How to identify (not remove) SETS of data that are duplicated? Dplyr or other solution?

Question

so I have data about Sites, nested in Class. In each Site there is a Time (timepoint) variable. The data of interest is Count1, Total1, Count2, Total2.

I know there are whole duplicate sets within Class, across Sites for the values of Count1, Total1, Count2, Total2 for Time.

Here's what I mean - Let's say we have Class 1, with the first Site:

Class  Site           Time  Count1 Total1  Count2 Total2
1      a0QjvO281o1    1      8     64      4     34
1      a0QjvO281o1    2     16     64      8     34
1      a0QjvO281o1    3     16     64      8     34
1      a0QjvO281o1    4     16     64      8     34
1      a0QjvO281o1    6      8     64      4     34

And, I've noticed there are several other Sites with this EXACT pattern (or other repeated patterns).

Class  Site           Time  Count1 Total1  Count2 Total2
1      zlG1VmpE6QQ    1      8     64      4     34
1      zlG1VmpE6QQ    2     16     64      8     34
1      zlG1VmpE6QQ    3     16     64      8     34
1      zlG1VmpE6QQ    4     16     64      8     34
1      zlG1VmpE6QQ    6      8     64      4     34

I want to identify within Class how many Sites have the same pattern. Either marking them or reducing the data sets to the first unique site pattern, but I would like to be able to say how many Sites fit each found pattern.

So, here's the partial data:

