You were caught by a mysterious issue that I don’t understand either. plot(therapy.df$Region[therapy.df$sample==50],therapy.df$factor.a[therapy.df$sample==50],col=4,type=“l”,xlab=“Region”,ylab=“factor") Error: unexpected input in "plot(therapy.df$Region[therapy.df$sample==50],therapy.df$factor.a[therapy.df$sample==50],col=4,type=‚”
but if I change the order of arguments to plot(), it’s fine plot(therapy.df$Region[therapy.df$sample==50],therapy.df$factor.a[therapy.df$sample==50],type="l",col=4,xlab="Region",ylab="factor”) I don’t know what to tell you. If someone wiser than I is still reading, maybe s(he) can explain. Possibly a bug has crept into the call to “par”, but “bugs" suspected by non-experts like me usually turn out to be naive user errors. For your purposes, use the one that works. :-) > On Jun 10, 2015, at 11:03 AM, Rosa Oliveira <rosit...@gmail.com> wrote: > > Sorry, > > I taught I attached the cvs file :) > > <therapy.csv> > > > Don, > > I tried, but I got an error: > > > my.data$Region > [1] 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 > 5 6 7 8 9 10 > > my.data$sample > [1] 50 50 50 50 50 50 50 50 50 50 250 250 250 250 > 250 250 250 250 250 250 1000 1000 1000 1000 1000 1000 1000 1000 > [29] 1000 1000 > > my.data$factor.a > [1] 0.895 0.811 0.685 0.777 0.600 0.466 0.446 0.392 0.256 0.198 0.136 0.121 > 0.875 0.777 0.685 0.626 0.550 0.466 0.384 0.330 0.060 0.138 0.065 > [24] 0.034 0.931 0.124 0.060 0.028 0.017 0.014 > > > > plot(my.data$Region[my.data$sample==50],my.data$factor.a[my.data$sample==50],col=4,type=“l”,xlab=“Region”,ylab=“factor") > Error: unexpected input in > "plot(my.data$Region[my.data$sample==50],my.data$factor.a[my.data$sample==50],col=4,type=�” > > > I’m really naive, right? > > > Best, > RO > > > Atenciosamente, > Rosa Oliveira > > -- > ____________________________________________________________________________ > > <smile.jpg> > > Rosa Celeste dos Santos Oliveira, > > E-mail: rosit...@gmail.com <mailto:rosit...@gmail.com> > Tlm: +351 939355143 > Linkedin: https://pt.linkedin.com/in/rosacsoliveira > <https://pt.linkedin.com/in/rosacsoliveira> > ____________________________________________________________________________ > "Many admire, few know" > Hippocrates > >> On 10 Jun 2015, at 18:10, Don McKenzie <d...@u.washington.edu >> <mailto:d...@u.washington.edu>> wrote: >> >> For a legend, try (untested) >> >> legend(0.15,0.9,c("factora","factorb","factorc"),col=c(4,2,3),lty=1) >> >> If it overlaps data points move the first two arguments (0.15 and 0.9) >> around, or change the “ylim” argument in the plot() to ~1.2. >> >> to avoid clutter, put the line-types information in the figure caption (IMO) >> >> >>> On Jun 10, 2015, at 10:03 AM, Don McKenzie <d...@u.washington.edu >>> <mailto:d...@u.washington.edu>> wrote: >>> >>> >>>> On Jun 10, 2015, at 9:08 AM, Rosa Oliveira <rosit...@gmail.com >>>> <mailto:rosit...@gmail.com>> wrote: >>>> >>>> Dear All, >>>> >>>> >>>> I attach my data. >>>> >>>> Dear Jim, >>>> >>>> when I run your code (even the one you send me, not in my data), I get: >>>> >>>> Don't know how to automatically pick scale for object of type function. >>>> Defaulting to continuous >>>> Error in data.frame(x = c(0.1, 0.2, 0.1, 0.2, 0.1, 0.2, 0.1, 0.2, 0.1, : >>>> arguments imply differing number of rows: 24, 0 >>>> >>>> >>>> >>>> Dear Don, >>>> >>>> It’s meant that I will have 12 lines: >>>> 3 factors - lines colors >>>> with 3 different values of “sample” for each - line