Hi Everyone,
I hope I did this correctly (I called my data frame ao) and Thank you very
much for the info about using dput(), I'm starting to understand all the
different things that can be done in R and I appreciate all the advice. I
must appologize in advance since my coding is quite long but hopefully it
makes sense. and there is a efficient way to do this.
structure(list(num = 1:99, FORM_CHK = c(20870L, 22018L, 30737L,
22010L, 22028L, 36059L, 36063L, 36066L, 30587L, 30612L, 36056L,
30376L, 35153L, 30435L, 30536L, 30486L, 30475L, 36053L, 36048L,
36076L, 36045L, 36065L, 35772L, 36949L, 35702L, 36894L, 36080L,
35542L, 35457L, 35533L, 36042L, 36925L, 36827L, 36008L, 35817L,
36350L, 35985L, 35973L, 35801L, 36639L, 35810L, 35812L, 35807L,
36351L, 35967L, 35944L, 37006L, 36345L, 36062L, 36077L, 35802L,
35984L, 36043L, 35769L, 36360L, 36082L, 36071L, 36354L, 35771L,
35754L, 36295L, 35746L, 36064L, 35779L, 35751L, 35752L, 35785L,
35792L, 37011L, 36003L, 36040L, 36831L, 36031L, 36652L, 36992L,
36965L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA), RingNummerMan = structure(c(1L,
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L,
16L, 17L, 19L, 22L, 23L, 24L, 25L, 26L, 27L, 29L, 30L, 31L, 34L,
35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 46L, 47L, 48L,
49L, 50L, 51L, 52L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L, 63L,
65L, 67L, 69L, 70L, 73L, 74L, 75L, 76L, 78L, 79L, 80L, 81L, 82L,
83L, 85L, 86L, 87L, 88L, 89L, 93L, 96L, 97L, 18L, 20L, 21L, 28L,
32L, 33L, 45L, 53L, 62L, 64L, 66L, 68L, 71L, 72L, 77L, 84L, 90L,
91L, 92L, 94L, 95L, 98L, 99L), .Label = c("AJ...75425", "AL...62371",
"AR...11060", "AR...29297", "AR...29307", "AR...29502", "AR...29504",
"AR...29507", "AR...30039", "AR...30085", "AR...30165", "AR...30491",
"AR...30563", "AR...30616", "AR...30652", "AR...30687", "AR...30701",
"AR...30927", "AR...30959", "AR...30963", "AR...30964", "AR...30965",
"AR...30966", "AR...30985", "AR...30988", "AR...40917", "AR...40996",
"AR...45735", "AR...45904", "AR...45928", "AR...47609", "AR...65387",
"AR...65479", "AR...65550", "AR...65629", "AR...65948", "AR...86074",
"AR...86521", "AR...86527", "AR...90061", "AR...90064", "AR...90067",
"AR...90077", "AR...90081", "AR...90098", "AR...90101", "AR...90106",
"AR...90112", "AR...90133", "AR...90155", "AR...90176", "AR...90178",
"AR...90180", "AR...90187", "AR...90212", "AR...90247", "AR...90252",
"AR...90256", "AR...90258", "AR...90269", "AR...90272", "AR...90275",
"AR...90294", "AR...90298", "AR...90300", "AR...90337", "AR...90338",
"AR...90367", "AR...90397", "AR...90410", "AR...90463", "AR...90520",
"AR...90544", "AR...90556", "AR...90678", "AR...90712", "AR...90737",
"AR...90744", "AR...90829", "AR...90862", "AR...90863", "AR...90873",
"AR...90880", "AR...90892", "AR...90898", "AR...90945", "AR...90951",
"AR...90965", "AR...90970", "AR...90972", "AU...15008", "AU...15009",
