search for: 190l

...it is ggplot please see the two graphs at the bottom of the page (code). melt.nut <- (structure(list(RiverMile = c(119L, 119L, 119L, 119L, 119L, 119L, 119L, 119L, 119L, 148L, 148L, 148L, 148L, 148L, 148L, 148L, 179L, 179L, 179L, 179L, 179L, 179L, 179L, 185L, 185L, 185L, 185L, 185L, 185L, 185L, 190L, 190L, 190L, 190L, 190L, 190L, 190L, 190L, 190L, 190L, 190L, 198L, 198L, 198L, 198L, 198L, 198L, 198L, 198L, 198L, 198L, 202L, 202L, 202L, 202L, 202L, 202L, 202L, 202L, 202L, 202L, 215L, 215L, 215L, 215L, 215L, 215L, 215L, 215L, 215L, 215L, 215L, 215L, 61L, 61L, 61L, 61L, 61L, 61L, 61L, 61L, 61L, 1...

merge can only merge two objects at a time- I would like to merge more than two objects at a time. s.d <- structure(list(RiverMile = c(202L, 198L, 190L, 185L, 179L, 148L, 119L, 61L)), .Names = "RiverMile", row.names = c(NA, -8L), class = "data.frame") #s.d is all of the river miles that can occur in all of the data frames that I want to put together feb06 <- structure(list(RiverMile = c(202L, 190L, 185L), X2.1.06 = c(28500...

...ere included on different sampling dates. I would like to subset these data and then put them together as a big matrix with the by column being RiverMile. What is the easiest way to proceed as this is a process that will be done on 96+ constituents? feb06 <- structure(list(RiverMile = c(202L, 190L, 185L), X2.1.06 = c(2850000, NA, NA)), .Names = c("RiverMile", "X2.1.06"), row.names = c(29L, 31L, 32L), class = "data.frame") may06 <- structure(list(RiverMile = c(202L, 198L, 190L, 185L, 148L), X5.1.06 = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_)), .Name...

..., 2.470317011, 0.768531626, 2.633107621, 3.113199095, 0.773824094, 3.208461305, 0.680150068, 0.680150068, 0.026385752, 0.369310858, 8.049276658, 7.487378383, 0.950072035, 0.950072035, 0.763580377, 0.333244629, 5.475999014, 9.235631398, 2.587682905), RiverMile = c(148L, 179L, 185L, 202L, 179L, 185L, 190L, 119L, 148L, 179L, 185L, 202L, 215L, 119L, 202L, 198L, 215L, 148L, 198L, 190L, 202L, 215L, 198L, 198L, 215L, 148L, 148L, 202L, 202L, 215L, 119L, 179L, 185L, 190L, 198L, 61L, 61L, 119L, 148L, 202L, 202L, 61L, 61L, 119L, 148L, 185L, 202L, 215L )), .Names = c("TSS", "GPP", "Ri...

...= c(3.117647059, 2.736842105, 2.25, 22, 3, 2.428571429, 6.428571429, NA, NA, 2.384615385, 3, NA, 3.25, NA, 3.166666667, 9, 23, 3.5, 11, 3.916666667, 3.4, 3.444444444, 8.75, 2.733333333, 3.583333333, 2.75, 17, NA, 2.933333333, 2.533333333, 2.5, 11), RiverMile = c(148L, 179L, 185L, 202L, 179L, 185L, 190L, 119L, 148L, 179L, 185L, 202L, 119L, 202L, 148L, 190L, 202L, 148L, 202L, 119L, 179L, 185L, 190L, 61L, 119L, 148L, 202L, 202L, 119L, 148L, 185L, 202L)), .Names = c("GPP", "TSS", "Iron", "TIN.TP", "RiverMile"), class = "data.frame", row.name...

