search for: 75l

...) loc f N color ordered pchloc 98 75 S1 6.39 green 1 16 99 75 S8 6.44 blue 2 16 71 75 S8 6.60 blue 3 16 100 75 R6 6.64 black 4 16 70 75 S1 6.81 green 5 16 51 75 S8 6.83 blue 6 16 > dput(ZZ) structure(list(loc = c(75L, 75L, 75L, 75L, 75L, 75L, 75L, 75L, 56L, 56L, 75L, 75L, 75L, 75L, 75L, 75L, 75L, 56L, 75L, 75L, 56L, 56L, 75L, 75L, 75L, 56L, 75L, 56L, 56L, 75L, 75L, 75L, 75L, 75L, 75L, 56L, 56L, 75L, 75L, 75L, 75L, 56L, 75L, 75L, 75L, 75L, 56L, 56L, 56L, 56L, 75L, 75L, 75L, 75L, 75L, 75L, 75L, 56L, 75L, 56L, 75L...

...uot;, "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, 61L, 61L, 61L, 60L, 60L, 60L, 59L, 59L, 59L, 58L, 58L, 58L, 57L, 57L, 57L...

...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]", "(0.3,0.35]", "(0.35,0.4]", "(0.4,...

...", "Group 3", "Group 4", and "Group 5". I am hoping for a few different techniques 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,...

...50L, 50L, 51L, 51L, 52L, 52L, 53L, 53L, 53L, 54L, 54L, 54L, 54L, 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...

...660, 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, 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,...

...080, 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", "Score"), row.names = c(NA, 50L), class = "data.frame") I'm trying to round the time down to the nearest half hour, without losing the date. Fo...

I would like to organize my data as follows: I have a table that contains various data, and the numbers represent a level of similarity between these data, eg RF00013 has 100% similarity with the data RF00014. I would leave my table as a heatmap where darker colors represent higher similarity, and the lighter colors represent less level of similarity. I'm using version 2.11 of R. these

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

Good Afternoon, I'm trying to create a graph that displays the best way the following information. ??? For instance organized by bar graph, A, B, C Source X1000s X600s X500s X250s X100s X50s X10s X5s X3s X1s 1 A 47 63 75 116 125 129 131 131 131 131 2 B 37 64 45 11 25 19 61 131 186 186 3 C 17 62 25 66 12 29 91 171 186

...expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call)[1L] prefix <- paste("Error in", dcall, ": ") LONG <- 75L msg <- conditionMessage(e) sm <- strsplit(msg, "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], ty...

...9L, 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, >>>>>>>>&g...

....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, -109L, -114L, -118L, -102L, -109L, -101L, -101L, -74L, -78L, -63L, -67L, -75L, -65L, -60L, -62L, -67L,...

...expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call)[1L] prefix <- paste("Error in", dcall, ": ") LONG <- 75L msg <- conditionMessage(e) sm <- strsplit(msg, "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], ty...

...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, 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, 51...

...expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call)[1L] prefix <- paste("Error in", dcall, ": ") LONG <- 75L msg <- conditionMessage(e) sm <- strsplit(msg, "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], ty...

...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, 247L, 243L, 14...

Hi, I managed to use the attached data set and figure out the following: flies <- read.table("example12_1.dat",header=TRUE,sep="\t") boxplot(long ~ group, data = flies, horizontal = TRUE, col = "red") I'm very new to R and would like some help with the following: 1. Change the order on the y-axis from 1, 2, 3, 4, 5 to 5, 4, 3, 2, 1.

..., 215L, 119L, 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 &lt...

...pr, classes, parentenv, handlers) 7: tryCatch(expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call)[1L] prefix <- paste("Error in", dcall, ": ") LONG <- 75L msg <- conditionMessage(e) sm <- strsplit(msg, "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], type = "b") if (w > LONG) prefix <- paste(...