"AU...15027", "AU...15032", "AU...15036", "AU...15038", "AU...15046",
"AU...15049", "AU...15505"), class = "factor"), year_score_taken = c(2006L,
2008L, 2009L, 2008L, 2008L, 2011L, 2011L, 2011L, 2009L, 2009L,
2011L, 2009L, 2010L, 2009L, 2009L, 2009L, 2009L, 2011L, 2011L,
2011L, 2011L, 2011L, 2011L, 2012L, 2011L, 2012L, 2011L, 2010L,
2010L, 2010L, 2011L, 2012L, 2012L, 2011L, 2011L, 2012L, 2011L,
2011L, 2011L, 2012L, 2011L, 2011L, 2011L, 2012L, 2011L, 2011L,
2013L, 2012L, 2011L, 2011L, 2011L, 2011L, 2011L, 2011L, 2012L,
2012L, 2011L, 2012L, 2011L, 2011L, 2011L, 2011L, 2011L, 2011L,
2011L, 2011L, 2011L, 2011L, 2013L, 2011L, 2011L, 2012L, 2011L,
2012L, 2012L, 2012L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), COR_LOC = c(15.13404,
13.88054, 30.0969, 19.09152, 16.88054, 14.15718, 39.15718, 16.15718,
16.13566, 23.07538, 39.15718, 24.56838, 12.13942, 21.4123, 19.06945,
12.33264, 32.48872, 30.15718, 37.15718, 37.15718, 49.15718, 22.15718,
18.50272, 23.69432, 24.9322, 47.29712, 41.15718, 21.47903, 38.6588,
34.99572, 28.15718, 13.08614, 16.71908, 22.68894, 19.2616, 15.96234,
22.83964, 13.89992, 14.2616, 18.17118, 24.2616, 22.2616, 13.2616,
23.96234, 24.89992, 24.05062, 10.20884, 6.96234, 13.15718, 17.15718,
40.2616, 21.83964, 20.15718, 39.50272, 26.81164, 20.3843, 14.15718,
7.96234, 19.50272, 40.74384, 5.7675, 42.95482, 29.15718, 18.32188,
28.74384, 37.74384, 22.32188, 25.32188, 18.20884, 14.68894, 22.15718,
39.71908, 18.2067, 15.1109, 15.61466, 47.4532, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA), IndividuID = c(11394L, 15676L, 342518L, 344902L,
344909L, 377497L, 377499L, 377504L, 352003L, 351986L, 352260L,
352392L, 353800L, 353892L, 353949L, 354060L, 354074L, 377487L,
377490L, 377511L, 377513L, 377495L, 377297L, 357796L, 366326L,
378446L, 377518L, 358157L, 358730L, 366215L, 377519L, 378407L,
378453L, 377443L, 377358L, 377726L, 377422L, 377402L, 377341L,
378354L, 377350L, 377352L, 377347L, 378408L, 377396L, 377374L,
377774L, 377743L, 377500L, 377510L, 377342L, 377421L, 377786L,
377294L, 377836L, 378291L, 377508L, 378199L, 377296L, 377280L,
373000L, 373020L, 377496L, 377306L, 373025L, 377278L, 377310L,
377317L, 377337L, 377439L, 377450L, 377464L, 377478L, 400290L,
400361L, 400260L, 357889L, 377477L, 377298L, 400370L, 356930L,
356939L, 378115L, 377562L, 378018L, 377834L, 378290L, 378228L,
378268L, 378052L, 378103L, 377332L, 377514L, 400356L, 400357L,
400372L, 400259L, 400256L, 400354L), BroedJaar = c(2012L, 2012L,
2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L,
2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L,
2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L,
2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L,
2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L,
2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L,
2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L,
2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L,