...quot;, "2006/07", "2006/10", "2006/12", "2007/02", "2007/04", "2007/06", "2007/08", "2007/10", "2007/12", "2008/01"), class = "factor"), RiverMile = c(61L, 119L, 148L, 179L, 185L, 187L, 190L, 196L, 198L, 202L, 215L, 61L, 119L, 148L, 179L, 185L, 187L, 190L, 196L, 198L), Site = structure(c(9L, 1L, 2L, 3L, 4L, 10L, 5L, 11L, 6L, 7L, 8L, 9L, 1L, 2L, 3L, 4L, 10L, 5L, 11L, 6L ), .Label = c("119", "148", "179", "185", "190", &qu...

..., 2.470317011, 0.768531626, 2.633107621, 3.113199095, 0.773824094, 3.208461305, 0.680150068, 0.680150068, 0.026385752, 0.369310858, 8.049276658, 7.487378383, 0.950072035, 0.950072035, 0.763580377, 0.333244629, 5.475999014, 9.235631398, 2.587682905), RiverMile = c(148L, 179L, 185L, 202L, 179L, 185L, 190L, 119L, 148L, 179L, 185L, 202L, 215L, 119L, 202L, 198L, 215L, 148L, 198L, 190L, 202L, 215L, 198L, 198L, 215L, 148L, 148L, 202L, 202L, 215L, 119L, 179L, 185L, 190L, 198L, 61L, 61L, 119L, 148L, 202L, 202L, 61L, 61L, 119L, 148L, 185L, 202L, 215L )), .Names = c("TSS", "GPP", "Ri...

...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, 192L, 192L, 192L, 197L, 197L, 197L, 224L, 224L, 224L, 229L, 232L, 232L, 232L, 232L, 232L, 232L, 232L, 249L, 249L), age = c(6.6054794521, 9.301369863, 22.638356164, 31.961670089, 17.15890411, 25.106091718, 8.197260274, 11.295890411, 14.191780822, 22.43394935, 28.6, 6.6794520548, 1...

....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, 660L, 333L, 4360L,...

...20L, 33L, 68L, 62L, 111L, 10L, 149L, 17L, 49L, 164L, 271L, 8L, 60L, 2L, 48L, 127L, 80L, 70L, 13L, 31L, 32L, 3L, 50L, 144L, 25L, 12L, 84L, 80L, 116L, 6L, 49L, 127L, 5L, 56L, 13L, 49L, 39L, 13L, 22L, 24L, 55L, 44L, 92L, 59L, 111L, 10L, 58L, 104L, 3L, 177L, 36L, 38L, 50L, 28L, 190L, 17L, 21L, 2L, 38L, ...... ...... ...... "767", "768", "769", "770", "771", "772", "773", "774", "775", "776", "777", "778", "779", "780", "781", &qu...

...>hackme</source-password> <!-- Relays log in username 'relay' --> <relay-password>hackme</relay-password> <!-- Admin logs in with the username given below --> <admin-user>admin</admin-user> "icecast.xml" 190L, 6848C -------------- next part -------------- An HTML attachment was scrubbed... URL: http://lists.xiph.org/pipermail/icecast/attachments/20110310/85c420ec/attachment.htm

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

...quot;D", "E", "F", "G", "H", "I", "J", "K"), class = "factor"), Yes = c(18L, 2L, 1L, 2L, 44L, 27L, 2L, 15L, 13L, 3L, 34L), No = c(171L, 11L, 5L, 8L, 146L, 80L, 5L, 30L, 22L, 5L, 42L), Num = c(189L, 13L, 6L, 10L, 190L, 107L, 7L, 45L, 35L, 8L, 76L)), .Names = c("Case", "Yes", "No", "Num"), class = "data.frame", row.names = c(NA, -11L)) Thanks in advance Sam

I would appreciate pointers on what I should read to understand this output: summary(lm(TDS ~ Cond + Ca + Cl + Mg + Na + SO4)) Call: lm(formula = TDS ~ Cond + Ca + Cl + Mg + Na + SO4) Residuals: ALL 1 residuals are 0: no residual degrees of freedom! Coefficients: (6 not defined because of singularities) Estimate Std. Error t value Pr(>|t|) (Intercept) 125 NA

...martpink111 at yahoo.com" <smartpink111 at yahoo.com> Sent: Wednesday, February 27, 2013 8:47 AM Subject: RE: matrix multiplication there you go >dput(eliza) structure(c(428L, 359L, 353L, 498L, 169L, 46L, 29L, 444L, 194L,? 439L, 284L, 79L, 226L, 105L, 106L, 326L, 234L, 196L, 417L, 190L,? 480L, 275L, 478L, 341L, 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,...