    df <- 
structure(list(Class = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), Site = structure(c(3L, 
3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 9L, 9L, 
9L, 9L, 9L, 17L, 17L, 17L, 17L, 17L, 19L, 19L, 19L, 19L, 19L, 
30L, 30L, 30L, 30L, 30L, 49L, 49L, 49L, 49L, 49L, 54L, 54L, 54L, 
54L, 54L, 56L, 56L, 56L, 56L, 56L, 62L, 62L, 62L, 62L, 62L, 66L, 
66L, 66L, 66L, 66L, 86L, 86L, 86L, 86L, 86L, 88L, 88L, 88L, 88L, 
88L, 98L, 98L, 98L, 98L, 98L, 33L, 33L, 33L, 33L, 33L, 128L, 
128L, 128L, 128L, 128L, 141L, 141L, 141L, 141L, 141L, 153L, 153L, 
153L, 153L, 153L, 154L, 154L, 154L, 154L, 154L, 274L, 274L, 274L, 
274L, 274L, 291L, 291L, 291L, 291L, 291L, 306L, 306L, 306L, 306L, 
306L, 309L, 309L, 309L, 309L, 309L, 336L, 336L, 336L, 336L, 336L, 
342L, 342L, 342L, 342L, 342L, 396L, 396L, 396L, 396L, 396L, 413L, 
413L, 413L, 413L, 413L, 418L, 418L, 418L, 418L, 418L, 435L, 435L, 
435L, 435L, 435L, 451L), .Label = c("~", "A0e3A15Lh1d", "a0QjvO281o1", 
"A0R2gEqRbTv", "A4J3Jp6KNz2", "A757EHpLOya", "A8kkDgEvEZV", "ab5F7MfRxZW", 
"AcjfpLUXjwt", "admxsO3fTtq", "aEBm7REs6XS", "AEZgWxwdbd9", "AezXCsZxd2U", 
"AFjm1YmnfyO", "AFTwI0xBM6e", "aGw7PyLMEkl", "aHNXoYj7uNJ", "AibLRYCSE4P", 
"aitNX6Qxkon", "ajEqsuhE9fV", "aJFDh98Iahb", "AKG4BvCUVsF", "AMtGkXGugJb", 
"aNczAtKAJsv", "aoY0wrz6qBF", "aOz3ikxG7qM", "aPWuF0rDfuJ", "aQrGXlhzEJB", 
"ARu0wnYDkam", "As7tGowP84e", "AsqolR3dfgv", "atj39UeK8N9", "atmjKVCRnzw", 
"aUhP7zZ7LPU", "aUMEQzUKI0K", "AuP8NAgS7Th", "aUyy9i4fwhS", "AVFW2vlGxds", 
"awoAlwC06Go", "awxCmxmeea2", "AWYFb5fwcYb", "Ax2Q16uPW55", "AXO6R085bth", 
"Ay6W05BTgDV", "aZMeFIlkevS", "B08adcYOEl7", "b5MVFPi1inY", "B7fffQm5omx", 
"ba3kFfcKXNk", "bCK7hWM4bnK", "BDlYKSCaOIG", "BE3TZDysXuQ", "bErpy9bSZAV", 
"Beu6pmpSDJE", "BgfNJiJlDrF", "bGUeQEEpq7q", "bgWDDBsRLIL", "bHwo17fsILI", 
"bifefa8JnfN", "bIQ3gsw51RH", "bisxDvmwluW", "biy6fHoOcZp", "bK7yQP8LNkJ", 
"Bke0tWeJyBr", "bKMNhuIYaYW", "blkWvfFDVm6", "bnaDFC8EVAo", "BNDeQ6sJctI", 
"Bokks2ESodd", "BoKlS77F7Il", "BqLRDDu69ic", "bqoZAzbsajz", "BRlA0HkkMGM", 
"bT501IhkxV9", "BTliRZoJs4i", "bTTf1R7zgRn", "bTZAPQPXgI5", "BUtglXWCjkf", 
"BvcJEyVWsGG", "bVHpRZguCL2", "BVymUZcbCuf", "BwkVolONMBn", "bWtq9NnOoCU", 
"c2YR2oDyx7t", "c3dhvyZuPum", "c3LYcysugey", "c46Q9ExLocA", "C52gwcl9fmp", 
"c5IYnQ3M7dj", "c6yCKEAemfr", "C8uv1qapHmC", "Ca2rjTu7g6A", "cAsHVMiIVHT", 
"cB7mNM1MNm0", "Cbboq0XBHn1", "cbUfMWJl9sK", "ccixNtjWLkf", "ccL7Esacksn", 
"CgmvbI2pkyK", "cGvhZR5kDxQ", "chFA8wLA953", "cIb00kbYPgm", "cjoj6MxgfxE", 
"cJrxpXipqCm", "cMR1ECoHpE4", "CmRKRa25mZu", "cnCuI3VeJKt", "cNUlz8NllVu", 
