below is my data frame. I would like to compute summary statistics for mgl for each river mile (mean, median, mode). My apologies in advance- I would like to get something like the SAS print out of PROC Univariate. I have performed an ANOVA and a tukey LSD and I would just like the summary statistics. thanks stephen RM mgl 1 215 0.9285714 2 215 0.7352941 3 215 1.6455696 4 215 0.6000000 5 sc 1.8333333 6 sc 0.8333333 7 sc 2.5438596 8 sc 0.2500000 9 202 NA 10 202 0.5500000 11 202 0.8148148 12 202 1.6666667 13 198 0.5038760 14 198 0.3823529 15 198 0.7600000 16 198 0.4800000 17 hc 3.1818182 18 hc 3.7254902 19 hc 4.3750000 20 hc 2.6415094 21 190 0.3500000 22 190 0.4400000 23 190 0.6500000 24 190 0.5000000 25 bc 9.0000000 26 bc 5.0000000 27 bc 4.0000000 28 bc 3.2000000 29 185 0.7386364 30 185 0.5000000 31 185 1.1538462 32 185 0.6000000 33 179 1.8181818 34 179 1.1980000 35 179 2.5000000 36 179 2.0000000 37 148 2.0833333 38 148 2.3333333 39 148 3.1000000 40 148 2.2142857 41 119 2.4444444 42 119 2.3275862 43 119 4.7142857 44 119 1.7692308 45 61 2.8888889 46 61 3.2500000 47 61 4.7500000 48 61 2.6337449 -- Let's not spend our time and resources thinking about things that are so little or so large that all they really do for us is puff us up and make us feel like gods. We are mammals, and have not exhausted the annoying little problems of being mammals. -K. Mullis
Here is one way of doing it: (no exactly sure if 'mode' makes sense with your data)> x <- read.table(textConnection("RM mgl+ 1 215 0.9285714 + 2 215 0.7352941 + 3 215 1.6455696 + 4 215 0.6000000 + 5 sc 1.8333333 + 6 sc 0.8333333 + 7 sc 2.5438596 + 8 sc 0.2500000 + 9 202 NA + 10 202 0.5500000 + 11 202 0.8148148 + 12 202 1.6666667 + 13 198 0.5038760 + 14 198 0.3823529 + 15 198 0.7600000 + 16 198 0.4800000 + 17 hc 3.1818182 + 18 hc 3.7254902 + 19 hc 4.3750000 + 20 hc 2.6415094 + 21 190 0.3500000 + 22 190 0.4400000 + 23 190 0.6500000 + 24 190 0.5000000 + 25 bc 9.0000000 + 26 bc 5.0000000 + 27 bc 4.0000000 + 28 bc 3.2000000 + 29 185 0.7386364 + 30 185 0.5000000 + 31 185 1.1538462 + 32 185 0.6000000 + 33 179 1.8181818 + 34 179 1.1980000 + 35 179 2.5000000 + 36 179 2.0000000 + 37 148 2.0833333 + 38 148 2.3333333 + 39 148 3.1000000 + 40 148 2.2142857 + 41 119 2.4444444 + 42 119 2.3275862 + 43 119 4.7142857 + 44 119 1.7692308 + 45 61 2.8888889 + 46 61 3.2500000 + 47 61 4.7500000 + 48 61 2.6337449"), header=TRUE)> # compute the stats > x.stats <- by(x, x$RM, function(.rm){+ c(mean=mean(.rm$mgl, na.rm=TRUE), median=median(.rm$mgl, na.rm=TRUE)) + })> do.call(rbind, x.stats)mean median 119 2.8138868 2.3860153 148 2.4327381 2.2738095 179 1.8790455 1.9090909 185 0.7481206 0.6693182 190 0.4850000 0.4700000 198 0.5315572 0.4919380 202 1.0104938 0.8148148 215 0.9773588 0.8319327 61 3.3806584 3.0694444 bc 5.3000000 4.5000000 hc 3.4809545 3.4536542 sc 1.3651316 1.3333333> >On Feb 12, 2008 11:57 AM, stephen sefick <ssefick at gmail.com> wrote:> below is my data frame. I would like to compute summary statistics > for mgl for each river mile (mean, median, mode). My apologies in > advance- I would like to get something like the SAS print out of PROC > Univariate. I have performed an ANOVA and a tukey LSD and I would > just like the summary statistics. > thanks > > stephen > > RM mgl > 1 215 0.9285714 > 2 215 0.7352941 > 3 215 1.6455696 > 4 215 0.6000000 > 5 sc 1.8333333 > 6 sc 0.8333333 > 7 sc 2.5438596 > 8 sc 0.2500000 > 9 202 NA > 10 202 0.5500000 > 11 202 0.8148148 > 12 202 1.6666667 > 13 198 0.5038760 > 14 198 0.3823529 > 15 198 0.7600000 > 16 198 0.4800000 > 17 hc 3.1818182 > 18 hc 3.7254902 > 19 hc 4.3750000 > 20 hc 2.6415094 > 21 190 0.3500000 > 22 190 0.4400000 > 23 190 0.6500000 > 24 190 0.5000000 > 25 bc 9.0000000 > 26 bc 5.0000000 > 27 bc 4.0000000 > 28 bc 3.2000000 > 29 185 0.7386364 > 30 185 0.5000000 > 31 185 1.1538462 > 32 185 0.6000000 > 33 179 1.8181818 > 34 179 1.1980000 > 35 179 2.5000000 > 36 179 2.0000000 > 37 148 2.0833333 > 38 148 2.3333333 > 39 148 3.1000000 > 40 148 2.2142857 > 41 119 2.4444444 > 42 119 2.3275862 > 43 119 4.7142857 > 44 119 1.7692308 > 45 61 2.8888889 > 46 61 3.2500000 > 47 61 4.7500000 > 48 61 2.6337449 > > > -- > Let's not spend our time and resources thinking about things that are > so little or so large that all they really do for us is puff us up and > make us feel like gods. We are mammals, and have not exhausted the > annoying little problems of being mammals. > > -K. Mullis > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >-- Jim Holtman Cincinnati, OH +1 513 646 9390 What is the problem you are trying to solve?
