Wonderful! This is great news. Thanks, Deepayan. On Wed, 12 Jul 2023 at 09:21, Deepayan Sarkar <deepayan.sar...@gmail.com> wrote:
> > > On Wed, 12 Jul 2023 at 08:57, Anupam Tyagi <anupty...@gmail.com> wrote: > >> Thanks. >> I made a graph in Stata that is close to what I want in R. Stata graph is >> attached. The main differences between Stata and R graphs that I was able >> to make, with ggplot or lattice, is that I have been able to scale y-axis >> of each sub-graph independently in Stata, but not in R. Also, x-axis >> labels >> are also complete in Stata but not in R. Is there a way to do this in R >> via >> base-R, ggplot or lattice? > > > Yes, of course. For lattice, add the argument > > scales = list(y = "free") > > For ggplot2, change > > facet_wrap(~Measure) > > to > > facet_wrap(~Measure, scale = "free") > > -Deepayan > > I had initially thought that these types of >> panel graphs are common and should be easy to do, but that is not how this >> is turning out to be. Any help is welcome. >> > >> On Fri, 7 Jul 2023 at 17:57, PIKAL Petr <petr.pi...@precheza.cz> wrote: >> >> > Hallo Anupam >> > >> > With >> > >> > ggplot change axis label size into Google >> > >> > the first answer I got was >> > >> > axis.text theme >> > >> > r - Change size of axes title and labels in ggplot2 - Stack Overflow >> > < >> https://stackoverflow.com/questions/14942681/change-size-of-axes-title-and-labels-in-ggplot2 >> > >> > >> > >> > >> > so >> > >> > >> > >> > ggplot(TrialData4, aes(x=Income, y=Percent, group=Measure)) + >> geom_point() >> > + >> > geom_line() + facet_wrap(~Measure) + >> > theme(axis.text=element_text(size=5)) >> > >> > >> > >> > Should do the trick. >> > >> > >> > >> > S pozdravem | Best Regards >> > >> > >> > *RNDr. Petr PIKAL*Vedoucí Výzkumu a vývoje | Research Manager >> > >> > >> > *PRECHEZA a.s.*nábř. Dr. Edvarda Beneše 1170/24 | 750 02 Přerov | Czech >> > Republic >> > Tel: +420 581 252 256 | GSM: +420 724 008 364 >> > petr.pi...@precheza.cz | *www.precheza.cz <https://www.precheza.cz/>* >> > >> > *Osobní údaje: *Informace o zpracování a ochraně osobních údajů >> > obchodních partnerů PRECHEZA a.s. jsou zveřejněny na: * >> https://www.precheza.cz/zasady-ochrany-osobnich-udaju/ >> > <https://www.precheza.cz/zasady-ochrany-osobnich-udaju/>* | Information >> > about processing and protection of business partner’s personal data are >> > available on website: * >> https://www.precheza.cz/en/personal-data-protection-principles/ >> > <https://www.precheza.cz/en/personal-data-protection-principles/>* >> > >> > *Důvěrnost: *Tento e-mail a jakékoliv k němu připojené dokumenty jsou >> > důvěrné a podléhají tomuto právně závaznému prohlášení o vyloučení >> > odpovědnosti: *https://www.precheza.cz/01-dovetek/ >> > <https://www.precheza.cz/01-dovetek/>* | This email and any documents >> > attached to it may be confidential and are subject to the legally >> binding >> > disclaimer: *https://www.precheza.cz/en/01-disclaimer/ >> > <https://www.precheza.cz/en/01-disclaimer/>* >> > >> > >> > >> > *From:* Anupam Tyagi <anupty...@gmail.com> >> > *Sent:* Friday, July 7, 2023 12:48 PM >> > *To:* PIKAL Petr <petr.pi...@precheza.cz> >> > *Cc:* r-help@r-project.org >> > *Subject:* Re: [R] Plotting factors in graph panel >> > >> > >> > >> > Thanks! You are correct, the graphs look very similar, except ggplot is >> > scaling the text font to make it more readable. Is there a way to scale >> > down the x-axis labels, so they are readable? >> > >> > >> > >> > On Fri, 7 Jul 2023 at 12:02, PIKAL Petr <petr.pi...