2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L,
2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L,
2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L), ManipulatieOuders = c(0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L), LegBeginDag = c(11L, 15L, 15L, 13L, 8L, 26L, 15L, 16L,
1L, 3L, 4L, 9L, 13L, 20L, 11L, 2L, 9L, 13L, 31L, 1L, 12L, 8L,
13L, 7L, 10L, 11L, 17L, 10L, 11L, 19L, 20L, 13L, 14L, 24L, 17L,
10L, 8L, 29L, 7L, 26L, 10L, 15L, 2L, 6L, 8L, 13L, 1L, 5L, 12L,
12L, 15L, 19L, 10L, 1L, 5L, 13L, 6L, 5L, 16L, 2L, 2L, 30L, 10L,
21L, 8L, 19L, 8L, 27L, 3L, 8L, 14L, 18L, 17L, 7L, 4L, 10L, 13L,
11L, 31L, 25L, 23L, 7L, 7L, 7L, 8L, 3L, 14L, 14L, 15L, 5L, 10L,
11L, 18L, 1L, 31L, 3L, 8L, 20L, 14L), LegBeginMaand = c(4L, 4L,
5L, 4L, 5L, 4L, 4L, 4L, 4L, 5L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
3L, 4L, 4L, 4L, 5L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 3L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 4L, 4L, 4L,
4L), broodinfo = c(55334L, 55325L, 55317L, 55349L, 55366L, 55303L,
55461L, 55528L, 55296L, 55297L, 55630L, 55567L, 55345L, 55444L,
55526L, 55571L, 55462L, 55346L, 55576L, 55577L, 55601L, 55300L,
55607L, 55634L, 55558L, 55633L, 55590L, 55594L, 55537L, 55466L,
55327L, 55603L, 55600L, 55302L, 55319L, 55609L, 55574L, 55310L,
55554L, 55582L, 55561L, 55320L, 55555L, 55578L, 55343L, 55331L,
55314L, 55560L, 55460L, 55551L, 55322L, 55306L, 55348L, 55589L,
55572L, 55565L, 55595L, 55606L, 55323L, 55635L, 55568L, 55614L,
55447L, 55312L, 55344L, 55321L, 55569L, 55309L, 55570L, 55562L,
55550L, 55605L, 55465L, 55445L, 55587L, 55332L, 55629L, 55613L,
55448L, 55632L, 55636L, 55531L, 55329L, 55597L, 55298L, 55596L,
55318L, 55608L, 55463L, 55532L, 55557L, 55536L, 55333L, 55533L,
55538L, 55637L, 55330L, 55326L, 55525L), BroedselID = c(55334L,
55325L, 55317L, 55349L, 55366L, 55303L, 55461L, 55528L, 55296L,
55297L, 55630L, 55567L, 55345L, 55444L, 55526L, 55571L, 55462L,
55346L, 55576L, 55577L, 55601L, 55300L, 55607L, 55634L, 55558L,
55633L, 55590L, 55594L, 55537L, 55466L, 55327L, 55603L, 55600L,
55302L, 55319L, 55609L, 55574L, 55310L, 55554L, 55582L, 55561L,
55320L, 55555L, 55578L, 55343L, 55331L, 55314L, 55560L, 55460L,
55551L, 55322L, 55306L, 55348L, 55589L, 55572L, 55565L, 55595L,
55606L, 55323L, 55635L, 55568L, 55614L, 55447L, 55312L, 55344L,
55321L, 55569L, 55309L, 55570L, 55562L, 55550L, 55605L, 55465L,
55445L, 55587L, 55332L, 55629L, 55613L, 55448L, 55632L, 55636L,
55531L, 55329L, 55597L, 55298L, 55596L, 55318L, 55608L, 55463L,
55532L, 55557L, 55536L, 55333L, 55533L, 55538L, 55637L, 55330L,
55326L, 55525L), NestkastNummer = c(176L, 124L, 51L, 717L, 54L,
19L, 11L, 42L, 90L, 9L, 713L, 82L, 709L, 2L, 39L, 86L, 16L, 710L,
93L, 94L, 163L, 14L, 170L, 718L, 79L, 715L, 130L, 133L, 57L,
25L, 128L, 164L, 162L, 15L, 60L, 172L, 91L, 31L, 73L, 97L, 111L,
64L, 74L, 95L, 704L, 148L, 36L, 80L, 8L, 68L, 105L, 22L, 716L,
127L, 88L, 81L, 140L, 169L, 109L, 719L, 35L, 185L, 6L, 34L, 707L,