types >>>> >>>> >>>> [Three colors, one for each factor, >>>> and three line types (lty=1,2,3), one for eachvalue of “sample - >>>> preferable dash, thin and thick). >>>> >>>> >>>> in the X - I should have region (because I have 10 regions) >>>> for each region I have the outcome of 3 different treatments (factor) >>>> for each region and each treatment I have 3 different sample size. >>> >>> But in your original post you had 4 sample sizes: 10,20,30,40. >>>> >>>> I need to “see” the the influence of the region in the treatment outcome >>>> for each sample size. >>>> >>>> So, at the end I should have 9 lines >>>> 3 red (1 dash, 1 thin, 1 thick) - concerning factor a (dash for sample >>>> size 50, thin for sample size 250 and thick for sample size 1000) >>>> 3 blue (1 dash, 1 thin, 1 thick) - concerning factor b (dash for sample >>>> size 50, thin for sample size 250 and thick for sample size 1000) >>>> 3 green (1 dash, 1 thin, 1 thick) - concerning factor c (dash for sample >>>> size 50, thin for sample size 250 and thick for sample size 1000) >>>> >>>> >>>> >>>> Hope this time is clear. >>>> >>>> >>>> I also though about doing 3 different graphs, each one for 1 different >>>> sample size, and in that case I should have 3 graphs each one with 3 lines >>>> 1 red to factor a, 1 blue to factor b and 1 green to factor c. >>>> >>>> Do you all think is better? >>> >>> A matter of style perhaps but I would use dotplots because you have only >>> two data points for each “line”. The lines will be misleading. You also >>> could use >>> panel plots, but given your skill set (unless someone wants to spend a fair >>> bit of time with you), it’s probably best to stay as simple as possible. >>> >>> But given your original post (cleaned up) # untested: apologies for any >>> typos >>> >>>> region sample factora factorb >>>> factorc >>>> 0.1 10 0.895 0.903 >>>> 0.378 >>>> 0.2 10 0.811 0.865 >>>> 0.688 >>>> 0.1 20 0.735 0.966 >>>> 0.611 >>>> 0.2 20 0.777 0.732 >>>> 0.653 >>>> 0.1 30 0.600 0.778 >>>> 0.694 >>>> 0.2 30 0.466 174.592 >>>> 0.461 >>>> 0.1 40 0.446 0.432 >>>> 0.693 >>>> 0.2 40 0.392 0.294 >>>> 0.686 >>> >>> >>> plot(my.data$region[my.data$sample==10],my.data$factora[my.data$sample==10],col=4,type=“l”,ylim=c(0,1),xlab=“region”,ylab=“factor") >>> lines(my.data$region[my.data$sample==10],my.data$factorb[my.data$sample==10],col=2) >>> lines(my.data$region[my.data$sample==10],my.data$factorc[my.data$sample==10],col=3) >>> >>> lines(my.data$region[my.data$sample==20],my.data$factora[my.data$sample==20],col=4,lty=2) >>> lines(my.data$region[my.data$sample==20],my.data$factorb[my.data$sample==20],col=2,lty=2) >>> lines(my.data$region[my.data$sample==20],my.data$factorc[my.data$sample==20],col=3,lty=2) >>> >>> # Now do two more groups of 3, changing the parameter “lty” to 3 and then 4 >>> >>> >>> # Look at the syntax and note what changes and what stays constant. Do you >>> see how this works? >>> # there will be what looks like a vertical line where sample = 30 and >>> factorb = 174.592. Do you see why? >>> >>> # then you will need a legend >>> >>>> Nonetheless I can’t do it :( >>>> >>>> best, >>>> RO >>>> >>>> >>>> >>>> Atenciosamente, >>>> Rosa Oliveira >>>> >>>> -- >>>> ____________________________________________________________________________ >>>> >>>> <smile.jpg> >>>> Rosa Celeste dos Santos Oliveira, >>>> >>>> E-mail: rosit...@gmail.com <mailto:rosit...