"CoySgwRgeRE", "CpZyeEzz39h", "CqIH5ytvqTS", "cRbK3weaIO6", "cs2MtDT1y17", 
"CSVVXoe0xGC", "ctEZrxoEucg", "CxCDdfOd0Nj", "cXzO64qne5O", "CZq12nSSyn9", 
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"DhPZWGceA1Q", "DiKXevYOYNB", "DJIgnE1QQbB", "dkR7YOB6UT6", "dKy3aHycCap", 
"dl9g8UYxk20", "DLmEBtWqO9S", "DLza3NSQYUI", "dmUHnTHgfYg", "dnRXJOdEzdw", 
"doRK8OhG0kd", "DQaEryfraV6", "dQk8ubXxXLX", "dQOwWKXxFeq", "DrHlSXIHalR", 
"DrLeENdZwxX", "DRUaAOrybxb", "dSJcUkmJWvZ", "dSuHNzaRaSf", "dtDftsTowRA", 
"DVF2BNdSzV9", "DW7NajJs9ry", "dw94DZyrpUZ", "Dxa8RiDlXB6", "dXBB3LIqhd8", 
"dY1ATXbywBu", "DY3V0E6pUYD", "dYIdx3HoWbL", "DZMyvdZEDeB", "dZrjKdqCi1w", 
"e2cMNKCnHOw", "E2g3H9rUdML", "e59NHDOFTWC", "E6KoR8hXk7P", "E6vLBntf9QE", 
"E8PnLO9QRcE", "e9NQxtBNruk", "e9QjFd6fZ4I", "EAdX1JPb4Dm", "eCGBeD0uz0D", 
"ECHaJeidpTR", "edLdPyMjbaz", "EefeXxr8yDS", "ef6tzAcpMeF", "eFB6BfJ2BTY", 
"EjFYleP5G9K", "eLGdmsoRjWn", "ElmgbenqYn7", "EM5PauW0KWg", "EmhBF1JUw3i", 
"enR40fiMtoo", "EpxhEmcMVXh", "EQpPsVwWvqz", "EQtHhnAYjJp", "erfgs35WGXU", 
"eRNEYF9OfA8", "ERqjIjzKnNm", "EsdcJsyJTJG", "ESNgljw6VvC", "eSZjKIwHPYi", 
"etyPfIkrlrM", "Eu1JrO8bBkB", "euFWewBZ5Xr", "EVaNkH5nz1s", "eXgA6Zfn6KQ", 
"EXIi96SW1Bm", "eYPdhvwFirr", "eZ2NazTVbb6", "EzN8D82lOTp", "F03oK0VRgyk", 
"f0WCSs2fwvv", "F3CHKWYM2Pb", "f3FoF8cpKiH", "F42k81lXXMO", "F8ZvmoAy2bh", 
"fd5zuIbL3Qd", "fDN9KAuRv2o", "FdqK3U8rDRX", "fG2ws21A6Lj", "fgDQSAYp5pj", 
"FGjbxwib4q5", "FgLXwaIGGbn", "FiqXUXkRHXr", "fiuesJ8f3xw", "fJAqAOFzB2b", 
"fJmQ6P38mHh", "fJy2O3xh1fV", "FjZuMxKuYvb", "FKe5fQHbu8l", "FKuw35vjqRz", 
"FmAQ159jI3w", "FMGmKkEOmV4", "FmuzZuFFMzD", "FMX7RNQIwYu", "FNUYBvpbWaA", 
"fnzDrz05g0T", "FO80di9Jxuk", "FOKfyVchS21", "fP0XmUTTfks", "fpCA3TMnMA3", 
"FPkj0JvlmyK", "FPSoejJAWSU", "FqkwtkM7eXB", "FqlQZiGKxpr", "FThJa71HEEs", 
"FVaQ3fSHtT5", "FvQrsd2gVeu", "fx7bCRgdYic", "FxrH3E1ge0f", "fYtsyMj84LY", 
"G0EID1cpxEB", "g4jJZ1SNP4I", "g7AYmMzlRL5", "G7hnxrBDXd2", "GCQVHCnV25O", 
"GcYMteoIkw9", "GDCM1IWa7Zh", "gdsUTJnwdzb", "Ge7oZ5R4iBk", "gEff10Pq35y", 
"GFPi9bpW3sN", "ggMEnqgD9kD", "gKR0a28tTp5", "gKRGyOXbpzj", "glEuzcZNWIM", 
"GlWdTuycHxs", "glyDmwEFzrr", "gmmjFqs7MFB", "GMWgNQ8JB1r", "gqFwQOY1wSE", 
"gqNh2d7WJva", "grKa7EwswRX", "gsIY3JD3iHh", "GSWPAgMxhy2", "gsX0auFXP9m", 
"Gtef53Qyxrj", "GTQqEhUUV1F", "guGv3PY445Z", "gUve5bZAut8", "gVZ58EQOH6K", 
"GwXv8OX78AT", "GXIQmznIdQe", "GxIVLRDNmVF", "GziA2Vc0HX4", "h0RMK448nhs", 
"H0vjaO76Wg8", "H1G7wWYemSm", "H3mOm6sbODE", "h4IQGhyYAQp", "H6LR8zRVQLW", 
"hAoSAyLR3I6", "HB6ZBS6kyJ8", "HcKIEHFgpDb", "hCuRPOStRLU", "HdTW2XJg3IO", 
"HdxFUpXFp2O", "hFwwNnFm1B8", "hHMHykeQBua", "HI3Z2eSmWYl", "hiRGzSqrLx5", 
