search for: 80l

...L, 3L, 2L, 3L, 1L, 2L, 1L, 2L, 3L), .Label = c("bank", "missed", "steal"), class = "factor"), Var2 = structure(c(89L, 89L, 89L, 88L, 88L, 88L, 87L, 87L, 87L, 86L, 86L, 86L, 85L, 85L, 85L, 84L, 84L, 84L, 83L, 83L, 83L, 82L, 82L, 82L, 81L, 81L, 81L, 80L, 80L, 80L, 79L, 79L, 79L, 78L, 78L, 78L, 77L, 77L, 77L, 76L, 76L, 76L, 75L, 75L, 75L, 74L, 74L, 74L, 73L, 73L, 73L, 72L, 72L, 72L, 71L, 71L, 71L, 70L, 70L, 70L, 69L, 69L, 69L, 68L, 68L, 68L, 67L, 67L, 67L, 66L, 66L, 66L, 65L, 65L, 65L, 64L, 64L, 64L, 63L, 63L, 63L, 62L, 62L, 62L...

...d is id number, age is the age of the person, and seq is the sequence variable that I've created. Thanks very much for the help. david freedman, atlanta ds=data.frame(list(id = c(1L, 1L, 1L, 1L, 8L, 8L, 16L, 16L, 16L, 16L, 16L, 19L, 32L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 79L, 79L, 80L, 80L, 80L, 80L, 85L, 86L, 96L, 96L, 96L, 103L, 103L, 106L, 106L, 106L, 106L, 106L, 106L, 106L, 140L, 140L, 144L, 144L, 144L, 144L, 144L, 144L, 144L, 146L, 146L, 146L, 146L, 160L, 160L, 160L, 160L, 160L, 160L, 164L, 164L, 176L, 176L, 176L, 176L, 176L, 176L, 176L, 176L, 181L, 190L, 192L, 192L, 192L,...

...L, 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), .Label = c("dn", "up" ), class = "factor"), sand.silt = c(20L, 45L, 90L, 21L, 80L, 77L, 30L, 80L, 36L, 9L, 62L, 71L, 20L, 65L, 10L, 70L, 50L, 80L, 90L, 97L, 94L, 82L, 30L, 10L, 65L, 80L, 90L, 70L, 10L, 50L, 60L, 40L, 10L, 45L, 10L, 10L, 15L, 10L, 8L, 35L, 10L, 40L, 10L, 10L, 28L, 5L, 45L, 35L, 2L, 10L, 40L, 2L, 70L, 40L, 20L, 30L, 50L, 60L, 10L, 100L, 98L, 98L, 90L, 87L, 87L, 40...

...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, 76L, 77L, 78L, 79L, 80L, 81L, 82L, 83L, 84L, 85L, 86L, 87L, 88L, 89L, 90L, 91L, 92L, 93L, 94L, 95L, 96L, 97L, 98L, 99L, 100L, 101L, 102L, 103L, 104L, 105L, 106L, 107L, 108L, 109L, 110L, 111L, 112L, 113L, 114L, 115L, 116L, ...... ...... ..... V2 = structure(c(278L, 23L, 11L, 169L, 14L, 86L, 94L, 51L, 37L, 43L, 22L, 16...

...index.date to obtain information from other df for every id six month previous the index date. Then I should normalize the ftime to a common time frame and look form patterns in that time frame. (Do not know yet how I will do it. ) ### test data #### structure(list(id = c(1L, 1L, 1L, 46L, 80L, 80L, 80L, 80L, 88L, 160L, 179L, 179L, 179L, 179L, 179L, 179L, 192L, 192L, 192L, 204L, 204L, 204L, 204L, 205L, 211L, 233L, 233L, 272L, 272L, 272L, 272L, 309L, 309L, 309L, 310L, 310L, 314L, 314L, 315L, 316L, 320L, 320L, 320L, 320L, 324L, 324L, 324L, 329L, 329L, 339L, 354L, 354L, 354L, 357L, 358...

...4.5, 4.5, 4.6, 4.5, 4.6, 3.9, 4.2, 4.9, 4.9, 4.5, 16.7, 17.4, 17.5, 17.5, 17.4, 1.9, 2.4, 1.7, 1.2, 1.5, 1.1, 1.8, 3.1, 3.1, 3, 4.1, 4.2, 2.7, 4.5, 0.4, 1.2, 3, 3.5, 1.2, 0.8, 0.9, 2, -0.8, 5.8, 0.6, 1, 0.9, 4.4, 2.3, -0.1), dD = c(-66L, -81L, -81L, -71L, -68L, -79L, -73L, -77L, -74L, -71L, -73L, -80L, -76L, -80L, -74L, -77L, -74L, -77L, -74L, -82L, -79L, -72L, -74L, -71L, -76L, -72L, -76L, -73L, -75L, -78L, -81L, -77L, -77L, -73L, -79L, -104L, -98L, -98L, -109L, -106L, -99L, -107L, -100L, -98L, -95L, -95L, -95L, -97L, -98L, -121L, -119L, -118L, -121L, -121L, -106L, -116L, -122L, -112L, -125L, -...