@precheza.cz> wrote: >> > >> > Hallo Anupam >> > >> > I do not see much difference in ggplot or lattice, they seems to me >> > provide almost identical results when removing theme part from ggplot. >> > >> > library(ggplot2) >> > library(lattice) >> > >> > ggplot(TrialData4, aes(x=Income, y=Percent, group=Measure)) + >> geom_point() >> > + >> > geom_line() + facet_wrap(~Measure) >> > >> > xyplot(Percent ~ Income | Measure, TrialData4, >> > type = "o", pch = 16, as.table = TRUE, grid = TRUE) >> > >> > So it is probably only matter of your preference which one do you >> choose. >> > >> > Cheers >> > Petr >> > >> > >> > > -----Original Message----- >> > > From: R-help <r-help-boun...@r-project.org> On Behalf Of Deepayan >> Sarkar >> > > Sent: Thursday, July 6, 2023 3:06 PM >> > > To: Anupam Tyagi <anupty...@gmail.com> >> > > Cc: r-help@r-project.org >> > > Subject: Re: [R] Plotting factors in graph panel >> > > >> > > On Thu, 6 Jul 2023 at 15:21, Anupam Tyagi <anupty...@gmail.com> >> wrote: >> > > > >> > > > Btw, I think "lattice" graphics will provide a better solution than >> > > > "ggplot", because it puts appropriate (space saving) markers on the >> > > > axes and does axes labels well. However, I cannot figure out how to >> do >> > > > it in "lattice". >> > > >> > > You will need to convert Income to a factor first. Alternatively, use >> > > dotplot() instead of xyplot(), but that will sort the levels wrongly, >> so >> > better to >> > > make the factor first anyway. >> > > >> > > TrialData4 <- within(TrialData4, >> > > { >> > > Income <- factor(Income, levels = c("$10", "$25", "$40", "$75", "> >> > $75")) >> > > }) >> > > >> > > xyplot(Percent ~ Income | Measure, TrialData4, >> > > type = "o", pch = 16, as.table = TRUE, grid = TRUE) >> > > >> > > or >> > > >> > > dotplot(Percent ~ Income | Measure, TrialData4, >> > > type = "o", as.table = TRUE) >> > > >> > > This is not really any different from the ggplot() version though. >> > > Maybe you just don't like the effect of the '+ theme_classic()' part. >> > > >> > > Best, >> > > -Deepayan >> > > >> > > >> > > > On Thu, 6 Jul 2023 at 15:11, Anupam Tyagi <anupty...@gmail.com> >> wrote: >> > > > >> > > > > Hi John: >> > > > > >> > > > > Thanks! Below is the data using your suggestion. I used "ggplot" >> to >> > > > > make a graph. I am not too happy with it. I am looking for >> something >> > > > > simpler and cleaner. Plot is attached. >> > > > > >> > > > > I also tried "lattice" package, but nothing got plotted with >> "xyplot" >> > > > > command, because it is looking for a numeric variable on x-axis. >> > > > > >> > > > > ggplot(TrialData4, aes(x=Income, y=Percent, group=Measure)) + >> > > > > geom_point() >> > > > > + >> > > > > geom_line() + facet_wrap(~Measure) + theme_classic() >> > > > > >> > > > > > dput(TrialData4)structure(list(Income = c("$10", "$25", "$40", >> > > > > > "$75", "> $75", >> > > > > "$10", "$25", "$40", "$75", "> $75", "$10", "$25", "$40", "$75", >> "> >> > > > > $75", "$10", "$25", "$40", "$75", "> $75", "$10", "$25", "$40", >> > > > > "$75", "> $75", "$10", "$25", "$40", "$75", "> $75", "$10", "$25", >> > > > > "$40", "$75", "> $75", "$10", "$25", "$40", "$75", "> $75", "$10", >> > > > > "$25", "$40", "$75", "> $75", "$10", "$25", "$40", "$75", "> $75", >> > > > > "$10", "$25", "$40", "$75", "> $75", "$10", "$25", "$40", "$75", >> "> >> > > > > $75", "$10", "$25", "$40", "$75", "> $75", "$10", "$25", "$40", >> > > > > "$75", "> $75", "$10", "$25", "$40", "$75", "> $75", "$10", "$25", >> > > > > "$40", "$75", "> $75", "$10", "$25", "$40", "$75", "> $75", "$10", >> > > > > "$25", "$40", "$75", "> $75", "$10", "$25", "$40", "$75", "> $75", >> > > > > "$10", "$25", "$40", "$75", "> $75", "$10", "$25", "$40", "$75", >> "> >> > > > > $75", "$10", "$25", "$40", "$75", "> $75", "$10", "$25", "$40", >> > > > > "$75", "> $75", "$10", "$25", "$40", "$75", "> $75", "$10", "$25", >> > > > > "$40", "$75", "> $75", "$10", "$25", "$40", "$75", "> $75", "$10", >> > > > > "$25", "$40", "$75", "> $75", "$10", "$25", "$40", "$75", "> $75" >> > > > > ), Percent = c(3.052, 2.292, 2.244, 1.706, 1.297, 29.76, 28.79, >> > > > > 29.51, 28.9, 31.67, 31.18, 32.64, 34.31, 35.65, 37.59, 36, 36.27, >> > > > > 33.94, 33.74, 29.44, 46.54, 54.01, 59.1, 62.17, 67.67, 24.75, >> 24.4, >> > > > > 25, 24.61, 24.02, 25.4, 18.7, 29, 11.48, 7.103, 3.052, 2.292, >> 2.244, >> > > > > 1.706, 1.297, 29.76, 28.79, 29.51, 28.9, 31.67, 31.18, 32.64, >> 34.31, >> > > > > 35.65, 37.59, 36, 36.27, 33.94, 33.74, 29.44, 46.54, 54.01, 59.1, >> > > > > 62.17, 67.67, 24.75, 24.4, 25, 24.61, 24.02, 25.4, 18.7, 29, >> 11.48, >> > > > > 7.103, 3.052, 2.292, 2.244, 1.706, 1.297, 29.76, 28.79, 29.51, >> 28.9, >> > > > > 31.67, 31.18, 32.64, 34.31, 35.65, 37.59, 36, 36.27, 33.94, 33.74, >> > > > > 29.44, 46.54, 54.01, 59.1, 62.17, 67.67, 24.75, 24.4, 25, 24.61, >> > > > > 24.02, 25.4, 18.7, 29, 11.48, 7.103, 3.052, 2.292, 2.244, 1.706, >> > > > > 1.297, 29.76, 28.79, 29.51, 28.9, 31.67, 31.18, 32.64, 34.31, >> 35.65, >> > > > > 37.59, 36, 36.27, 33.94, 33.74, 29.44, 46.54, 54.01, 59.1, 62.17, >> > > > > 67.67, 24.75, 24.4, 25, 24.61, 24.02, 25.4, 18.7, 29, 11.48, >> 7.103), >> > > > > Measure = c("MF None", "MF None", "MF None", "MF None", "MF None", >> > > > > "MF Equity", "MF Equity", "MF Equity", "MF Equity", "MF Equity", >> "MF >> > > > > Debt", "MF Debt", "MF Debt", "MF Debt", "MF Debt", "MF Hybrid", >> "MF >> > > > > Hybrid", "MF Hybrid", "MF Hybrid", "MF Hybrid", "Bank None", "Bank >> > > > > None", "Bank None", "Bank None", "Bank None", "Bank Current", >> "Bank >> > > > > Current", "Bank Current", "Bank Current", "Bank Current", "Bank >> > > > > Savings", "Bank Savings", "Bank Savings", "Bank Savings", "Bank >> > > > > Savings", "MF None 1", "MF None 1", "MF None 1", "MF None 1", "MF >> > > > > None 1", "MF Equity 1", "MF Equity 1", "MF Equity 1", "MF Equity >> 1", >> > > > > "MF Equity 1", "MF Debt 1", "MF Debt 1", "MF Debt 1", "MF Debt 1", >> > > > > "MF Debt 1", "MF Hybrid 1", "MF Hybrid 1", "MF Hybrid 1", "MF >> Hybrid >> > > > > 1", "MF Hybrid 1", "Bank None 1", "Bank None 1", "Bank None 1", >> > > > > "Bank None 1", "Bank None 1", "Bank Current 1", "Bank Current 1", >> > > > > "Bank Current 1", "Bank Current 1", "Bank Current 1", "Bank >> Savings >> > > > > 1", "Bank Savings 1", "Bank Savings 1", "Bank Savings 1", "Bank >> > > > > Savings 1", "MF None 2", "MF None 2", "MF None 2", "MF None 2", >> "MF >> > > > > None 2", "MF Equity 2", "MF Equity 2", "MF Equity 2", "MF Equity >> 2", >> > > > > "MF Equity 2", "MF Debt 2", "MF Debt 2", "MF Debt 2", "MF Debt 2", >> > > > > "MF Debt 2", "MF Hybrid 2", "MF Hybrid 2", "MF Hybrid 2", "MF >> Hybrid >> > > > > 2", "MF Hybrid 2", "Bank None 2", "Bank None 2", "Bank None 2", >> > > > > "Bank None 2", "Bank None 2", "Bank Current 2", "Bank Current 2", >> > > > > "Bank Current 2", "Bank Current 2", "Bank Current 2", "Bank >> Savings >> > > > > 2", "Bank Savings 2", "Bank Savings 2", "Bank Savings 2", "Bank >> > > > > Savings 2", "MF None 3", "MF None 3", "MF None 3", "MF None 3", >> "MF >> > > > > None 3", "MF Equity 3", "MF Equity 3", "MF Equity 3", "MF Equity >> 3", >> > > > > "MF Equity 3", "MF Debt 3", "MF Debt 3", "MF Debt 3", "MF Debt 