@gmail.com> >>>> Tlm: +351 939355143 >>>> Linkedin: https://pt.linkedin.com/in/rosacsoliveira >>>> <https://pt.linkedin.com/in/rosacsoliveira> >>>> ____________________________________________________________________________ >>>> "Many admire, few know" >>>> Hippocrates >>>> >>>>> On 10 Jun 2015, at 14:13, John Kane <jrkrid...@inbox.com >>>>> <mailto:jrkrid...@inbox.com>> wrote: >>>>> >>>>> Hi Jim, >>>>> >>>>> I was looking at that last night and had the same problem of visualizing >>>>> what Rosa needed. >>>>> >>>>> Hi Rosa >>>>> This is nothing like what you wanted and I really don't understand your >>>>> data but would something like this work as a substitute or am I >>>>> completely lost? >>>>> >>>>> >>>>> dat1 <- structure(list(region = c(0.1, 0.2, 0.1, 0.2, 0.1, 0.2, 0.1, >>>>> 0.2), sample = c(10L, 10L, 20L, 20L, 30L, 30L, 40L, 40L), factora = >>>>> c(0.895, >>>>> 0.811, 0.735, 0.777, 0.6, 0.466, 0.446, 0.392), factorb = c(0.903, >>>>> 0.865, 0.966, 0.732, 0.778, 0.592, 0.432, 0.294), factorc = c(0.37, >>>>> 0.688, 0.611, 0.653, 0.694, 0.461, 0.693, 0.686)), .Names = c("region", >>>>> "sample", "factora", "factorb", "factorc"), class = "data.frame", >>>>> row.names = c(NA, >>>>> -8L)) >>>>> >>>>> >>>>> mdat1 <- melt(dat1, id.var = c("region", "sample"), >>>>> variable.name = "factor", >>>>> value.name = "value") >>>>> str(mdat1) >>>>> >>>>> ggplot(mdat1, aes(region, value, colour = factor)) + >>>>> geom_line() + facet_grid(sample ~ .) >>>>> >>>>> John Kane >>>>> Kingston ON Canada >>>>> >>>>> >>>>>> -----Original Message----- >>>>>> From: drjimle...@gmail.com <mailto:drjimle...@gmail.com> >>>>>> Sent: Wed, 10 Jun 2015 20:51:52 +1000 >>>>>> To: rosit...@gmail.com <mailto:rosit...@gmail.com> >>>>>> Subject: Re: [R] graphs, need urgent help (deadline :( ) >>>>>> >>>>>> Hi Rosa, >>>>>> Like Don, I can't work out what you want and I don't even have the >>>>>> picture. For example, your specification of color and line type leaves >>>>>> only one point for each color and line type, and the line from one >>>>>> point to the same point is not going to show up. Here is a possibility >>>>>> that may lead (eventually) to a solution. >>>>>> >>>>>> library(plotrix) >>>>>> par(tcl=-0.1) >>>>>> gap.plot(x=rep(seq(10,45,by=5),3), >>>>>> y=unlist(my.data[,c("factora","factorb","factorc")]), >>>>>> main="A plot of factorial mystery", >>>>>> gap=c(1.1,174),ylim=c(0,175),ylab="factor score",xlab="Group", >>>>>> xticlab=c(" \n0.1\n10"," \n0.2\n10"," \n0.1\n20"," \n0.2\n20", >>>>>> " \n0.1\n30"," \n0.2\n30"," \n0.1\n40"," \n0.2\n40"), >>>>>> ytics=c(0,0.5,1,174.59),pch=rep(1:3,each=8),col=rep(c(4,2,3),each=8)) >>>>>> mtext(c("Region","Sample"),side=1,at=6,line=c(0,1)) >>>>>> lines(seq(10,45,by=5),my.data$factora,col=4) >>>>>> lines(seq(10,45,by=5),my.data$factorb[c(1:5,NA,7,8)],col=2) >>>>>> lines(seq(10,45,by=5),my.data$factorc,col=3) >>>>>> >>>>>> Jim >>>>>> >>>>>> >>>>>> On Wed, Jun 10, 2015 at 10:53 AM, Rosa Oliveira <rosit...@gmail.com >>>>>> <mailto:rosit...@gmail.com>> >>>>>> wrote: >>>>>>> Dear Don and all, >>>>>>> >>>>>>> I’ve read the tutorial and tried several codes before posting :) >>>>>>> I’m really naive. >>>>>>> >>>>>>> >>>>>>> >>>>>>> what I was trying to : is something like the graph in the picture I >>>>>>> drawee. >>>>>>> >>>>>>> >>>>>>> >>>>>>> >>>>>>> Is it more clear now? >>>>>>> >>>>>>> Atenciosamente, >>>>>>> Rosa Oliveira >>>>>>> >>>>>>> -- >>>>>>> ____________________________________________________________________________ >>>>>>> >>>>>>> >>>>>>> Rosa Celeste dos Santos Oliveira, >>>>>>> >>>>>>> E-mail: rosit...