"hjeei4JLTiF", "HjwC2LDSWHK", "HlElMRh1t6W", "hlIZJlEsd7B", "hLwLFwQgUdb", 
"HmIC1eI4aEQ", "HmuBn2Tdutx", "HN6AdgqShbf", "hoSu28MRYPv", "hq6x4qBOYsg", 
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"HU4RdTNlezp", "hWWRAoV26mI", "HXA0U1WlIhx", "hxckGietsww", "Hy4Uo9AjrnA", 
"hy52ywnDIAM", "Hy5stTfQzCG", "HZd0k5dqZ9h", "hZV0CekLNni", "i0rzEGmhViY", 
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"P91Rf8wCj7Z", "p9J64kFu5Fd", "PDOfJJdpbob", "pdRTIO2JqPL", "PDWC7RxX4t9", 
"pEAFBcOJIVF", "PEfq6d3TONP", "PeNS8yHqYH1", "pEvaEn24SR1", "pg9F69FU9fh", 
"Pi6v7zcA26e", "PibIwh4xKHI", "PicYz4ZaEkF", "PIm96jtkVB5", "pIVjHCsQgJI", 
"PJI3sARzQAG", "PK027w8aZ5K", "PKfz9RYfKzF", "pl8h1HdqpFW", "pl9IGnhmOJc", 
"PlISiBPN3db", "pMiRPEvyleJ", "pMtEAU5iVTB", "PnB0GLiMdBm", "PPb3XMcCAf3", 
"PSdLvfFlDRF", "pthlRKVLgNp", "PTZfXfOkUR1", "pWmPB9No5RJ", "PWXwPbUM2DB", 
"pxPQCkuJZrl", "PxXh1I86blw", "Pz198xRjRHD", "q2UUKkPtvll", "q4hyZcb2pgA", 
"q6ke2WlwbWr", "Q75pcfnDLwr", "Q86baYhZPOB", "q8fmqtJVDhh", "qBrBhSbFC0d", 
"qc9eMgI8Y95", "QCY2lUMpt7f", "QDkCAOGVng6", "QdYKp8ivavV", "qeBFicifeNz", 
"QeKGz2D6wNe", "qEt7nmwua6v", "QGJz6Rv3qHU", "Qgzh7S5pLc3", "qHaaYvuNGIB", 
"qiBueINJbti", "qimfq5GL5mV", "qJsVouyMqE8", "qlnxDl1BOrw", "Qlt1DOyb7iP", 
"qm0fcx7VGOQ", "QMT77ObrHQa", "QOyCdSRSUXL", "Qpj3LVa0kMf", "qQ84fCTxdGh", 
"QRaKmOedEZx", "qs9EipoiiBD", "qsPQEZph59z", "QTFJClMfP8c", "QtJyTjN5faU", 
"qU7z54bY9jA", "QvByLV2hsHo", "QVFUUfes7vc", "QvQ5bpVOJDj", "Qwzbgh4Flmx", 
"qx2DdF2CKFL", "qXdueHJNqcv", "QxSfgx5QfT7", "qxuRrLWQmXL", "Qztk8cjmz1e", 
"r0ehsy1jjxa", "r2w7bZu3FsL", "R3ac44RpwRG", "r4mXVpHUWC7", "r6p12UeHOyg", 
"r9efDheFtk3", "rakWSnvNhWr", "rbBZoYFr4DM", "rBtlT7YCRKx", "RdbYAXOnm2S", 
"RdM4hjZsFRg", "Re2M8SlCc98", "RfmkqgjDUPL", "rgAmPaAHmNU", "rGbQXTyOdmW", 
"RHpQbDCZK5O", "rhxxSbYXZRR", "RiIZqF2hfqY", "rIR8cwAz0sf", "rJ3tipUjVQ4", 
"rlAmYWNUTnR", "rLiYzJJRiBA", "rLOyzoOdZqC", "RMKAo2HcVkM", "rnGH1Q5IyIU", 
"robJRJuEFfM", "RovRnV9RWFd", "rpmWXDmHjsq", "rPPdTvv1QoY", "RqLdtXwHdGO", 
"rR1aDWav3z1", "RrjHJQJDQSr", "rrZEwHEjjy8", "rsM3sdDc3Lk", "RsmDQZSmpD7", 
"RtK3aS9WP2H", "ru8BHTnYxI3", "RU8DlKBg48x", "rUysfjKrKqk", "Rv3o89GkqWH", 
"rVC8KePJHu3", "RvCLp5qbvtz", "RvQqAbOcEfA", "RW617O0UjQJ", "RWvmueaioAl", 
"RxADuUq1Ba1", "RxHTSbz8VN5", "RxND5KsxzvW", "RyRJf2UHJL1", "S1Rh4YnCAAZ", 
"s28njgt1wYe", "s4eb8Spa5TC", "S6gaiIWGmh9", "S6X4d5WHA1H", "sAnH4cWV41G", 
"SATZgjyfpdZ", "sAyk7hwXEbV", "sBu9GwU5IKe", "SdlDgZMNxqX", "SegMIAP4dhw", 
"SfB5NwJXaot", "SfPGp94cYZa", "SG0QMcMgRRq", "sG2EfH7UYLQ", "SgK14sd0Fq1", 