...he TRUE/FALSE options of the colnames argument in sqlFetch (RODBC) seem to be reversed, at least for .xls files. ## z is a connection to an xls workbook opened by odbcConnectExcel() > dat<-sqlFetch(z,'SuccessRates',colnames=FALSE) > dat[1:5,] RecID Name Run Grams Lost Run (80L) 1 NA Activase 117 839.91 0 2 NA Activase 118 860.52 0 3 NA Activase 119 921.23 0 4 NA Activase NA NA 1 5 NA Activase 120 722.62 0 > dat2<-sqlFetch(z,'SuccessRates',colnames=TRUE) > dat2[1:5,] N...

...98, 96, 98, 98, 99, 98, 98, 99, 99, 98, 99, 98, 99, 99, 99, 99, 98, 99, 96, 99, 98, 98, 99, 97, 98, 99, 99, 97, 99, 99, 98, 98, 98, 99, NA, 99, 98, 98, 98, 98, 98, 98, 98, 99, 99, 98, 99, 99, 98, 98, 99, 99, 97, 98, 98, 98, 99, 98, 98, 98, 99, 98, 98)), .Names = "var1", row.names = c(NA, 80L), class = "data.frame") cut2(dat[,1], g=4) Warning message: In min(xx[xx > upper]) : no non-missing arguments to min; returning Inf Regards, Charles [[alternative HTML version deleted]]

Hi All, I have a scatter plot produced using ggplot2 and I want to add the regression line to this scatter plot. I suppose I can use geom_smooth() to do this, but for the sake of learning ( I am new both to R and ggplot2), I want to try and add it as a function (something that curve() does in the standard R plotting). I did some search and found that stat_function() can be used for this. But

..., I can't seem to get the data to match the axis anymore. I must be using the axis.break() in plotrix incorrectly, but I cannot see where my issue is. This is what I have so far. ###### library(plotrix) par(mar=c(6,8,4,4)) ###Data Saline <- structure(list(Time = c(-20L, 0, 30L, 45L, 60L, 80L, 110L,140L,200L, 260L, 320L), Average = c(119.250,118.750,117.500,132.75,151.875,159.75,142.75,160,168,167.125,143),SEM=c(2.211,2.569,2.665,5.435146394,6.208741369,8.363550657,8.51349469,14.30284687,15.93865792,16.76541326,13.796)), .Names = c("Time (min)", "Arterial Plasma Glucose...

..., 14784, 14784, 14784, 14784, 14784, 14784, 14784, 14784 ), class = "Date"), bp_date = structure(c(12660, 14571, 13392, 13080, 12012, 13080, 13894, 14622, 12654, 13894), class = "Date"), SBP = c(135L, 160L, 135L, 153L, 150L, 153L, 151L, 126L, 150L, 151L), DBP = c(85L, 80L, NA, 79L, 82L, 79L, 76L, 60L, 82L, 91L)), .Names = c("prochi", "date_1st_event", "bp_date", "SBP", "DBP"), row.names = 108:117, class = "data.frame") It consists of repeated measures for the same individual. What I want to do is fi...

...44340, 1210555800, 1210563120, 1210564980, 1210572600, 1210585620, 1210595520, 1210602840, 1210613820, 1210618200, 1210633260, 1210640940, 1210650240, 1210663560, 1210677660, 1210686960, 1210695240, 1210705380), class = c("POSIXct", "POSIXt"), tzone = ""), Score = c(80L, 11L, 81L, 152L, 130L, 122L, 142L, 20L, 1L, 31L, 93L, 136L, 128L, 112L, 48L, 57L, 92L, 108L, 100L, 107L, 81L, 37L, 47L, 70L, 114L, 125L, 99L, 46L, 108L, 106L, 111L, 75L, 75L, 136L, 36L, 13L, 35L, 71L, 105L, 113L, 116L, 116L, 94L, 130L, 102L, 19L, 1L, 33L, 78L, 89L, 115L, 130L, 117L, 105L, 0L,...

...55L, 56L, 56L, 57L, 57L, 57L, 58L, 58L, 58L, 59L, 60L, 60L, 60L, 61L, 61L, 62L, 62L, 63L, 63L, 64L, 64L, 64L, 65L, 65L, 66L, 66L, 66L, 67L, 67L, 67L, 68L, 68L, 68L, 69L, 69L, 70L, 70L, 71L, 71L, 73L, 73L, 73L, 73L, 74L, 74L, 74L, 74L, 75L, 75L, 75L, 75L, 76L, 76L, 76L, 76L, 78L, 78L, 78L, 79L, 79L, 80L, 80L, 81L, 81L, 81L, 81L, 82L, 82L, 82L, 83L, 83L, 83L, 84L, 85L, 85L, 85L, 87L, 87L, 87L, 87L, 87L, 87L, 88L, 88L, 88L, 88L, 89L, 89L, 90L, 91L, 91L, 91L, 91L, 91L, 92L, 93L, 93L, 94L, 95L, 95L, 95L, 95L, 96L, 96L, 96L, 97L, 97L, 98L, 98L, 98L, 98L, 99L, 100L, 100L, 100L, 100L, 100L), d = c(15, 27...