101L, 38L, 28L, 84L, 113L, 62L, 168L, 23L, 3L, 117L, 150L, 705L,
183L, 7L, 714L, 720L, 49L, 144L, 153L, 12L, 143L, 56L, 171L,
17L, 50L, 77L, 55L, 175L, 52L, 58L, 722L, 145L, 125L, 32L), lat_xm =
c(729.2669944,
1001.809576, 501.4865527, 105.2662516, 622.0842564, 313.4718688,
198.828763, 248.3819471, 466.4434076, 155.709257, 433.2482345,
388.4860969, 306.5590574, 14.98895776, 191.9843836, 309.4336924,
308.6123573, 351.526526, 606.8213156, 601.8249333, 912.0799656,
267.5461811, 1084.557939, 264.26089, 359.6713191, 488.4822672,
1018.578266, 915.707476, 773.276261, 171.4513083, 1084.831712,
952.5985963, 878.4741353, 288.3530553, 913.9963847, 1071.827424,
456.313756, 51.12730755, 582.6607182, 592.1059359, 740.3548678,
1042.875765, 476.8468377, 654.0474325, 276.375404, 877.6528113,
135.7921596, 300.9466765, 145.6480126, 829.1262723, 601.4827177,
237.6363065, 500.3230173, 1129.730741, 398.06821, 340.8493193,
770.4016222, 1051.63655, 571.7097287, 314.4300781, 117.5861334,
437.9708453, 95.41039954, 105.7453938, 235.5829892, 627.9704095,
177.0636713, 99.17481232, 396.6993402, 973.4739067, 1034.662528,
1046.77705, 221.278275, 27.24031031, 724.0652756, 942.6742674,
325.9970589, 261.933799, 116.7648206, 464.0478832, 532.6968545,
423.9399058, 656.8536222, 979.9076146, 221.2098377, 701.5473216,
709.8290013, 1120.559295, 345.5719307, 463.4318862, 429.6207308,
659.112262, 717.7684649, 533.3812884, 819.3388243, 600.9351721,
722.4910753, 1126.719223, 26.8297633), long_ym = c(385.4016022,
744.3388344, 1278.519267, 582.1054392, 1183.781188, 1313.545671,
1155.204087, 1008.093201, 812.6125238, 1045.899477, 474.135164,
887.4467064, 626.9169985, 700.9728169, 849.3068501, 799.1579293,
1418.180093, 598.1175046, 928.3664402, 1111.83807, 367.2768291,
1318.32705, 501.4891137, 542.5200518, 1095.7148, 552.6387801,
636.2573659, 479.9172936, 1057.018971, 980.7392501, 739.0014835,
485.8106446, 371.9470232, 1365.91848, 942.3769994, 664.2784869,
887.335514, 669.5046549, 1156.983212, 893.8960158, 933.9261864,
783.4794517, 1191.342439, 975.8466709, 453.8976828, 55.70866057,
731.2178331, 973.6227733, 1002.199869, 920.5827929, 678.1778549,
1141.415921, 578.9919757, 710.2019861, 738.8902861, 936.706063,
480.8068625, 454.8984371, 771.1368166, 510.940689, 680.7353401,
1087.041598, 895.6751282, 641.8171157, 573.7658194, 651.9358502,
816.2819528, 819.6178023, 828.7357905, 801.8266126, 856.9792948,
415.0906484, 1086.374437, 737.4447458, 559.866446, 0, 423.6526577,
1166.990753, 957.8330951, 562.8687158, 564.7590286, 1339.676479,
197.5933584, 132.099559, 1205.686591, 246.6303384, 1106.500715,
597.3391415, 1389.380609, 1312.878499, 1155.760068, 1152.090634,
433.6602223, 1252.833235, 1028.88666, 522.3937678, 151.7810272,
796.3780665, 631.3647851), avg_pop_eb = c(23.57103359, 23.57103359,
23.57103359, 23.57103359, 23.57103359, 23.57103359, 23.57103359,
23.57103359, 23.57103359, 23.57103359, 23.57103359, 23.57103359,