...241L, 242L, 240L, 238L, 239L, 235L, 236L, 237L, 234L, 232L, 233L, 231L, 229L, 230L, 226L, 228L, 227L, 223L, 225L, 224L, 220L, 221L, 222L, 217L, 219L, 218L, 214L, 216L, 215L, 211L, 212L, 213L, 210L, 208L, 209L, 207L, 205L, 206L, 202L, 204L, 203L, 201L, 199L, 200L, 196L, 197L, 198L, 195L, 193L, 194L, 190L, 192L, 191L, 189L, 187L, 188L, 184L, 185L, 186L, 183L, 181L, 182L, 178L, 180L, 179L, 175L, 177L, 176L, 172L, 174L, 173L, 171L, 169L, 170L, 166L, 168L, 167L, 163L, 165L, 164L, 162L, 160L, 161L, 159L, 157L, 158L, 156L, 154L, 155L, 153L, 151L, 152L, 148L, 150L, 149L, 147L, 145L, 146L, 142L, 143L, 144L...

Hi, I have a data set: > Dataset X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17 1 user1 m 22 19 28 24 12 18 9 7 4 5 4 7 5 7 9 2 user2 f 25 19 23 18 18 15 6 8 6 6 7 10 7 7 7 3 user3 f 28 21 24 18 15 12 10 6 7 9 5 10 5 9 5 4 user4 f 26 19 26 21 12 18 6 6 5 1 3 8 6 5 6 5 user5 m 21 22 26 18 9 6 4 6 1

...ositive"), class = "factor"), value = c(153L, 157L, 151L, 152L, 129L, 129L, 89L, 134L, 129L, 126L, 125L, 106L, 108L, 120L, 148L, 109L, 128L, 123L, 132L, 111L, 142L, 139L, 146L, 156L, 153L, 167L, 123L, 161L, 177L, 178L, 163L, 175L, 140L, 141L, 143L, 217L, 206L, 185L, 192L, 203L, 196L, 190L, 195L, 192L, 217L, 210L, 181L, 197L, 222L, 123L, 168L, 156L, 169L, 178L, 178L, 149L, 181L, 175L, 177L, 168L, 153L, 179L, 139L, 156L, 142L, 115L, 135L, 143L, 164L, 158L, 111L, 119L, 131L, 120L, 160L, 141L, 161L, 123L, 135L, 152L, 135L, 164L, 191L, 183L, 81L, 94L, 74L, 90L, 77L, 62L, 57L, 74L, 71L, 7...

Hi All, this is my first mail here. I'm trying to plot a multiline chart grouping values with no success. I have read a lot in the official Wiki and also searched via Google, but I did not find anything. I'm importing some data from a cvs file. Here is a sample: YEAR,AREA,CASES 1988,CONTRACTS,286 1988,INTERNATIONAL,189 1988,FAMILY,385 1988,TAXATION,177 1989,CONTRACTS,233

...orecast (MyModel, h=12) Since my last observation was on december 31st, 2016 I expected my forecast date to start on 2017, but instead it returned odd dates. This is my dataset dput(dataset): structure(list(Date = structure(c(8L, 22L, 36L, 50L, 64L, 78L, 92L, 106L, 120L, 134L, 148L, 162L, 176L, 190L, 204L, 218L, 232L, 246L, 260L, 274L, 288L, 302L, 316L, 330L, 344L, 358L, 372L, 386L, 400L, 414L, 428L, 442L, 456L, 470L, 484L, 498L, 512L, 526L, 540L, 554L, 568L, 582L, 596L, 610L, 624L, 638L, 652L, 666L, 680L, 694L, 708L, 722L, 5L, 19L, 33L, 47L, 61L, 75L, 89L, 103L, 117L, 130L, 144L, 158L, 172L,...