I have grouped my data for each 5 minutes using dplyr package. date_chunk represents the grouping variable. I need to define lower and upper threshold of the grouping variable as separate variable. For example, in first group: lower threshold is 6:37:29 and upper threshold is 6:42:28. I am not intended to get maximum value of a group by sample. I have just added reproducible dataset with grouping variable. Your helping hand is highly appreciated.
Mac_address UNIX_T.x UTC_T.x Loc.x UNIX_T.y UTC_T.y Loc.y Link_1 TT T1 T2 date_chunk
6174ba6829753695bb111bfd3a1288d6 1492670249 4/20/2017 6:37 P2 1492670369 4/20/2017 6:39 P3 P2P3 120 1492670323 1492670323 4/20/2017 6:37
9ca4cf09f1caf2de82e3ec982892df7a 1492670253 4/20/2017 6:37 P2 1492674921 4/20/2017 7:55 P3 P2P3 4668 1492673132 1492673127 4/20/2017 6:37
2521a4d2e65100d0fe6c57f111e0109c 1492670258 4/20/2017 6:37 P2 1492671709 4/20/2017 7:01 P3 P2P3 1451 1492671153 1492671151 4/20/2017 6:37
2521a4d2e65100d0fe6c57f111e0109c 1492670290 4/20/2017 6:38 P2 1492671709 4/20/2017 7:01 P3 P2P3 1419 1492671165 1492671164 4/20/2017 6:37
a4f70f558c1f3479a36d62a8a22ab77f 1492670354 4/20/2017 6:39 P2 1492670614 4/20/2017 6:43 P3 P2P3 260 1492670514 1492670514 4/20/2017 6:37
2f15e55a9c3cd70349c1cc5b0d5db00c 1492670432 4/20/2017 6:40 P2 1492670584 4/20/2017 6:43 P3 P2P3 152 1492670526 1492670526 4/20/2017 6:37
35571d9eb84fc322e868ba0f42936a99 1492670489 4/20/2017 6:41 P2 1492670629 4/20/2017 6:43 P3 P2P3 140 1492670575 1492670575 4/20/2017 6:37
5ee52129ae79c183c194ede0b934aa53 1492670520 4/20/2017 6:42 P2 1492670651 4/20/2017 6:44 P3 P2P3 131 1492670601 1492670601 4/20/2017 6:37
2521a4d2e65100d0fe6c57f111e0109c 1492670557 4/20/2017 6:42 P2 1492671709 4/20/2017 7:01 P3 P2P3 1152 1492671268 1492671266 4/20/2017 6:42
e4297c1687b3fea3da2392564720c443 1492670564 4/20/2017 6:42 P2 1492691151 4/20/2017 12:25 P3 P2P3 20587 1492683263 1492683241 4/20/2017 6:42
c27b544af1552a77cd7a38b36923d037 1492670566 4/20/2017 6:42 P2 1492670707 4/20/2017 6:45 P3 P2P3 141 1492670653 1492670653 4/20/2017 6:42
4e68c4a8ff6a71e1fc4df59b587556a7 1492670595 4/20/2017 6:43 P2 1492670742 4/20/2017 6:45 P3 P2P3 147 1492670686 1492670686 4/20/2017 6:42
4bb0326fd40a4a159296cc20a5cc196c 1492670640 4/20/2017 6:44 P2 1492670772 4/20/2017 6:46 P3 P2P3 132 1492670721 1492670721 4/20/2017 6:42
badbb2a52973196ace7cb66c50aa39b2 1492670700 4/20/2017 6:45 P2 1492671974 4/20/2017 7:06 P3 P2P3 1274 1492671486 1492671485 4/20/2017 6:42
badbb2a52973196ace7cb66c50aa39b2 1492670761 4/20/2017 6:46 P2 1492671889 4/20/2017 7:04 P3 P2P3 1128 1492671457 1492671456 4/20/2017 6:42
badbb2a52973196ace7cb66c50aa39b2 1492670820 4/20/2017 6:47 P2 1492671880 4/20/2017 7:04 P3 P2P3 1060 1492671474 1492671473 4/20/2017 6:42
badbb2a52973196ace7cb66c50aa39b2 1492670849 4/20/2017 6:47 P2 1492671989 4/20/2017 7:06 P3 P2P3 1140 1492671552 1492671551 4/20/2017 6:47