23.57103359, 23.57103359, 23.57103359, 23.57103359, 23.57103359,
23.57103359, 23.57103359, 23.57103359, 23.57103359, 23.57103359,
23.57103359, 23.57103359, 23.57103359, 23.57103359, 23.57103359,
23.57103359, 23.57103359, 23.57103359, 23.57103359, 23.57103359,
23.57103359, 23.57103359, 23.57103359, 23.57103359, 23.57103359,
23.57103359, 23.57103359, 23.57103359, 23.57103359, 23.57103359,
23.57103359, 23.57103359, 23.57103359, 23.57103359, 23.57103359,
23.57103359, 23.57103359, 23.57103359, 23.57103359, 23.57103359,
23.57103359, 23.57103359, 23.57103359, 23.57103359, 23.57103359,
23.57103359, 23.57103359, 23.57103359, 23.57103359, 23.57103359,
23.57103359, 23.57103359, 23.57103359, 23.57103359, 23.57103359,
23.57103359, 23.57103359, 23.57103359, 23.57103359, 23.57103359,
23.57103359, 23.57103359, 23.57103359, 23.57103359, 23.57103359,
23.57103359, 23.57103359, 23.57103359, 23.57103359, 23.57103359,
23.57103359, 23.57103359, 23.57103359, 23.57103359, 23.57103359,
23.57103359, 23.57103359, 23.57103359, 23.57103359, 23.57103359,
23.57103359, 23.57103359, 23.57103359, 23.57103359, 23.57103359,
23.57103359, 23.57103359)), .Names = c("num", "FORM_CHK", "RingNummerMan",
"year_score_taken", "COR_LOC", "IndividuID", "BroedJaar",
"ManipulatieOuders",
"LegBeginDag", "LegBeginMaand", "broodinfo", "BroedselID",
"NestkastNummer",
"lat_xm", "long_ym", "avg_pop_eb"), class = "data.frame", row.names = c(NA,
-99L))
#Below is the code I made to run my analyses
XO<- matrix( 0,6, 76, byrow=TRUE);XO #I first made a matrix to store my
results in
names(ao)
ao$NestkastNummer
b<-c(77:99)
abo<-ao$NestkastNummer[-b];abo #removed values that were NA
rownames(XO) = c("EB_score","avg","pop_size","pop_avg_score",
"adj_pop_avg", "ind_pop_dif")
colnames(XO) = c((abo))
ncol(XO)
names(ao)
t <- ao$COR_LOC;t
i <- c(77:99)
ti <- t[-i];ti
XO[1,] = c(ti);XO #assigned values from data frame to the matrix
### average difference b/n neighbours for each individual
XO["avg", "176"]<- mean(abs((XO[1,"176"])-XO[1,c("140","162","713")]))
XO["avg", "124"]<-
mean(abs((XO[1,"124"])-XO[1,c("113","64","128","172","130","117")]))
XO["avg", "51"]<- mean(abs((XO[1,"51"])-XO[1,c("74")]))
XO["avg", "717"]<- mean(abs((XO[1,"717"])-XO[1,c("34","707","704","718")]))
XO["avg", "54"]<- mean(abs((XO[1,"54"])-XO[1,c("73","94")]))
XO["avg", "19"]<- mean(abs((XO[1,"19"])-XO[1,c("15","14")]))
XO["avg", "11"]<- mean(abs((XO[1,"11"])-XO[1,c("22","23","9")]))
XO["avg", "42"]<-
mean(abs((XO[1,"42"])-XO[1,c("23","79","80","39","25","9")]))
XO["avg", "90"]<- mean(abs((XO[1,"90"])-XO[1,c("91","97","109","88","84")]))
XO["avg", "9"]<- mean(abs((XO[1,"9"])-XO[1,c("11","23","42","25","8")]))
XO["avg", "713"]<- mean(abs((XO[1,"713"])-XO[1,c("715","719","710","176")]))
XO["avg", "82"]<- mean(abs((XO[1,"82"])-XO[1,c("81","91","84","86")]))
XO["avg", "709"]<-
mean(abs((XO[1,"709"])-XO[1,c("36","86","88","710","718","707","35")]))