@gmail.com <mailto:rosit...@gmail.com> >>>>>>> <mailto:rosit...@gmail.com <mailto:rosit...@gmail.com>> >>>>>>> Tlm: +351 939355143 >>>>>>> Linkedin: https://pt.linkedin.com/in/rosacsoliveira >>>>>>> <https://pt.linkedin.com/in/rosacsoliveira> >>>>>>> <https://pt.linkedin.com/in/rosacsoliveira >>>>>>> <https://pt.linkedin.com/in/rosacsoliveira>> >>>>>>> ____________________________________________________________________________ >>>>>>> "Many admire, few know" >>>>>>> Hippocrates >>>>>>> >>>>>>>> On 09 Jun 2015, at 19:23, Don McKenzie <d...@u.washington.edu >>>>>>>> <mailto:d...@u.washington.edu> >>>>>>>> <mailto:d...@u.washington.edu <mailto:d...@u.washington.edu>>> wrote: >>>>>>>> >>>>>>>> The answer lies in learning to use the help (and knowing where to >>>>>>>> start). Did you look at the tutorial that comes with the R >>>>>>>> installation? >>>>>>>> >>>>>>>> ?plot >>>>>>>> ?lines >>>>>>>> >>>>>>>> ?par >>>>>>>> >>>>>>>> In the last, look for the descriptions of “col” and “lty”. >>>>>>>> >>>>>>>> Using plot() and lines(), and subsetting the four unique values of >>>>>>>> “sample”, you can create your lines. >>>>>>>> >>>>>>>> Here is a crude start, assuming your columns are part of a data frame >>>>>>>> called “my.data”. Untested... >>>>>>>> >>>>> plot(my.data$region[my.data$sample==10],my.data$factora[my.data$sample==10],col=4) >>>>>>>> # blue line, not dashed >>>>>>>> . >>>>>>>> . >>>>>>>> . >>>>> lines(my.data$region[my.data$sample==20],my.data$factorb[my.data$sample==20],col=2,lty=2) >>>>>>>> # red dashed line >>>>>>>> >>>>>>>> >>>>>>>>> On Jun 9, 2015, at 10:36 AM, Rosa Oliveira <rosit...@gmail.com >>>>>>>>> <mailto:rosit...@gmail.com> >>>>>>>>> <mailto:rosit...@gmail.com <mailto:rosit...@gmail.com>>> wrote: >>>>>>>>> >>>>>>>>> Hi, >>>>>>>>> >>>>>>>>> another naive question (i’m pretty sure :( ) >>>>>>>>> >>>>>>>>> >>>>>>>>> I’m trying to plot a multiple line graph: >>>>>>>>> >>>>>>>>> region sample factora factorb >>>>>>>>> factorc >>>>>>>>> 0.1 10 0.895 0.903 0.378 >>>>>>>>> 0.2 10 0.811 0.865 0.688 >>>>>>>>> 0.1 20 0.735 0.966 0.611 >>>>>>>>> 0.2 20 0.777 0.732 0.653 >>>>>>>>> 0.1 30 0.600 0.778 0.694 >>>>>>>>> 0.2 30 0.466 174.592 0.461 >>>>>>>>> 0.1 40 0.446 0.432 0.693 >>>>>>>>> 0.2 40 0.392 0.294 0.686 >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> The first column should be the independent variable, the second should >>>>>>>>> compute a bold line for sample(10) and dash line for sample 20. >>>>>>>> >>>>>>>> What about the other two values of “sample”? >>>>>>>> >>>>>>>>> The others variables are outcomes for each of the first scenarios, and >>>>>>>>> so it should: the 3rd, 4th and 5th columns should be blue, red and >>>>>>>>> green respectively. >>>>>>>>> >>>>>>>>> >>>>>>>>> Resume :) >>>>>>>>> >>>>>>>>> I should have a graph, in the x-axe should have the region and in the >>>>>>>>> y axe, the factor. >>>>>>>>> Lines: >>>>>>>>> 1 - blue and bold for region 0.1, sample 10 and factor a >>>>>>>>> 2 - blue and dash for region 0.2, sample 10 and factor a >>>>>>>>> 3 - red and bold for region 0.1, sample 10 and factor b >>>>>>>>> 4 - red and dash for region 0.2, sample 10 and factor b >>>>>>>>> 5 - green and bold for region 0.1, sample 10 and factor c >>>>>>>>> 6 - green and dash for region 0.2, sample 10 and factor c >>>>>>>> >>>>>>>> Not consistent with what you said above. These are no longer lines, but >>>>>>>> points. >>>>>>>>> >>>>>>>>> nonetheless the