Hi Stephen, Try tapply(DATA$mgl,DATA$RM,summary) # DATA is a data.frame I hope this helps. Jorge On 2/12/08, stephen sefick <ssefick@gmail.com> wrote:> > below is my data frame. I would like to compute summary statistics > for mgl for each river mile (mean, median, mode). My apologies in > advance- I would like to get something like the SAS print out of PROC > Univariate. I have performed an ANOVA and a tukey LSD and I would > just like the summary statistics. > thanks > > stephen > > RM mgl > 1 215 0.9285714 > 2 215 0.7352941 > 3 215 1.6455696 > 4 215 0.6000000 > 5 sc 1.8333333 > 6 sc 0.8333333 > 7 sc 2.5438596 > 8 sc 0.2500000 > 9 202 NA > 10 202 0.5500000 > 11 202 0.8148148 > 12 202 1.6666667 > 13 198 0.5038760 > 14 198 0.3823529 > 15 198 0.7600000 > 16 198 0.4800000 > 17 hc 3.1818182 > 18 hc 3.7254902 > 19 hc 4.3750000 > 20 hc 2.6415094 > 21 190 0.3500000 > 22 190 0.4400000 > 23 190 0.6500000 > 24 190 0.5000000 > 25 bc 9.0000000 > 26 bc 5.0000000 > 27 bc 4.0000000 > 28 bc 3.2000000 > 29 185 0.7386364 > 30 185 0.5000000 > 31 185 1.1538462 > 32 185 0.6000000 > 33 179 1.8181818 > 34 179 1.1980000 > 35 179 2.5000000 > 36 179 2.0000000 > 37 148 2.0833333 > 38 148 2.3333333 > 39 148 3.1000000 > 40 148 2.2142857 > 41 119 2.4444444 > 42 119 2.3275862 > 43 119 4.7142857 > 44 119 1.7692308 > 45 61 2.8888889 > 46 61 3.2500000 > 47 61 4.7500000 > 48 61 2.6337449 > > > -- > Let's not spend our time and resources thinking about things that are > so little or so large that all they really do for us is puff us up and > make us feel like gods. We are mammals, and have not exhausted the > annoying little problems of being mammals. > > -K. Mullis > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >[[alternative HTML version deleted]]
Mode <- function(var)rownames(table(var))[which.max(table(var))]
as.data.frame(sapply(c("mean", "median", "Mode"),
function(fun)tapply(x$mgl, x$RM, fun, na.rm=T)))
On 12/02/2008, stephen sefick <ssefick at gmail.com>
wrote:> below is my data frame. I would like to compute summary statistics
> for mgl for each river mile (mean, median, mode). My apologies in
> advance- I would like to get something like the SAS print out of PROC
> Univariate. I have performed an ANOVA and a tukey LSD and I would
> just like the summary statistics.
> thanks
>
> stephen
>
> RM mgl
> 1 215 0.9285714
> 2 215 0.7352941
> 3 215 1.6455696
> 4 215 0.6000000
> 5 sc 1.8333333
> 6 sc 0.8333333
> 7 sc 2.5438596
> 8 sc 0.2500000
> 9 202 NA
> 10 202 0.5500000
> 11 202 0.8148148
> 12 202 1.6666667
> 13 198 0.5038760
> 14 198 0.3823529
> 15 198 0.7600000
> 16 198 0.4800000
> 17 hc 3.1818182
> 18 hc 3.7254902
> 19 hc 4.3750000
> 20 hc 2.6415094
> 21 190 0.3500000
> 22 190 0.4400000
> 23 190 0.6500000
> 24 190 0.5000000
> 25 bc 9.0000000
> 26 bc 5.0000000
> 27 bc 4.0000000
> 28 bc 3.2000000
> 29 185 0.7386364
> 30 185 0.5000000
> 31 185 1.1538462
> 32 185 0.6000000
> 33 179 1.8181818
> 34 179 1.1980000
> 35 179 2.5000000
> 36 179 2.0000000
> 37 148 2.0833333
> 38 148 2.3333333
> 39 148 3.1000000
> 40 148 2.2142857
> 41 119 2.4444444
> 42 119 2.3275862
> 43 119 4.7142857
> 44 119 1.7692308
> 45 61 2.8888889
> 46 61 3.2500000
> 47 61 4.7500000
> 48 61 2.6337449
>
>
> --
> Let's not spend our time and resources thinking about things that are
> so little or so large that all they really do for us is puff us up and
> make us feel like gods. We are mammals, and have not exhausted the
> annoying little problems of being mammals.
>
> -K. Mullis
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
--
Henrique Dallazuanna
Curitiba-Paran?-Brasil
25? 25' 40" S 49? 16' 22" O
stephen sefick wrote:> below is my data frame. I would like to compute summary statistics > for mgl for each river mile (mean, median, mode). My apologies in > advance- I would like to get something like the SAS print out of PROC > Univariate. I have performed an ANOVA and a tukey LSD and I would > just like the summary statistics.Hi Stephen, Have a look at "describe" in the prettyR package. You can specify the summary stats that you want, and the formatting may suit you. Jim