"sgNOxONNZIv", "sGXcrRdwzAk", "shkTq2LdpXw", "si6qmHhCV9F", "skR6XpFhu3u", 
"skuXY545bae", "skVM9VC2v6H", "sLkylFDaonQ", "sLQ3GDMCRSz", "sMVuTESYbpd", 
"soMCF3RbHqt", "sQhxc449PV4", "sRbFOoSk7qZ", "srTptJGYtcK", "SSS1hmwqHOR", 
"StSjQheznIv", "SvLVieXqQT7", "SVR6pSBhbCb", "sWlH85siDIT", "SWTCBn32M8D", 
"sYBdL54a73r", "t0V5NCdjdPi", "T15MpYA7f51", "t3snPDHuVBW", "T5LdflE3Peq", 
"T6RUeMH9KP0", "T6VbSgxjG4o", "t9Fl7c8SJbm", "TafeAKXESCA", "TBMPJiR0PKA", 
"tcjz9dmJW4y", "tDDh1EjIZkh", "TE62MxBLgne", "TE7dhvcKVwp", "tEiDKptkacd", 
"tEr481bYdow", "tfEtbnUgkGv", "TgpNd1eUCH5", "tGV21Z1HgXN", "thQZhxRh887", 
"TJp862VOKlS", "TK7P7QXIDOA", "TKb3FP8mXY0", "TL5cvVAN3cA", "TM31sX4CThP", 
"tMpwPcDzIfU", "tNf8m963xKK", "tnR9XvFJ5d7", "tNu7AdZ5358", "tOEYJ1EgIkn", 
"TqSXqCuyodR", "tRgUTgCKu4J", "troIuBzxemz", "TSQWaAvOer5", "TsSlV9eE7Mz", 
"ttKnsfno2BN", "tvoTu4cpYbh", "TWJPFfCeHES", "twyDPmlDNjH", "TyjDUvHkCAx", 
"TYYPCGssY7i", "tz00ETYw78Y", "TZ307ap3HvE", "TzPwGs1AcCL", "TZxEGcWjbdk", 
"u0ezFwC4OLL", "U3DjjRVyEun", "u45lZujojLF", "U6Mo4GsQKwT", "U7jt55boMwC", 
"U8feQBluEhj", "UBe2SLdSmxV", "uBjjsyieqtr", "UccWk7OAtZ2", "uDXFpf8Ko6P", 
"uE4KejhmDyk", "uGfkThgxZsI", "Uih0KGtvZeo", "UIyI4hkq7Bx", "UjoXPWJKPXb", 
"uKFFT93nPmp", "UKSoohp2vBC", "UL70316n0C2", "UlD5QNXAW40", "uLDFnAy4ro0", 
"UNxoCz1KXnW", "uOmh6keHjf6", "uormVxMEerw", "Upe0kYdbeUy", "UPSbASHNQmU", 
"UQ1K5VqXqcZ", "uQvg5rWo87I", "usFB6MgBB6t", "uTeZmtXQzSN", "utgv86YyClH", 
"UTmdWR44H5x", "uUmAJIXkmsO", "UUsAfkqIPhV", "Uv6Baj6YaG1", "UV9ZR51T6Ts", 
"UvVxiC7b1jZ", "UW4ZNlm05Jq", "UxEq7311Xzd", "UXhcOzwv9o5", "UXSSmcXoWR8", 
"v15yxuZyGjR", "V1MbBFGqwbB", "V5LD5oYeZys", "v6BprVsEEt2", "V7Hl62C5Wgz", 
"Vah8YYh5HI5", "vbDOTEMQjfW", "vBjsjEqsmWL", "vBym1l507tA", "vf1kkxsjkB1", 
"vFSbE4W5Kg6", "VfZPt9kXxL9", "vGLQ19KWuBv", "VHK1T5sygmw", "VLuN2iZ9oZp", 
"VmwVU8HFDBn", "vnaUuR9C4FH", "vniKeY4S1Ru", "vOu023c0Snx", "vOuGO9bkEUa", 
"vrQvRBzXiLv", "vRRoviRJVgX", "VS1mxlo1mVx", "VsFXXXagVmp", "VSHfWQyhzUu", 
"vugElbQMtcL", "vvaX4oKLyKo", "vw87QIZ7dhk", "VWLVmvtDCSI", "vxXQe9jxSPE", 
"vy0hyVTrTom", "Vy1JFQbsNBB", "vzGc2nPWraO", "vzVRv2jtJxL", "w0aCC4wNNzW", 
"W1wtZLbWuY0", "w2yXiR4CyWt", "w539HzekPQh", "w55gRgLikEN", "WBhss2tvLa8", 
"WcPEy9epMgd", "WCSGolF5yhy", "wdcS5ORWZte", "WDyq0ryAjpn", "webeuXrveDi", 
"WeSJR8GDPmC", "WFApCUf18Lp", "wfFCmvMEGOQ", "WFiPvuGJf9O", "WggRnJplCQI", 
"wgqFTVU7Iky", "wIMmZwl1gpX", "WjCGPzMzLVr", "WJfiDULf7ZC", "wkl1yyAzga3", 
"wlspYUyDoQM", "wm060hpEM7g", "wMPB6u0GZDL", "Wn07Tbv74qp", "wNha3idA7l6", 
"WnZVpXq5XCO", "wOe4JHkqbUm", "Wog7gclb7TJ", "wq4bmXnJK45", "Wq4O1nlYk1C", 
"wqUwUpMD2mJ", "wrGYa8E94Yc", "WSAfRmiEJOF", "wSP90pEfCng", "wSW662GVwZP", 
