search for: 87l

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

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

...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, 27.5, 10.5, 12.25, 14, 32.5, 80, 49.5, 15.25, 13.5, 12.25, 12, 72.5, 68.5, 12, 9.2...

...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, 69L, 69L, 69L...

...1L, 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,...

...est.df Var1 Freq 1 (0,0.05] 68 2 (0.05,0.1] 87 3 (0.1,0.15] 85 4 (0.15,0.2] 72 5 (0.2,0.25] 65 6 (0.25,0.3] 73 7 (0.3,0.35] 74 .... I would prefer a dataframe labelled like this. 0.05 68 0.1 87 How to do? Thanks Wim > dput (test.tab) structure(c(68L, 87L, 85L, 72L, 65L, 73L, 74L, 72L, 77L, 78L, 75L, 74L, 83L, 93L, 89L, 75L, 67L, 59L, 56L, 208L), .Dim = 20L, .Dimnames = structure(list( c("(0,0.05]", "(0.05,0.1]", "(0.1,0.15]", "(0.15,0.2]", "(0.2,0.25]", "(0.25,0.3]", "(0.3,0.3...

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

...9L, -107L, -100L, -98L, -95L, -95L, -95L, -97L, -98L, -121L, -119L, -118L, -121L, -121L, -106L, -116L, -122L, -112L, -125L, -109L, -114L, -118L, -102L, -109L, -101L, -101L, -74L, -78L, -63L, -67L, -75L, -65L, -60L, -62L, -67L, -59L, -62L, -68L, -61L, -58L, -69L, -57L, -59L, -67L, -73L, -81L, -90L, -87L, -82L, -80L, -80L, -81L, -83L, -90L, -89L, -107L, -122L, -128L, -113L, -124L, -93L, -89L, -92L, -85L, -79L, -84L, -83L, -148L, -142L, -127L, -130L, -123L, -131L, -85L, -87L, -90L, -81L, -65L, -81L, -119L, -121L, -94L, -90L, -117L, -95L, -69L, -122L, -103L, -85L, -106L)), .Names = c("mine"...

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 <-

Hi I've records like this df= x panel 4 1 93 2 21 3 83 4 75 1 87 2 87 3 78 4 50 1 76 2 86 3 65 4 84 1 40 2 39 3 26 4 i want to create histogram out of it . i want all the mid and count values for panel wise my code is histoutput = ddply(df,.(df[2]),hist) i'm not able to get the required result. please help me using for loop takes a lot of time if there are more records ----- Thanks

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

...0L, 44L, 59L, 124L, 145L, 126L, 103L, 67L, 97L, 66L, 76L, 108L, 36L, 48L, 41L, 69L, 47L, 57L, 167L, 136L, 176L, 85L, 36L, 82L, 222L, 149L, 171L, 145L, 122L, 192L, 136L, 164L, 154L, 46L, 57L, 57L, 70L, 55L, 102L, 111L, 152L, 204L, 41L, 46L, 103L, 156L, 148L, 155L, 103L, 124L, 176L, 111L, 142L, 187L, 43L, 52L, 75L, 64L, 91L, 78L, 196L, 314L, 265L, 44L, 39L, 98L, 197L, 273L, 274L, 89L, 91L, 74L, 91L, 112L, 98L, 140L, 90L, 121L, 120L, 161L, 83L, 230L, 266L, 282L, 35L, 53L, 57L, 315L, 332L, 202L, 90L, 79L, 89L, 67L, 116L, 109L, 44L, 68L, 75L, 29L, 52L, 52L, 253L, 203L, 87L, 105L, 234L, 152L,...