independent variable is nominal, I should plot a line >>>>>>>>> graph. >>>>>>>>> >>>>>>>>> Can anyone help me please? >>>>>>>>> I have my file as a cvs file, so I first read that file (that I know >>>>>>>>> how to do :)). >>>>>>>>> >>>>>>>>> But I have it in that format. >>>>>>>>> >>>>>>>>> Best, >>>>>>>>> RO >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> Atenciosamente, >>>>>>>>> Rosa Oliveira >>>>>>>>> >>>>>>>>> -- >>>>>>>>> ____________________________________________________________________________ >>>>>>>>> >>>>>>>>> >>>>>>>>> Rosa Celeste dos Santos Oliveira, >>>>>>>>> >>>>>>>>> E-mail: rosit...@gmail.com <mailto:rosit...@gmail.com> >>>>>>>>> <mailto:rosit...@gmail.com <mailto:rosit...@gmail.com>> >>>>>>>>> Tlm: +351 939355143 >>>>>>>>> Linkedin: https://pt.linkedin.com/in/rosacsoliveira >>>>>>>>> <https://pt.linkedin.com/in/rosacsoliveira> >>>>>>>>> <https://pt.linkedin.com/in/rosacsoliveira >>>>>>>>> <https://pt.linkedin.com/in/rosacsoliveira>> >>>>>>>>> ____________________________________________________________________________ >>>>>>>>> "Many admire, few know" >>>>>>>>> Hippocrates >>>>>>>>> >>>>>>>>> >>>>>>>>> [[alternative HTML version deleted]] >>>>>>>>> >>>>>>>>> ______________________________________________ >>>>>>>>> R-help@r-project.org <mailto:R-help@r-project.org> >>>>>>>>> <mailto:R-help@r-project.org <mailto:R-help@r-project.org>> mailing >>>>>>>>> list -- To >>>>>>>>> UNSUBSCRIBE and more, see >>>>>>>>> https://stat.ethz.ch/mailman/listinfo/r-help >>>>>>>>> <https://stat.ethz.ch/mailman/listinfo/r-help> >>>>>>>>> <https://stat.ethz.ch/mailman/listinfo/r-help >>>>>>>>> <https://stat.ethz.ch/mailman/listinfo/r-help>> >>>>>>>>> PLEASE do read the posting guide >>>>>>>>> http://www.R-project.org/posting-guide.html >>>>>>>>> <http://www.r-project.org/posting-guide.html> >>>>>>>>> <http://www.r-project.org/posting-guide.html >>>>>>>>> <http://www.r-project.org/posting-guide.html>> >>>>>>>>> and provide commented, minimal, self-contained, reproducible code. >>>>>>>> >>>>>>>> <PastedGraphic-1.tiff> >>>>>>>> >>>>>>> >>>>>>> ______________________________________________ >>>>>>> R-help@r-project.org <mailto:R-help@r-project.org> mailing list -- To >>>>>>> UNSUBSCRIBE and more, see >>>>>>> https://stat.ethz.ch/mailman/listinfo/r-help >>>>>>> <https://stat.ethz.ch/mailman/listinfo/r-help> >>>>>>> PLEASE do read the posting guide >>>>>>> http://www.R-project.org/posting-guide.html >>>>>>> <http://www.r-project.org/posting-guide.html> >>>>>>> and provide commented, minimal, self-contained, reproducible code. >>>>>> >>>>>> ______________________________________________ >>>>>> R-help@r-project.org <mailto:R-help@r-project.org> mailing list -- To >>>>>> UNSUBSCRIBE and more, see >>>>>> https://stat.ethz.ch/mailman/listinfo/r-help >>>>>> <https://stat.ethz.ch/mailman/listinfo/r-help> >>>>>> PLEASE do read the posting guide >>>>>> http://www.R-project.org/posting-guide.html >>>>>> <http://www.r-project.org/posting-guide.html> >>>>>> and provide commented, minimal, self-contained, reproducible code. >>>>> >>>>> ____________________________________________________________ >>>>> FREE 3D MARINE AQUARIUM SCREENSAVER - Watch dolphins, sharks & orcas on >>>>> your desktop! >>>>> Check it out at http://www.inbox.com/marineaquarium >>>>> <http://www.inbox.com/marineaquarium> >>>>> >>>>> >>>> >>> >>> <PastedGraphic-1.tiff> >>> >> >> <PastedGraphic-1.tiff> >> > ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