"wtoXU3G9YIy", "WtPSqPwjH2f", "wtV2TtEPCCZ", "Wtw2jbyaHz2", "WUChzooYWJ1", 
"WUFgPdTN02g", "wUQiuRjZxiO", "Ww9Rq2KLlqV", "WWabB2sc4B7", "wxKEHpSLvib", 
"wXnoTA2MDy9", "WYk4A1fVYD7", "WYMXHupBG7P", "wzD83xmvR3b", "WzemydwRD0R", 
"X4ZVDdDd2xa", "X6efCWparbb", "X6uv3PName4", "X7deWPhTiIy", "X8TsrtMQFiu", 
"X8UmaBiq1yy", "xbJCVaOZWp5", "XbjRzgMPN24", "XbubJh2yjOw", "XcqBCAaLcq5", 
"xd8LIlN7N8h", "XdKVljaiZ9j", "xeEUMp35d5m", "XeUDpg1CTKf", "xf9Q4yYDlq5", 
"XFEHZnnEGkT", "xFO9GKAXi1n", "xfxtwRZ7Ejp", "xhOpIbHQy8I", "XjBkSXvZLOZ", 
"xjfIPJ04cET", "XLt8l1uPicg", "xlYle4v5GZ8", "xmJNiAbmSfe", "XnkRi1jTMKr", 
"XPhxWI0fDyq", "XqDQsrhQ7W5", "Xsd3yzbnFOf", "XTF6vymtG8J", "xuovzIjWZUG", 
"Xv1I8z1cK76", "XvVmyn071HT", "XxBMueAFsnk", "xxVZKlzMYJJ", "xyr4dO4G3tW", 
"y4rr2PbfufS", "yaa2uBLsdRa", "YBG39jGSV17", "yDcnCB4aZEX", "YDuoFIKpONe", 
"YdWxRCaQR2D", "yfgSogitBGX", "YFi06xiFHWs", "YFi2V7qfmJf", "yfpM2zJ3Zuc", 
"ygTl7hih5qi", "YGtrgJxKWiU", "yIcfnuZhejK", "YIxt0WtezdT", "yJ014QFEqru", 
"yJO8QTnBF3o", "yKfdWuLsdDx", "ylMgcLnwgce", "YNy9ymD2A8p", "yONz8gph9A7", 
"YowwYq8CIXJ", "YPsxC0bl7T2", "YQP6diqjJAl", "YqR6LoSk2Ed", "yqwh11CvYXU", 
"YRemZ3p9bFA", "ySxRSgTOeqD", "yTvx2IJ0w0z", "ytwga9hKjVj", "YtyO06HBaVr", 
"YvEkkZlNeCK", "yVFdJkYsLK5", "yvoQHXHGvbT", "YVT9zsaVBzp", "YWbmL6VK8R6", 
"Ywm8eA9tZHe", "yXady1QV27H", "yY7MHufA6C9", "yYG52aLO1GK", "yYgG4h097xR", 
"YyhPAO5yx22", "Yz5yhyHf7Ul", "z2cGjpx37Mw", "Z42m6cWsI9m", "z4DptoHrJnb", 
"z4kLOdnL1Op", "z5tZes2s49Z", "z5WklS85YjT", "z6bId6qlNk4", "Z6ZZLw50mAM", 
"z8MwD6T43n2", "z8UkGdr2xNs", "Z90jET09ZrD", "zaeb1Zos2Mu", "ZBkpY2KdibX", 
"Zc0BcScQDBU", "zCjn57zZQVN", "ZcrdEBruDka", "ZCT4YbaBFUb", "ZdVIx83rdI7", 
"zEQXA689E4a", "ZfjQmCjVKRF", "zfutn6ulVcO", "zFzYdXMnPoP", "zG4JqtM8wHO", 
"ZGyAErBl5PS", "ZifoCg4OvIj", "ZJ6MAab9PJE", "ZKVzRmYkKzQ", "zlG1VmpE6QQ", 
"zN6xXPgmzqK", "zOfDRrZmbQO", "zOGa9wLHDFE", "zQmuipEUYbz", "zR7UekDUG3X", 
"zrs6iFpEtF1", "ZrUjQFzR1gM", "zTnxsAMqHRP", "Zu7gpmcwfqY", "zvOkAI9ewwE", 
"zvv07VAowTS", "ZWAdop7zYgJ", "ZWAEE8DrywN", "zxIlF5RwQFi", "ZXONCt7P01p"
), class = "factor"), Time = c(1L, 2L, 3L, 4L, 6L, 1L, 2L, 3L, 
4L, 6L, 1L, 2L, 3L, 4L, 6L, 1L, 2L, 3L, 4L, 6L, 1L, 2L, 3L, 4L, 
6L, 1L, 2L, 3L, 4L, 6L, 1L, 2L, 3L, 4L, 6L, 1L, 2L, 3L, 4L, 6L, 
1L, 2L, 3L, 4L, 6L, 1L, 2L, 3L, 4L, 6L, 1L, 2L, 3L, 4L, 6L, 1L, 
2L, 3L, 4L, 6L, 1L, 2L, 3L, 4L, 6L, 1L, 2L, 3L, 4L, 6L, 1L, 2L, 
3L, 4L, 6L, 1L, 2L, 3L, 4L, 6L, 1L, 2L, 3L, 4L, 6L, 1L, 2L, 3L, 
4L, 6L, 1L, 2L, 3L, 4L, 6L, 1L, 2L, 3L, 4L, 6L, 1L, 2L, 3L, 4L, 
6L, 1L, 2L, 3L, 4L, 6L, 1L, 2L, 3L, 4L, 6L, 1L, 2L, 3L, 4L, 6L, 
