search for: 135l

...uot;ind_1", "ind_1"), date_1st_event = structure(c(14784, 14784, 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 c...

...60L, 432L, 259L, 840L, 8200L, 630L, 180L, 189L, 1490L, 27L, 8080L, 6291L, 240L, 841L, 5469L, 4035L, 12555L, 5320L, 9249L, 240L, 1149L, 40L, 660L, 333L, 4360L, 180L, 360L, 240L, 2900L, 120L, 2639L, 1221L, 10019L, 2990L, 259L, 25L, 320L, 1684L, 305L, 40L, 27L, 4213L, 108L, 222L, 216L, 80L, 148L, 135L, 970L, 222L, 240L, 1332L, 43875L, 210L, 162L, 185L, 180L, 459L, 35854L, 3270L, 162L, 259L, 120L, 9130L, 2120L, 111L, 222L, 595L, 888L, 222L, 189L, 210L, 1740L, 630L, 520L, 120L, 9673L, 160L, 648L, 280L, 378L, 240L, 40L, 444L, 407L, 210L, 185L, 180L, 148L, 110L, 486L, 148L, 756L, 100L, 2750L, 40...

...L, 4L, 3L, 0L, 3L, 2L, 3L, 4L, ? ? ? ? 0L, 3L, 4L, 3L, 2L, 1L, 3L, 0L), V5 = c(1L, 1L, 1L, 1L, ? ? ? ? 0L, 1L, 1L, 2L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, ? ? ? ? 0L, 0L), V6 = c(991L, 312L, 271L, 409L, 176L, 280L, 360L, ? ? ? ? 735L, 248L, 208L, 152L, 167L, 295L, 159L, 393L, 199L, ? ? ? ? 135L, 257L, 151L, 112L)), .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, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,...

...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, 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, 7...

...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 long it stays above that point. I'm not incredibly fami...

..., 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, 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, 418...

...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, 139L, 140L, 141L, 138L, 137L, 136L, 135L, 133L, 134L, 132L, 130L, 131L, 127L, 129L, 128L, 126L, 124L, 125L, 121L, 122L, 123L, 120L, 118L, 119L, 117L, 115L, 116L, 112L, 114L, 113L, 109L, 110L, 111L, 106L, 108L, 107L, 105L, 103L, 104L, 102L, 100L, 101L, 99L, 97L, 98L, 94L, 96L, 95L, 93L, 91L, 92L, 90L, 88L, 89L, 85L, 86L, 87L, 84L, 82L, 83L...

I have data in a file named hands.dat, which is given at the end of this question. (It's from a stats textbook example on anova). I'd like to do an aov on this, which I guess would be d <- read.table("~/hands.dat", header=TRUE) aov(Bacterial.Counts ~ Water + Soap + Antibacterial.Soap + Alcohol.Spray, data=d) but this fails. Do I need to break d$Method up into columns for

...3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L), .Label = c("A", "B", "C", "D", "E", "F", "G"), class = "factor"), total = c(135L, 118L, 121L, 64L, 53L, 49L, 178L, 123L, 128L, 127L, 62L, 129L, 126L, 99L, 183L, 45L, 57L, 45L, 72L, 30L, 71L, 123L, 89L, 102L, 60L, 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, 136...

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

...t;, "DATE", "DOW_NUM", "WEEK"), row.names = c(223L, 235L, 272L, 287L, 330L, 346L, 379L, 395L, 634L, 655L, 683L, 707L, 750L, 761L, 790L, 808L, 837L, 865L, 887L, 923L, 948L, 968L, 1001L, 1017L, 418L, 448L, 476L, 502L, 527L, 554L, 580L, 600L, 16L, 37L, 74L, 95L, 123L, 135L, 176L, 192L, 215L, 236L, 277L, 288L, 331L, 339L, 384L, 391L, 625L, 653L, 684L, 705L, 737L, 755L, 783L, 807L, 834L, 859L, 885L, 915L, 944L, 967L, 993L, 1020L, 417L, 443L, 469L, 501L, 532L, 550L, 577L, 603L, 17L, 36L, 57L, 79L, 107L, 132L, 158L, 183L, 210L, 237L, 269L, 299L, 315L, 348L, 372L, 397...

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

...152L, 166L, 180L, 194L, 208L, 222L, 236L, 250L, 264L, 278L, 292L, 306L, 320L, 334L, 348L, 362L, 376L, 390L, 404L, 418L, 432L, 446L, 460L, 474L, 488L, 502L, 516L, 530L, 544L, 558L, 572L, 586L, 600L, 614L, 628L, 642L, 656L, 670L, 684L, 698L, 712L, 726L, 10L, 24L, 38L, 52L, 66L, 80L, 94L, 108L, 121L, 135L, 149L, 163L, 177L, 191L, 205L, 219L, 233L, 247L, 261L, 275L, 289L, 303L, 317L, 331L, 345L, 359L, 373L, 387L, 401L, 415L, 429L, 443L, 457L, 471L, 485L, 499L, 513L, 527L, 541L, 555L, 569L, 583L, 597L, 611L, 625L, 639L, 653L, 667L, 681L, 695L, 709L, 723L, 6L, 20L, 34L, 48L, 62L, 76L, 90L, 104L, 118L,...