...0L, 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, 40L, 97L, 92L, 70L, 50L, 81L, 35L, 70L, 89L, 28L, 28L, 82L, 81L, 33L, 80L, 40L, 40L, 60L, 30L, 5L, 50L, 70L, 75L, 85L, 95L, 93L, 80L, 80L, 60L, 82L, 60L, 5L, 70L, 80L, 40L), gravel = c(8L, 45L, 7L, 5L, 10L, 5L, 35L, 7L, 45L, 60L, 0L, 0L, 5L, 8L, 25L, 0L, 45L, 15L, 0L, 1L, 2L, 5L, 6L, 15L, 10L...

what am I doing wrong? chron(as.character(f), format=c(dates="%m/%d/%y", times="%h:%m")) f <- structure(c(51L, 60L, 66L, 87L, 90L, 115L, 23L, 35L, 37L, 6L, 12L, 55L, 84L, 96L, 109L, 17L, 29L, 41L, 3L, 74L, 94L, 102L, 30L, 8L, 46L, 69L, 107L, 15L, 25L, 39L, 1L, 71L, 95L, 19L, 56L, 62L, 76L, 85L, 99L, 111L, 42L, 4L, 52L, 61L, 67L, 91L, 13L, 24L, 36L, 38L, 7L, 81L, 82L, 57L, 64L, 100L, 113L, 21L, 33L, 44L, 78L, 54L, 73L, 83...

...268901825, 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,...

...136L, 36L, 13L, 35L, 71L, 105L, 113L, 116L, 116L, 94L, 130L, 102L, 19L, 1L, 33L, 78L, 89L, 115L, 130L, 117L, 105L, 0L, 36L, 80L, 130L, 124L, 124L, 66L, 75L, 57L, 94L, 124L, 165L, 170L, 158L, 127L, 116L, 107L, 118L, 150L, 96L, 101L, 59L, 38L, 46L, 77L, 83L, 54L, 61L, 60L, 55L, 110L, 127L, 129L, 87L, 61L, 70L, 85L, 110L, 131L, 151L, 123L, 50L, 77L, 100L, 135L, 151L)), .Names = c("Date", "Score" ), row.names = c(NA, 100L), class = "data.frame") I am trying to write code that will check to see if the score is above a certain point, and then if it is, calculate how...

..., 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, 262L, 159L, 195L, 102L,? 75L, 136L, 402L, 32L, 199L, 286L, 477L, 54L, 429L, 80L, 316L,? 30L, 333L, 387L, 452L, 324L, 456L, 39L, 138L, 113L, 448L, 377L,? 122L, 441L, 396L, 454L, 497L, 161L, 21L, 117L, 413L, 94L, 459L,? 156L, 365L, 322L, 397L, 88L, 207L, 150L, 209L, 184L, 378L, 217L,? 176L, 52L, 374L, 189L, 97L, 340L, 357L, 157L, 220L, 74L, 356L,? 495L, 453L, 26L, 499L, 364L, 267L, 331L, 245L, 258L, 24...

...quot;, "H", "I", "K", "L", "M", "N", "P", "Q", "R", "S", "T", "V", "Y"), class = "factor"), ratio = c(99L, 100L, 100L, 1L, 99L, 100L, 100L, 1L, 98L, 100L, 10L, 87L, 3L, 79L, 9L, 12L, 84L, 99L, 1L, 83L, 13L, 100L, 100L, 100L, 100L, 99L, 100L, 100L, 100L, 98L, 2L, 100L, 100L, 100L, 2L, 98L, 100L, 100L, 1L, 99L, 100L, 100L, 98L, 100L, 95L, 5L, 98L, 2L, 3L, 95L, 1L, 1L, 98L)), .Names = c("position", "residue", "ratio"), class = &quot...

The following reproducable code shows the setting of my problem: set.seed(260808) n = 50 x = rnorm(n) y = rnorm(n) z = ceiling(runif(n,0,4)) g = runif(n,0,6) G = factor(ceiling(g)) xyplot(y ~ x | G) plsy <- trellis.par.get("plot.symbol") plsy$pch = z trellis.par.set("plot.symbol",plsy) xyplot(y ~ x | G) plsy$pch = as.character(z)

...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, 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, 1...