search for: 929l

Hi, I am trying to identify duplicate values in a column in a date frame. The duplicated function identifies the duplicate rows in the data frame but it only does this for the second record, not both records. Is there a way to mark both rows in the data frame as TRUE? dfA$dups<-duplicated(dfA$Value) dfA Site State Value dups 929 VA 73 FALSE 929 VA 73 TRUE 930 VA 76 FALSE 930 VA 76 TRUE 931

..., 634L, 658L, 649L, 637L, 655L, 640L, 644L, 645L, 636L, 647L, 646L, 639L, 654L, 665L, 673L, 680L, 701L, 688L, 712L, 737L, 738L, 784L, 766L, 785L, 753L, 773L, 799L, 791L, 808L, 818L, 826L, 821L, 820L, 838L, 830L, 837L, 841L, 840L, 844L, 850L, 845L, 886L, 875L, 887L, 868L, 899L, 912L, 915L, 931L, 929L, 934L, 939L, 957L, 988L, 975L, 981L, 1015L, 1003L, 1043L, 1051L, 1056L, 1034L, 1031L, 1073L, 1068L, 1065L, 1079L, 1101L, 1092L, 1089L, 1096L), class = "data.frame") [[alternative HTML version deleted]]

...1899L, 1284L, 1488L, 1618L, 2523L, 1217L, 1292L, 698L, 945L, 1506L, 1543L, 1460L, 1170L, 1300L, 1169L, 895L, 405L, 812L, 2388L, 966L, 338L, 647L, 587L, 203L, 857L, 370L, 687L, 570L, 587L, 928L, 520L, 134L, 587L, 891L, 1699L, 1483L, 1461L, 1240L, 804L, 708L, 988L, 426L, 647L, 719L, 1365L, 619L, 929L, 3758L, 511L, 1242L, 1160L, 734L, 1398L, 857L, 966L, 2112L, 1117L, 1605L, 740L, 309L, 1555L, 938L, 864L, 957L, 1271L, 1291L, 1073L, 391L, 1056L, 560L, 650L, 1382L, 978L, 963L, 1328L, 620L, 1186L, 954L, 837L, 1200L, 1601L, 812L, 1879L, 1496L, 1433L, 1016L, 1035L, 2787L, 390L, 1443L, 1231L, 1511L...

...ole dataset but I am having trouble with 'newdata'. The model was created with 153 records and want to predict for 208 records. wolf2 <- structure(list(gridcell = c(367L, 444L, 533L, 587L, 598L, 609L, 620L, 629L, 641L, 651L, 662L, 674L, 684L, 695L, 738L, 748L, 804L, 805L, 872L, 919L, 929L, 938L, 950L, 958L, 966L, 975L, 976L, 985L, 994L, 1006L, 1015L, 1019L, 1022L, 1025L, 1027L, 1028L, 1029L, 1032L, 1040L, 1043L, 1050L, 1053L, 1061L, 1070L, 1074L, 1078L, 1080L, 1082L, 1083L, 1084L, 1090L, 1095L, 1096L, 1099L, 1106L, 1116L, 1124L, 1125L, 1130L, 1133L, 1134L, 1137L, 1138L, 1139L,...

...853L, 854L, 855L, 856L, 857L, 858L, 859L, 860L, 861L, 862L, 863L, 864L, 865L, 866L, 867L, 868L, 869L, 870L, 871L, 885L, 886L, 887L, 888L, 889L, 890L, 891L, 892L, 893L, 894L, 895L, 896L, 897L, 898L, 899L, 900L, 901L, 902L, 903L, 904L, 905L, 906L, 907L, 908L, 909L, 910L, 924L, 925L, 926L, 927L, 928L, 929L, 930L, 931L, 932L, 933L, 934L, 935L, 936L, 937L, 938L, 939L, 940L, 941L, 942L, 943L, 944L, 945L, 946L, 947L, 948L, 949L, 963L, 964L, 965L, 966L, 967L, 968L, 969L, 970L, 971L, 972L, 973L, 974L, 975L, 976L, 977L, 978L, 979L, 980L, 981L, 982L, 983L, 984L, 985L, 986L, 987L, 988L, 1002L, 1003L, 1004L, 1...

...L, 1070L, 1202L, 1334L, 1466L, 1598L, 1730L, 1862L, 1994L, 2126L, 2258L, 2390L, 2522L, 2654L, 2786L, 2918L, 3050L, 3182L, 3314L, 3446L, 3578L, 3708L, 25L, 157L, 289L, 421L, 553L, 685L, 817L, 949L, 1081L, 1213L, 1345L, 1477L, 1609L, 1741L, 1873L, 2005L, 2137L, 2269L, 2401L, 2533L, 2665L, 2797L, 2929L, 3061L, 3193L, 3325L, 3457L, 3589L, 3712L, 3833L, 3954L, 36L, 168L, 300L, 432L, 564L, 696L, 828L, 960L, 1092L, 1224L, 1356L, 1488L, 1620L, 1752L, 1884L, 2016L, 2148L, 2280L, 2412L, 2544L, 2676L, 2808L, 2940L, 3072L, 3204L, 3336L, 3468L, 3600L, 3723L, 3844L, 47L, 179L, 311L, 443L, 575L, 707L, 8...

...24L, 15924L, 15924L, 15924L, 15924L, 15925L, 15925L, 15925L, 15925L, 15925L, 15925L, 15925L, 15925L, 15926L, 15926L, 15926L, 15926L, 15926L, 15926L, 15926L, 15926L, 15927L, 15927L, 15927L, 15927L, 15927L, 15927L, 15927L, 15927L, 15928L, 15928L, 15928L, 15928L, 15928L, 15928L, 15928L, 15928L, 15929L, 15929L, 15929L, 15929L, 15929L, 15929L, 15929L, 15929L, 15930L, 15930L, 15930L, 15930L, 15930L, 15930L, 15930L, 15930L, 15931L, 15931L, 15931L, 15931L, 15931L, 15931L, 15931L, 15931L, 15932L, 15932L, 15932L, 15932L, 15932L, 15932L, 15932L, 15932L, 15933L, 15933L, 15933L, 15933L, 15933L, 15933...

Hello, I have a pedigree file such this: FAMID ID FA ID MO ID SEX STATUS 1 1 0 0 2 0 1 2 3 1 2 2 1 4 3 1 1 2 1 5 3 1 1 0 1 6 3 1 1 0 1 7 3 1 2 2 1 8 3 1 1 0 1 9 3 1 1 0 1 10 3 1 2 0 1 11 3 1 1 0 1 3 0 0 1 0 2 12 13