...94L, 208L, 222L, 236L, 250L, 264L, 278L, > 292L, 306L, 320L, 334L, 348L, 362L, 376L, 390L, 404L, 418L, 432L, > 446L, 460L, 474L, 488L, 502L, 516L, 530L, 544L, 558L, 572L, 586L, > 600L, 614L, 628L, 642L, 656L, 670L, 684L, 698L, 712L, 726L, 10L, > 24L, 38L, 52L, 66L, 80L, 94L, 108L, 121L, 135L, 149L, 163L, 177L, > 191L, 205L, 219L, 233L, 247L, 261L, 275L, 289L, 303L, 317L, 331L, > 345L, 359L, 373L, 387L, 401L, 415L, 429L, 443L, 457L, 471L, 485L, > 499L, 513L, 527L, 541L, 555L, 569L, 583L, 597L, 611L, 625L, 639L, > 653L, 667L, 681L, 695L, 709L, 723L, 6L, 20L, 34L, 48L, 62L, 76...

...L, 250L, 264L, 278L, > > 292L, 306L, 320L, 334L, 348L, 362L, 376L, 390L, 404L, 418L, 432L, > > 446L, 460L, 474L, 488L, 502L, 516L, 530L, 544L, 558L, 572L, 586L, > > 600L, 614L, 628L, 642L, 656L, 670L, 684L, 698L, 712L, 726L, 10L, > > 24L, 38L, 52L, 66L, 80L, 94L, 108L, 121L, 135L, 149L, 163L, 177L, > > 191L, 205L, 219L, 233L, 247L, 261L, 275L, 289L, 303L, 317L, 331L, > > 345L, 359L, 373L, 387L, 401L, 415L, 429L, 443L, 457L, 471L, 485L, > > 499L, 513L, 527L, 541L, 555L, 569L, 583L, 597L, 611L, 625L, 639L, > > 653L, 667L, 681L, 695L, 709L, 723L, 6L, 20...

...15L, 16L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 63L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 73L, 74L, 75L, 76L, 77L, 95L, 96L, 97L, 98L, 99L, 100L, 101L, 102L, 103L, 104L, 105L, 106L, 107L, 108L, 109L, 110L, 127L, 128L, 129L, 130L, 131L, 132L, 133L, 134L, 135L, 136L, 137L, 138L, 139L, 140L, 141L, 159L, 160L, 161L, 162L, 163L, 164L, 165L, 166L, 167L, 168L, 169L, 170L, 171L, 172L, 173L, 174L ), class = c("nfnGroupedData", "nfGroupedData", "groupedData", "data.frame"), formula = Prop ~ end | temp, FUN = function (x) m...

...L, 492L, 151L, 126L, 153L, 174L, 179L, 203L, 182L, 132L, 131L, 115L, 149L, 169L, 177L, 171L, 193L, 223L, 243L, 284L, 271L, 282L, 303L, 380L, 442L, 433L, 379L, 463L, 454L, 69L, 80L, 77L, 87L, 101L, 139L, 132L, 138L, 75L, 66L, 83L, 110L, 135L, 136L, 137L, 139L, 94L, 481L, 476L, 509L, 57L, 509L, 500L, 249L, 307L, 279L, 262L, 281L, 181L, 223L, 232L, 218L, 252L, 301L, 328L, 363L, 422L, 485L, 11L, 37L, 24L, 23L, 35L, 50L, 40L, 41L, 44L, 53L, 190L, 158L, 141L, 142L, 164L, 205L,...

Dear R user I want to create a table (as below) to summarize the attached data (Test.csv, which can be read into R by using 'read.csv(Test.csv, header=F)' ), to indicate the day that there are any data available, e.g.value=1 if there are any data available for that day, otherwise value=0. 28/04 29/04 30/04 01/05 02/05 532703 0 1 1

Man, R has a steep learning curve (but I suppose you all know this). I have very little programming knowledge, so when I search for answers to my questions, I struggle with making sense of a lot of the pages. I have a spreadsheet that I've read into R using read.csv. I've also attached it. It looks like this (except there are 1600+ entries): > Sunday SunDate SunTime

...????????????????????303L, >380L, 442L, 433L, 379L, 463L, 454L, 69L, 80L, 77L,? > >???????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????87L, >101L, 139L, 132L, 138L, 75L, 66L, 83L, 110L, 135L, 136L,? > >???????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????137L, >139L, 94L, 481L, 476L, 509L, 57L, 509L, 500L, 249L,? > >???????????????????????????????????????????????????????...