badbb2a52973196ace7cb66c50aa39b2 1492670849 4/20/2017 6:47 P2 1492682285 4/20/2017 9:58 P3 P2P3 11436 1492677903 1492677891 4/20/2017 6:47
badbb2a52973196ace7cb66c50aa39b2 1492670849 4/20/2017 6:47 P2 1492671882 4/20/2017 7:04 P3 P2P3 1033 1492671486 1492671485 4/20/2017 6:47
badbb2a52973196ace7cb66c50aa39b2 1492670883 4/20/2017 6:48 P2 1492671872 4/20/2017 7:04 P3 P2P3 989 1492671493 1492671492 4/20/2017 6:47
badbb2a52973196ace7cb66c50aa39b2 1492670941 4/20/2017 6:49 P2 1492671872 4/20/2017 7:04 P3 P2P3 931 1492671515 1492671514 4/20/2017 6:47
badbb2a52973196ace7cb66c50aa39b2 1492671001 4/20/2017 6:50 P2 1492671889 4/20/2017 7:04 P3 P2P3 888 1492671549 1492671548 4/20/2017 6:47
badbb2a52973196ace7cb66c50aa39b2 1492671061 4/20/2017 6:51 P2 1492671880 4/20/2017 7:04 P3 P2P3 819 1492671566 1492671565 4/20/2017 6:47
badbb2a52973196ace7cb66c50aa39b2 1492671120 4/20/2017 6:52 P2 1492671979 4/20/2017 7:06 P3 P2P3 859 1492671650 1492671649 4/20/2017 6:47
badbb2a52973196ace7cb66c50aa39b2 1492671149 4/20/2017 6:52 P2 1492671989 4/20/2017 7:06 P3 P2P3 840 1492671667 1492671666 4/20/2017 6:52
badbb2a52973196ace7cb66c50aa39b2 1492671149 4/20/2017 6:52 P2 1492671991 4/20/2017 7:06 P3 P2P3 842 1492671668 1492671667 4/20/2017 6:52
badbb2a52973196ace7cb66c50aa39b2 1492671149 4/20/2017 6:52 P2 1492682285 4/20/2017 9:58 P3 P2P3 11136 1492678018 1492678006 4/20/2017 6:52
badbb2a52973196ace7cb66c50aa39b2 1492671182 4/20/2017 6:53 P2 1492671882 4/20/2017 7:04 P3 P2P3 700 1492671614 1492671613 4/20/2017 6:52
badbb2a52973196ace7cb66c50aa39b2 1492671240 4/20/2017 6:54 P2 1492671987 4/20/2017 7:06 P3 P2P3 747 1492671701 1492671700 4/20/2017 6:52
badbb2a52973196ace7cb66c50aa39b2 1492671306 4/20/2017 6:55 P2 1492671882 4/20/2017 7:04 P3 P2P3 576 1492671661 1492671661 4/20/2017 6:52
badbb2a52973196ace7cb66c50aa39b2 1492671361 4/20/2017 6:56 P2 1492671889 4/20/2017 7:04 P3 P2P3 528 1492671687 1492671686 4/20/2017 6:52
badbb2a52973196ace7cb66c50aa39b2 1492671450 4/20/2017 6:57 P2 1492671989 4/20/2017 7:06 P3 P2P3 539 1492671782 1492671782 4/20/2017 6:57
badbb2a52973196ace7cb66c50aa39b2 1492671450 4/20/2017 6:57 P2 1492682285 4/20/2017 9:58 P3 P2P3 10835 1492678133 1492678122 4/20/2017 6:57
badbb2a52973196ace7cb66c50aa39b2 1492671480 4/20/2017 6:58 P2 1492671884 4/20/2017 7:04 P3 P2P3 404 1492671729 1492671729 4/20/2017 6:57
badbb2a52973196ace7cb66c50aa39b2 1492671541 4/20/2017 6:59 P2 1492671889 4/20/2017 7:04 P3 P2P3 348 1492671756 1492671755 4/20/2017 6:57
badbb2a52973196ace7cb66c50aa39b2 1492671602 4/20/2017 7:00 P2 1492682285 4/20/2017 9:58 P3 P2P3 10683 1492678192 1492678180 4/20/2017 6:57
badbb2a52973196ace7cb66c50aa39b2 1492671662 4/20/2017 7:01 P2 1492671991 4/20/2017 7:06 P3 P2P3 329 1492671865 1492671865 4/20/2017 6:57
badbb2a52973196ace7cb66c50aa39b2 1492671722 4/20/2017 7:02 P2 1492671991 4/20/2017 7:06 P3 P2P3 269 1492671888 1492671888 4/20/2017 6:57