1L, 2L, 3L, 4L, 6L, 1L, 2L, 3L, 4L, 6L, 1L, 2L, 3L, 4L, 6L, 1L, 
2L, 3L, 4L, 6L, 1L, 2L, 3L, 4L, 6L, 1L, 2L, 3L, 4L, 6L, 1L), 
    Count1 = c(8L, 16L, 16L, 16L, 8L, 12L, 24L, 24L, 24L, 12L, 
    8L, 16L, 16L, 16L, 8L, 8L, 16L, 16L, 16L, 8L, 8L, 16L, 16L, 
    16L, 8L, 8L, 16L, 16L, 16L, 8L, 8L, 16L, 16L, 16L, 8L, 12L, 
    24L, 24L, 24L, 12L, 8L, 16L, 16L, 16L, 8L, 8L, 16L, 16L, 
    16L, 8L, 12L, 24L, 24L, 24L, 12L, 8L, 16L, 16L, 16L, 8L, 
    12L, 24L, 24L, 24L, 12L, 8L, 16L, 16L, 16L, 8L, 8L, 16L, 
    16L, 16L, 8L, 8L, 16L, 16L, 16L, 8L, 8L, 16L, 16L, 16L, 8L, 
    8L, 16L, 16L, 16L, 8L, 8L, 16L, 16L, 16L, 8L, 8L, 16L, 16L, 
    16L, 8L, 8L, 16L, 16L, 16L, 8L, 8L, 16L, 16L, 16L, 8L, 8L, 
    16L, 16L, 16L, 8L, 8L, 16L, 16L, 16L, 8L, 8L, 16L, 16L, 16L, 
    8L, 8L, 16L, 16L, 16L, 8L, 8L, 16L, 16L, 16L, 8L, 8L, 16L, 
    16L, 16L, 8L, 8L, 16L, 16L, 16L, 8L, 8L, 16L, 16L, 16L, 8L, 
    8L), Total1 = c(64L, 64L, 64L, 64L, 64L, 96L, 96L, 96L, 96L, 
    96L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 
    64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 
    64L, 64L, 96L, 96L, 96L, 96L, 96L, 64L, 64L, 64L, 64L, 64L, 
    64L, 64L, 64L, 64L, 64L, 96L, 96L, 96L, 96L, 96L, 64L, 64L, 
    64L, 64L, 64L, 96L, 96L, 96L, 96L, 96L, 64L, 64L, 64L, 64L, 
    64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 
    64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 
    64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 
    64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 
    64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 
    64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 
    64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L), Count2 = c(4L, 
    8L, 8L, 8L, 4L, 4L, 8L, 8L, 8L, 4L, 3L, 7L, 8L, 8L, 4L, 4L, 
    8L, 8L, 8L, 4L, 3L, 8L, 8L, 8L, 4L, 3L, 7L, 8L, 8L, 4L, 2L, 
    4L, 4L, 4L, 2L, 3L, 5L, 8L, 8L, 4L, 4L, 8L, 8L, 8L, 4L, 4L, 
    8L, 8L, 8L, 4L, 4L, 8L, 8L, 8L, 4L, 3L, 6L, 8L, 8L, 4L, 4L, 
    8L, 8L, 8L, 4L, 3L, 4L, 6L, 6L, 2L, 2L, 4L, 4L, 4L, 2L, 4L, 
    8L, 8L, 8L, 4L, 4L, 8L, 8L, 8L, 4L, 4L, 8L, 8L, 8L, 4L, 4L, 
    8L, 8L, 8L, 4L, 4L, 8L, 8L, 8L, 4L, 4L, 8L, 8L, 8L, 4L, 4L, 
    8L, 8L, 8L, 4L, 4L, 8L, 8L, 8L, 4L, 4L, 8L, 8L, 8L, 4L, 4L, 
    8L, 8L, 8L, 4L, 3L, 8L, 8L, 8L, 4L, 4L, 8L, 8L, 8L, 4L, 3L, 
    8L, 8L, 8L, 4L, 3L, 5L, 7L, 8L, 3L, 4L, 8L, 8L, 8L, 4L, 4L
    ), Total2 = c(34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 
    34L, 32L, 32L, 32L, 32L, 32L, 34L, 34L, 34L, 34L, 34L, 33L, 
    33L, 33L, 33L, 33L, 32L, 32L, 32L, 32L, 32L, 16L, 16L, 16L, 