XO["avg", "2"]<- mean(abs((XO[1,"2"])-XO[1,c("3","31")]))
XO["avg", "39"]<-
mean(abs((XO[1,"39"])-XO[1,c("25","42","80","81","86","38","28","6")]))
XO["avg", "86"]<-
mean(abs((XO[1,"86"])-XO[1,c("38","39","81","82","84","88","709","36")]))
XO["avg", "16"]<- mean(abs((XO[1,"16"])-XO[1,c("15")]))
XO["avg", "710"]<-
mean(abs((XO[1,"710"])-XO[1,c("709","88","713","719","718")]))
XO["avg", "93"]<-
mean(abs((XO[1,"93"])-XO[1,c("185","94","95","111","97","91")]))
XO["avg", "94"]<- mean(abs((XO[1,"94"])-XO[1,c("73","54","95","93","185")]))
XO["avg", "163"]<- mean(abs((XO[1,"163"])-XO[1,c("133","164","168","162")]))
XO["avg", "14"]<- mean(abs((XO[1,"14"])-XO[1,c("15","19")]))
XO["avg", "170"]<- mean(abs((XO[1,"170"])-XO[1,c("130","164","169","168")]))
XO["avg", "718"]<-
mean(abs((XO[1,"718"])-XO[1,c("707","709","710","719","704")]))
XO["avg", "79"]<-
mean(abs((XO[1,"79"])-XO[1,c("23","22","185","81","80","42")]))
XO["avg", "715"]<- mean(abs((XO[1,"715"])-XO[1,c("716","713")]))
XO["avg", "130"]<-
mean(abs((XO[1,"130"])-XO[1,c("124","172","170","164","133","117")]))
XO["avg", "133"]<-
mean(abs((XO[1,"133"])-XO[1,c("117","130","164","163","162","140")]))
XO["avg", "57"]<- mean(abs((XO[1,"57"])-XO[1,c("95","111")]))
XO["avg", "25"]<- mean(abs((XO[1,"25"])-XO[1,c("8","9","42","80","39")]))
XO["avg", "128"]<- mean(abs((XO[1,"128"])-XO[1,c("124","64","127","172")]))
XO["avg", "164"]<-
mean(abs((XO[1,"164"])-XO[1,c("130","170","169","168","163","133")]))
XO["avg", "162"]<- mean(abs((XO[1,"162"])-XO[1,c("176","140","133","163")]))
XO["avg", "15"]<- mean(abs((XO[1,"15"])-XO[1,c("16","19","14")]))
XO["avg", "60"]<- mean(abs((XO[1,"60"])-XO[1,c("62","68","113")]))
XO["avg", "172"]<- mean(abs((XO[1,"172"])-XO[1,c("124","128","127","130")]))
XO["avg", "91"]<-
mean(abs((XO[1,"91"])-XO[1,c("185","93","97","90","84","82","81")]))
XO["avg", "31"]<- mean(abs((XO[1,"31"])-XO[1,c("2","3","36","35","34")]))
XO["avg", "73"]<- mean(abs((XO[1,"73"])-XO[1,c("74","54","94","185")]))
XO["avg", "97"]<-
mean(abs((XO[1,"97"])-XO[1,c("91","93","111","109","90")]))
XO["avg", "111"]<-
mean(abs((XO[1,"111"])-XO[1,c("95","57","68","101","109","97","93")]))
XO["avg", "64"]<- mean(abs((XO[1,"64"])-XO[1,c("113","62","128","124")]))
XO["avg", "74"]<- mean(abs((XO[1,"74"])-XO[1,c("51","73","185")]))
XO["avg", "95"]<- mean(abs((XO[1,"95"])-XO[1,c("94","57","111","93")]))
XO["avg", "704"]<- mean(abs((XO[1,"704"])-XO[1,c("719","718","707","717")]))
XO["avg", "148"]<- mean(abs((XO[1,"148"])-XO[1,c("150")]))
XO["avg", "36"]<-
mean(abs((XO[1,"36"])-XO[1,c("28","38","86","709","707","35","3")]))
XO["avg", "80"]<- mean(abs((XO[1,"80"])-XO[1,c("42","79","81","39","25")]))
XO["avg", "8"]<- mean(abs((XO[1,"8"])-XO[1,c("9","25")]))
XO["avg", "68"]<-
mean(abs((XO[1,"68"])-XO[1,c("111","60","113","117","101")]))
XO["avg", "105"]<- mean(abs((XO[1,"105"])-XO[1,c("88","109","101","716")]))
