search for: 88l

...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, 27.5, 10.5, 12.25, 14, 32.5, 80, 49.5, 15.25, 13.5, 12.25, 12, 72.5, 68.5, 12, 9.25, 12.75, 13.5, 28, 38, 10.25,...

...L, 2L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 3L, 2L, 1L, 2L, 3L, 1L, 3L, 2L, 1L, 2L, 3L, 1L, 3L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 1L, 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...

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

...4L, 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, 2...

...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, 358L, 359L, 364L, 366L,...

...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, 169L, 49L, 120L, 18L, 60L, 42L, 41L, 38L,...

...ng to build an animation and facing problem as animation is not coming "live". The goal is to build "heart beats" like diagram for the data given below. data : structure(list(date = 1971:1991, x = c(41L, 60L, 41L, 61L, 22L, 83L, 31L, 55L, 22L, 14L, 38L, 6L, 29L, 17L, 10L, 99L, 88L, 32L, 68L, 78L, 26L)), .Names = c("date", "x"), class = "data.frame", row.names = c(NA, -21L)) Program : > library(animation)> library(ggplot2) > anim <- function(a){for (i in seq(1,21)) {pl <- ggplot(a1111,aes(x=date,y=x))+geom_line()+scale_x_continu...

...9L, 179L, 185L, 190L, 198L, 61L, 61L, 119L, 148L, 202L, 202L, 61L, 61L, 119L, 148L, 185L, 202L, 215L )), .Names = c("TSS", "GPP", "RiverMile"), class = "data.frame", row.names = c(12L, 13L, 14L, 19L, 25L, 26L, 28L, 34L, 35L, 36L, 37L, 42L, 44L, 58L, 75L, 85L, 88L, 91L, 97L, 107L, 142L, 144L, 155L, 166L, 169L, 185L, 186L, 201L, 202L, 207L, 219L, 221L, 222L, 224L, 226L, 230L, 231L, 250L, 251L, 258L, 283L, 287L, 288L, 303L, 304L, 306L, 311L, 313L))) library(lattice) library(ggplot2) z <- nls(GPP~(a/(TSS+b)), start=c(a=0.01, b=0.01), data=r) f <- seq(-1,...

...4L, 52L, 61L, 67L, 91L, 13L, 24L, 36L, 38L, 7L, 81L, 82L, 57L, 64L, 100L, 113L, 21L, 33L, 44L, 78L, 54L, 73L, 83L, 108L, 16L, 28L, 2L, 58L, 65L, 86L, 101L, 32L, 43L, 77L, 93L, 104L, 10L, 48L, 53L, 97L, 110L, 18L, 27L, 75L, 92L, 103L, 31L, 9L, 47L, 70L, 72L, 106L, 14L, 26L, 40L, 79L, 98L, 112L, 68L, 88L, 105L, 20L, 11L, 49L, 63L, 5L, 80L, 50L, 59L, 89L, 114L, 22L, 34L, 45L), .Label = c("1/14/08 12:26", "1/15/08 15:25", "1/15/08 16:32", "1/16/08 11:36", "1/16/08 15:29", "1/21/08 11:21", "1/21/08 14:18", "1/22/07 13:59",...

Dear R users, I want to aggregate all *d *data from all combination of n *plots* taken by k. Thank very much! My data is like that: plot d 1 14 1 13 1 12 1 14 1 18 1 20 1 21 1 43 1 108 1 43 2 41 2 61 2 83 2 61 2 84 2 45 2 21 2 12 2 11 ... 100 10 100 12 -- --- Catalin-Constantin ROIBU Forestry engineer, PhD Forestry Faculty of Suceava

...uot;), ? ? ? ? V4 = c(0L, 2L, 1L, 4L, 3L, 2L, 4L, 2L, 0L, 2L, 4L, 3L, ? ? ? ? 5L, 0L, 5L, 4L, 2L, 0L, 4L, 1L), V5 = c(1L, 0L, 1L, 0L, ? ? ? ? 1L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, ? ? ? ? 0L, 1L), V6 = c(775L, 1648L, 303L, 160L, 296L, 272L, ? ? ? ? 72L, 184L, 80L, 232L, 184L, 88L, 160L, 231L, 88L, 224L, ? ? ? ? 232L, 152L, 72L, 256L)), .Names = c("V1", "V2", "V3", ? ? "V4", "V5", "V6"), row.names = c(NA, 20L), class = "data.frame"), ? ? structure(list(V1 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, ? ? 0L,...