    16L, 16L, 30L, 30L, 30L, 30L, 30L, 34L, 34L, 34L, 34L, 34L, 
    34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 31L, 31L, 
    31L, 31L, 31L, 34L, 34L, 34L, 34L, 34L, 22L, 22L, 22L, 22L, 
    22L, 16L, 16L, 16L, 16L, 16L, 34L, 34L, 34L, 34L, 34L, 34L, 
    34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 
    34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 
    34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 
    34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 33L, 33L, 33L, 33L, 
    33L, 34L, 34L, 34L, 34L, 34L, 33L, 33L, 33L, 33L, 33L, 28L, 
    28L, 28L, 28L, 28L, 34L, 34L, 34L, 34L, 34L, 34L)), row.names = c(1L, 
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 
16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 
29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 
42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 
55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L, 63L, 64L, 65L, 66L, 67L, 
68L, 69L, 70L, 71L, 72L, 73L, 74L, 75L, 1041L, 1042L, 1043L, 
1044L, 1045L, 1046L, 1047L, 1048L, 1049L, 1050L, 1051L, 1052L, 
1053L, 1054L, 1055L, 1056L, 1057L, 1058L, 1059L, 1060L, 1061L, 
1062L, 1063L, 1064L, 1065L, 1066L, 1067L, 1068L, 1069L, 1070L, 
1071L, 1072L, 1073L, 1074L, 1075L, 1076L, 1077L, 1078L, 1079L, 
1080L, 1081L, 1082L, 1083L, 1084L, 1085L, 1086L, 1087L, 1088L, 
1089L, 1090L, 1091L, 1092L, 1093L, 1094L, 1095L, 1096L, 1097L, 
1098L, 1099L, 1100L, 1101L, 1102L, 1103L, 1104L, 1105L, 1106L, 
1107L, 1108L, 1109L, 1110L, 1111L, 1112L, 1113L, 1114L, 1115L, 
1116L), class = "data.frame")

akrun · Accepted Answer

An option is to group by 'Class', 'Site', paste (str_c) the columns except 'Time' to a single string, then grouped by 'Class', 'Count1', ..., 'Total2', columns, get the group indices to create the 'ind' column and do a left_join with original dataset

library(dplyr)
library(stringr)
df %>%
    group_by(Class, Site) %>%
    summarise_at(vars(-Time), str_c, collapse="") %>% 
    group_by(Class, Count1, Total1, Count2, Total2) %>% 
    mutate(ind = group_indices()) %>%
    ungroup %>% 
    select(Class, Site, ind) %>%
    left_join(df)

Or a similar logic with data.table

library(data.table)
setDT(df)[df[, lapply(.SD, paste, collapse=""),
   .(Class, Site), .SDcols = patterns('Count|Total')][, 
     ind := .GRP, by = c('Class', 'Count1', 'Total1', 'Count2', 'Total2')
           ][, .(Class, Site, ind)], on = .(Class, Site)]

How to identify (not remove) SETS of data that are duplicated? Dplyr or other solution?

Answers (1)

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