XO["avg", "22"]<- mean(abs((XO[1,"22"])-XO[1,c("11","79","23")]))
XO["avg", "716"]<- mean(abs((XO[1,"716"])-XO[1,c("88","105","715")]))
XO["avg", "127"]<- mean(abs((XO[1,"127"])-XO[1,c("128","172")]))
XO["avg", "88"]<-
mean(abs((XO[1,"88"])-XO[1,c("86","84","90","109","105","716","710","709")]))
XO["avg", "81"]<-
mean(abs((XO[1,"81"])-XO[1,c("80","79","185","91","82","86","39")]))
XO["avg", "140"]<- mean(abs((XO[1,"140"])-XO[1,c("117","133","162","176")]))
XO["avg", "169"]<- mean(abs((XO[1,"169"])-XO[1,c("164","170","168")]))
XO["avg", "109"]<-
mean(abs((XO[1,"109"])-XO[1,c("90","97","111","101","105","88")]))
XO["avg", "719"]<- mean(abs((XO[1,"719"])-XO[1,c("718","710","713","704")]))
XO["avg", "35"]<-
mean(abs((XO[1,"35"])-XO[1,c("36","709","707","34","31","3")]))
XO["avg", "185"]<-
mean(abs((XO[1,"185"])-XO[1,c("79","74","73","94","93","91","81")]))
XO["avg", "6"]<- mean(abs((XO[1,"6"])-XO[1,c("39","28","3")]))
XO["avg", "34"]<- mean(abs((XO[1,"34"])-XO[1,c("31","35","707","717")]))
XO["avg", "707"]<-
mean(abs((XO[1,"707"])-XO[1,c("34","35","36","709","718","717","704")]))
XO["avg", "101"]<-
mean(abs((XO[1,"101"])-XO[1,c("105","109","111","68","113","117")]))
XO["avg", "38"]<- mean(abs((XO[1,"38"])-XO[1,c("39","86","36","28")]))
XO["avg", "28"]<- mean(abs((XO[1,"28"])-XO[1,c("6","39","38","36","3")]))
XO["avg", "84"]<- mean(abs((XO[1,"84"])-XO[1,c("82","91","90","88","86")]))
XO["avg", "113"]<-
mean(abs((XO[1,"113"])-XO[1,c("68","60","62","64","124","117","101")]))
XO["avg", "62"]<- mean(abs((XO[1,"62"])-XO[1,c("60","64","113")]))
XO["avg", "168"]<- mean(abs((XO[1,"168"])-XO[1,c("170","169","164","163")]))
XO["avg", "23"]<- mean(abs((XO[1,"23"])-XO[1,c("9","11","22","79","42")]))
XO["avg", "3"]<- mean(abs((XO[1,"3"])-XO[1,c("6","28","36","35","31","2")]))
XO["avg", "117"]<-
mean(abs((XO[1,"117"])-XO[1,c("101","113","124","130","133","140","68")]))
XO["avg", "150"]<- mean(abs((XO[1,"150"])-XO[1,c("148")]))
XO["pop_size",] <- 76
XO["pop_avg_score",]<- mean(XO["EB_score",])
for (i in XO){
XO["adj_pop_avg",] <-
((XO["pop_avg_score",])*(XO["pop_size",])-(XO["EB_score",]))/((XO["pop_size",]-1))
#here I ran a loop to get info
XO["ind_pop_dif",] <-abs((XO["EB_score",]-XO["adj_pop_avg",]))}
t.test(XO["avg",], XO["ind_pop_dif",], paired=TRUE)
XO
XO<-rbind(XO,0)
rownames(XO)<-c("EB_score","avg","pop_size","pop_avg_score", "adj_pop_avg",
"ind_pop_dif", "non_nei")
XO["non_nei",]<-0
rowMeans(XO[,1:76])
#This is the average observed discrepancy from individuals to neighbours
#IOW on average how different is a focal bird in this year different from
its neighbours
obso=mean(XO["avg",])
print(paste("Observed=", obso))
XY[15,1]<-round(obso, digits=4)
#This is the code I previously posted to find the difference in scores
between a single subject and its non-neighbours
o<-(ao[,c(13,5)])
o<-na.omit(o)
o<-o[!o$NestkastNummer %in% c(176,140,162,713),]
XO[7,1]<-abs((XO[1,"176"]-(mean(o[,"COR_LOC"]))))
Best,
Monaly.