Dear All, 1.I have been trying to aggregate my data but I have not been getting it correctly. In the data I want to convert hourly data into daily averages. Here is a sample of the data: Neph_no Date Time Temp_C Pressure_kPa RH 9 2014/03/28 10:00:00 38.4 95.9 29.7 9 2014/03/28 11:00:00 37.8 95.8 29.2 9 2014/03/28 12:00:00 36.7 95.8 35.1 9 2014/03/28 13:00:00 35.4 95.8 38.9 9

...1825, 61.367401123, 57.844799042 )), .Names = c("ptno", "age", "y"), row.names = c(1L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 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), class = "data.frame") library(nlme) grpdat = groupedData(y ~ age | ptno, data = tmpdat, FUN = mean,...

..., 197L, 395L, 85L, 295L, 70L, 18L, 471L,? 218L, 19L, 43L, 280L, 427L, 229L, 5L, 205L, 494L, 393L, 307L,? 465L, 383L, 265L, 103L, 348L, 166L, 58L, 320L, 14L, 107L, 440L,? 24L, 347L, 419L, 135L, 202L, 294L, 173L, 121L, 358L, 51L, 231L,? 118L, 109L, 182L, 219L, 42L, 73L, 435L, 389L, 431L, 81L, 149L,? 388L, 415L, 256L, 312L, 446L, 45L, 162L, 485L, 154L, 55L, 153L,? 137L, 290L, 93L, 40L, 110L, 167L, 315L, 266L, 317L, 314L, 264L,? 277L, 488L, 28L, 354L, 303L, 490L, 192L, 432L, 228L, 222L, 418L,? 323L, 244L, 239L, 193L, 120L, 116L, 148L, 57L, 246L, 300L, 143L,? 208L, 400L, 78L, 273L, 411L, 401L, 476L, 2...

...L, 57L, 74L, 71L, 71L, 77L, 72L, 63L, 77L, 83L, 63L, 68L, 83L, 71L, 81L, 73L, 70L, 81L, 91L, 91L, 78L, 93L, 75L, 71L, 64L, 62L, 51L, 56L, 47L, 51L, 93L, 66L, 74L, 67L, 70L, 66L, 71L, 60L, 71L, 79L, 73L, 96L, 81L, 89L, 54L, 63L, 52L, 48L, 48L, 57L, 69L, 101L, 109L, 89L, 74L, 96L, 97L, 96L, 92L, 84L, 88L, 82L, 76L, 78L, 88L, 76L, 69L, 83L, 84L, 79L, 76L, 62L, 58L, 79L, 83L, 94L, 95L, 113L, 107L, 53L, 45L, 34L, 39L, 42L, 38L, 34L, 41L, 28L, 30L, 36L, 48L, 35L, 28L, 31L, 29L, 45L, 45L, 45L, 48L, 39L, 52L, 43L, 41L, 42L, 44L, 38L, 44L, 24L, 26L, 22L, 12L, 13L, 17L, 20L, 28L, 28L, 32L, 25L, 25L, 35L, 2...

...2, 3, 4, 5, 1, 2, 3, 4, 5), Y = c(1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5), V1 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 45L, 131L, 0L, 0L, 34L, 481L, 1744L), V2 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 88L, 0L, 70L, 101L, 13L, 634L, 0L, 0L, 71L, 640L, 1636L), V3 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 49L, 3L, 113L, 1L, 44L, 167L, 336L, 933L, 0L, 14L, 388L, 1180L, 1709L), V4 = c(0L, 0L, 0L, 0L, 0L, 0L, 3L, 12L, 0L, 0L, 2L, 1L, 36L, 45L, 208L, 7L, 221L, 213L, 371L, 1440L, 26L, 211L...

...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, 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, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 1...

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 <-

...uot;Conductivity", "LithClass"), row.names = c(1L, 2L, 4L, 5L, 6L, 7L, 8L, 12L, 14L, 16L, 17L, 20L, 21L, 23L, 24L, 26L, 27L, 28L, 30L, 31L, 35L, 36L, 37L, 38L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 55L, 56L, 58L, 59L, 61L, 62L, 65L, 66L, 67L, 69L, 71L, 72L, 76L, 78L, 79L, 80L, 88L, 92L, 93L, 94L, 95L, 96L, 97L, 98L, 99L, 100L, 102L, 103L, 104L, 105L, 106L, 107L, 108L, 109L, 112L), class = "data.frame") The data (in the "structure") is removed, but the labels for all LithClass remain. If I then produce a boxplot or some other graphic where LithClass is in...

Folks, I have a data frame with columns 200401, 200402, ..., 201207, 201208. These represent years/months. What would be the best way to sum these columns by year? What about by quarter? Thanks for your time, KW -- [[alternative HTML version deleted]]