, 1510617600, 1507593600, 1474934400, 1438905600,
1504569600, 1477008000, 1443312000, 1443312000, 1484524800,
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1441238400, 1488758400, 1452643200, 1470700800, 1511740800,
1461888000, 1508803200, 1441238400, 1463616000, 1455062400,
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1460073600, 1448236800, 1463961600, 1447372800, 1485820800,
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1504569600, 1512432000, 1463097600, 1490745600, 1440028800,
1496448000), class = c("POSIXct", "POSIXt"), tzone = "UTC"),
tzone = "UTC")), row.names = c(NA, -300L), class = c("tbl_df",
"tbl", "data.frame"))
And here is df2:
structure(list(sequence_id = c(10545297L, 5696697L, 26853675L,
26800598L, 5477912L, 3564676L, 11545989L, 26788357L, 26790778L,
4682984L, 12887744L, 4254651L, 6472328L, 18236650L, 26829066L,
26784117L, 26886686L, 797197L, 26820954L, 26791541L, 11657412L,
3960964L, 10189029L, 21286407L, 12914356L, 26793531L, 26802965L,
12435451L, 5484298L, 26827162L, 26853752L, 25711869L, 9030699L,
14386264L, 26802894L, 26377583L, 13291447L, 1851672L, 26790782L,
9900386L, 26797667L, 6561255L, 26818879L, 11648069L, 14259988L,
26809952L, 26809264L, 15071783L, 26791374L, 26853008L, 6762100L,
26853620L, 26880265L, 26878102L, 26809279L, 26787754L, 5502014L,
17810813L, 18236753L, 5568166L, 9252741L, 26786093L, 18418962L,
1218679L, 26801395L, 16954415L, 26853619L, 26800113L, 26817488L,
26811724L, 26809375L, 26809666L, 5869152L, 7681085L, 26894216L,
15810230L, 26829083L, 26817434L, 26789887L, 26785533L, 26796803L,
26786930L, 26825007L, 26784040L, 26810066L, 26853657L, 18236660L,
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26902434L, 3948950L, 26816568L, 11453844L, 26826969L, 26813846L,
26897750L, 26802715L, 26790888L, 26815971L, 26797683L, 4726015L,
4617411L, 26797067L, 9252726L, 26797067L, 26785670L, 26789320L,
26901211L, 26894241L, 499985L, 26825082L, 21774171L, 26803324L,
26815122L, 56056L, 18236919L, 5425808L, 13209778L, 4726052L,
14386262L, 5477952L, 5564830L, 9756473L, 26894173L, 7136912L,
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26827055L, 16102402L, 26796994L, 26784422L, 14725739L, 26901257L,
26853712L, 26785221L, 26793075L, 11658007L, 26823570L, 26791524L,
26797467L, 26796972L, 8501567L, 26799777L, 5572466L, 26787249L,
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26805358L, 18158022L, 15810244L, 26878116L, 10623114L, 267502L,
9517623L, 16102411L, 26377567L, 8230310L, 13076594L, 26878082L,
415271L, 13833529L, 26823199L, 2410L, 26900200L), upload_id = c(851L,
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1746L, 669L, 2230L, 1506L, 2055L, 2314L, 1249L, 1757L, 2230L,
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The problem with these subsets is that I'm not sure how much overlap remains between the two of them for the join, but hopefully there will be some. I tried to filter() one to include upload_ids from the other, but I get an error saying:
Error in filter_impl(.data, quo) : Column
intervalclasses Period and Interval from lubridate are currently not supported.
Sorry this sounds complicated, please let me know if I can clarify this question further. I am truly grateful for your help!
回答1:
You can use the fuzzyjoin package:
library(BiocManager)
library(lubridate)
library(fuzzyjoin)
colnames(df2) <- c("sequence_id", "upload_id", "start")
df1$start <- int_start(df1$interval)
df1$end <- int_end(df1$interval)
df2$end <- df2$start
df3 <- interval_inner_join(df1, df2, by=c("start", "end")) # let 1 join with 2
来源：https://stackoverflow.com/questions/51412533/joining-data-frames-by-lubridate-date-within-intervals