On Thu, May 22, 2014 at 5:08 PM, John Kane <jrkrid...@inbox.com> wrote:
> Re dput() etc
> https://github.com/hadley/devtools/wiki/Reproducibility
>
> http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example
>
> What dput() does is take your data and ouput it in an ascii format that
> let's the reader here create an exact duplicate of your database.
>
> R is not WYSIWYG. Often what you see on the screen does not tell the whole
> tale. R supports a number of different data types: vectors, matrices,
> data.frames, lists, arrays and others. This site gives a useful though not
> complete summary of many data types
> http://www.statmethods.net/input/datatypes.html. When you have just
> created a new data set, or even when working with one that you have not
> worked with in some time it is a good idea to do a str() and class() on the
> data object just to be sure that you are working with the data types you
> think you have. What looks like a column of numbers in a data.frame may
> actually be a set of factors or a set of character (text) data and you're
> left wondering why multiplying it by some number is not working.
>
> Here is a short example to illustrate. Just copy and paste in the code
> dat1 <- data.frame(aa = as.factor(1:5), bb = 1:5)
> dat1 # data looks identical on the screen
> 5*dat1[,"aa"] # oops
> 5*dat1[, "bb"] # okay
> str(dat1)
>
>
> John Kane
> Kingston ON Canada
>
>
> > -----Original Message-----
> > From: monaly.mis...@gmail.com
> > Sent: Thu, 22 May 2014 16:31:39 +0100
> > To: smartpink...@yahoo.com, r-help@r-project.org
> > Subject: Re: [R] subsetting to exclude different values for each subject
> > in study
> >
> > Hi,
> >
> > Sorry I'm fairly new to R and I don't really understand using dput(),
> > when
> > you say reproducible example do you mean the code with the output?
> >
> > Best,
> >
> > Monaly.
> >
> >
> > On Thu, May 22, 2014 at 4:03 PM, arun <smartpink...@yahoo.com> wrote:
> >
> >> Hi,
> >>
> >> It would be helpful if you provide a reproducible example using ?dput().
> >>
> >> A.K.
> >>
> >>
> >>
> >>
> >> On Thursday, May 22, 2014 10:15 AM, Monaly Mistry
> >> <monaly.mis...@gmail.com>
> >> wrote:
> >> Hi,
> >>
> >> I've written a code to determine the difference in score for a single
> >> subject and its non-neighbours
> >>
> >> o<-(ao[,c(13,5)]) ##this is the table with the relevant information
> >> o<-na.omit(o) ##omitted data with NA
> >> o<-o[!o$NestkastNummer %in% c(176,140,162,713),] ##removed neighbours
> >> XO[7,1]<-abs((XO[1,"176"]-(mean(o[,"COR_LOC"])))) #difference between
> >> that
> >> individual and average non-neighbours scores
> >>
> >> Since each subject has a different number of non-neighbours I was
> >> wondering
> >> if there is an efficient way of writing the code, instead of writing the
> >> same code again and again (76 subjects) for each subject and its
> >> non-neighbours.
> >>
> >>
> >> Best,
> >>
> >> Monaly.
> >>
> >> [[alternative HTML version deleted]]
> >>
> >> ______________________________________________
> >> R-help@r-project.org mailing list
> >> https://stat.ethz.ch/mailman/listinfo/r-help
> >> PLEASE do read the posting guide
> >> http://www.R-project.org/posting-guide.html
> >> and provide commented, minimal, self-contained, reproducible code.
> >>
> >>
> >
> > [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> > http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
>
> ____________________________________________________________
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