I have been working with the pls procedure and have problems getting the procedure to work with matrix or frame data. I suspect the problem lies in my understanding of frames, but can't find anything in the documentation that will help. Here is what I have done: I read in an 10000 x 8 table of data, and assign the first four columns to matrix A and the second four to matrix B pls <-

Hello, It's an alternative to use SAS by function in R? I want to plot d histograms by plot.from example bellow: Thank you! plot d 1 1 16.3 2 1 25.0 3 1 57.8 4 1 17.0 5 2 10.8 13 2 96.4 17 3 76.0 18 3 32.0 19 3 11.0 20 3 11.0 24 3 106.0 25 3 12.5 21 4 19.3 22 4 12.0 26 4 15.0 27 5 99.3 32 7 11.0 36

...23.55, 23.61, 23.77, 23.83, 23.9, 23.96, 24, 24.01, 24.14, 24.5, 24.61, 24.76, 24.85, 24.99, 25, 25.6, 25.61, 25.7, 26.09, 26.5, 26.72, 26.89, 29.5, 30.54, 40.63, 40.73, 41.74, 43.5, 44.33, 45.33, 46.05, 47.11, 47.34, 49.58, 50.71, 77, 86.68, 97, 133.6, 203.48), Size = c(664640L, 440L, 407L, 180L, 690L, 851L, 190L, 480L, 720L, 74L, 111L, 1560L, 11400L, 160L, 9333L, 55665L, 222L, 23662L, 210L, 12735L, 1757L, 63736L, 18318L, 460L, 120L, 680L, 400L, 960L, 432L, 259L, 840L, 8200L, 630L, 180L, 189L, 1490L, 27L, 8080L, 6291L, 240L, 841L, 5469L, 4035L, 12555L, 5320L, 9249L, 240L, 1149L, 40L, 6...

...;, "POS", "SUI"), class = "factor"), ? ? V4 = c(5L, 2L, 1L, 3L, 1L, 0L, 1L, 5L, 1L, 3L, 2L, 3L, 4L, ? ? 0L, 4L, 2L, 4L, 0L, 5L, 0L), V5 = c(0L, 1L, 0L, 1L, 0L, 0L, ? ? 1L, 1L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 0L, 1L, 1L), ? ? V6 = c(830L, 295L, 136L, 696L, 136L, 80L, 183L, 176L, 192L, ? ? 184L, 176L, 176L, 184L, 72L, 120L, 96L, 207L, 112L, 192L, ? ? 216L)), .Names = c("V1", "V2", "V3", "V4", "V5", "V6"), row.names = c(NA, 20L), class = "data.frame"), structure(list(V1 = c(0L, 0L, 0L, 0L,...

...2800, 1210048980, 1210061520, 1210074480, 1210081200, 1210089300, 1210095960, 1210104120, 1210110900, 1210110900, 1210118400, 1210126980, 1210134180, 1210142640, 1210156080, 1210164180, 1210176840, 1210183740), class = c("POSIXct", "POSIXt"), tzone = ""), Score = c(80L, 11L, 81L, 152L, 130L, 122L, 142L, 20L, 1L, 31L, 93L, 136L, 128L, 112L, 48L, 57L, 92L, 108L, 100L, 107L, 81L, 37L, 47L, 70L, 114L, 125L, 99L, 46L, 108L, 106L, 111L, 75L, 75L, 136L, 36L, 13L, 35L, 71L, 105L, 113L, 116L, 116L, 94L, 130L, 102L, 19L, 1L, 33L, 78L, 89L)), .Names = c("Date"...

...s which I can pass on to my students. Thanks David Arnold College of the Redwoods > dput(flies) structure(list(long = c(40L, 37L, 44L, 47L, 47L, 47L, 68L, 47L, 54L, 61L, 71L, 75L, 89L, 58L, 59L, 62L, 79L, 96L, 58L, 62L, 70L, 72L, 74L, 96L, 75L, 46L, 42L, 65L, 46L, 58L, 42L, 48L, 58L, 50L, 80L, 63L, 65L, 70L, 70L, 72L, 97L, 46L, 56L, 70L, 70L, 72L, 76L, 90L, 76L, 92L, 21L, 40L, 44L, 54L, 36L, 40L, 56L, 60L, 48L, 53L, 60L, 60L, 65L, 68L, 60L, 81L, 81L, 48L, 48L, 56L, 68L, 75L, 81L, 48L, 68L, 35L, 37L, 49L, 46L, 63L, 39L, 46L, 56L, 63L, 65L, 56L, 65L, 70L, 63L, 65L, 70L, 77L, 81L, 86L,...

Hello, I'm a new R user. I have two different dummy tables with the variable name tb1 and tb2. tb1< v1 v2 v3 v4 "chr1" 22 23 3 "chr1" 36 37 1 "chr1" 54 55 0 "chr1" 77 78 1 "chr2" 80 81 4 "chr2" 85 86 0 "chr2" 99 100 1