3", >> > > > > "MF Debt 3", "MF Hybrid 3", "MF Hybrid 3", "MF Hybrid 3", "MF >> Hybrid >> > > > > 3", "MF Hybrid 3", "Bank None 3", "Bank None 3", "Bank None 3", >> > > > > "Bank None 3", "Bank None 3", "Bank Current 3", "Bank Current 3", >> > > > > "Bank Current 3", "Bank Current 3", "Bank Current 3", "Bank >> Savings >> > > > > 3", "Bank Savings 3", "Bank Savings 3", "Bank Savings 3", "Bank >> > > > > Savings 3")), class = c("tbl_df", "tbl", "data.frame"), row.names >> = >> > > > > c(NA, >> > > > > -140L)) >> > > > > >> > > > > >> > > > > >> > > > > >> > > > > On Thu, 29 Jun 2023 at 21:11, John Kane <jrkrid...@gmail.com> >> wrote: >> > > > > >> > > > >> Anupa, >> > > > >> >> > > > >> I think your best bet with your data would be to tidy it up in >> > > > >> Excel, read it into R using something like the readxl package >> and >> > > > >> then supply some sample data is the dput() function. >> > > > >> >> > > > >> In the case of a large dataset something like dput(head(mydata, >> > > > >> 100)) should supply the data we need. Just do dput(mydata) where >> > > > >> *mydata* is your data. Copy the output and paste it here. >> > > > >> >> > > > >> On Thu, 29 Jun 2023 at 08:37, Ebert,Timothy Aaron < >> teb...@ufl.edu> >> > > wrote: >> > > > >> >> > > > >>> Reposting the data did not help. We do not like to guess, and >> > > > >>> doing so takes a great deal of time that is likely wasted. >> > > > >>> Rows are observations. >> > > > >>> Columns are variables. >> > > > >>> In Excel, the first row will be variable names and all >> subsequent >> > > > >>> rows will be observations. >> > > > >>> >> > > > >>> Income is the first variable. It has seven states: $10, $25, >> $40, >> > > > >>> $75, >> > > > >>> >$75, "No", "Answer" >> > > > >>> MF is the second variable. It has six values: 1, 2, 3, 4, 5, 9 >> > > > >>> None is the third variable. It has seven values: 1, 3.05, 2.29, >> > > > >>> 2.24, 1.71, 1.30, 2.83 Equity is the last variable with many >> > > > >>> states, both numeric and text. A computer will read it all as >> > > > >>> text. >> > > > >>> >> > > > >>> As written the data cannot be analyzed. >> > > > >>> >> > > > >>> Equity looks like it should be numeric. However, it has text >> > values: >> > > > >>> "Debt", "Hybrid", Bank", "AC", "None", "Current", "Savings", >> "No", >> > > > >>> and "Answer" >> > > > >>> >> > > > >>> In looking at the data I try to find some organization where >> every >> > > > >>> variable has the same number of rows as every other variable. I >> > > > >>> fail with these data. >> > > > >>> I could combine "No" and "Answer" into one name "No Answer" to >> > > > >>> make it agree with MF, but then it does not work for None. >> > > > >>> >> > > > >>> >> > > > >>> Please rework the data in Excel so that we can properly >> interpret >> > > > >>> the content. If it is badly organized in Excel, moving it to R >> > will not help. >> > > > >>> Below, I tried adding carriage returns and spaces to organize >> the >> > > > >>> data, but I have a column of numbers that are not identified. >> The >> > > > >>> values below >> > > > >>> $10 do not make much sense compared to other values. >> > > > >>> >> > > > >>> I am tired of guessing. >> > > > >>> >> > > > >>> Tim >> > > > >>> >> > > > >>> -----Original Message----- >> > > > >>> From: R-help <r-help-boun...@r-project.org> On Behalf Of Anupam >> > > > >>> Tyagi >> > > > >>> Sent: Wednesday, June 28, 2023 11:49 PM >> > > > >>> To: r-help@r-project.org >> > > > >>> Subject: Re: [R] Plotting factors in graph panel >> > > > >>> >> > > > >>> [External Email] >> > > > >>> >> > > > >>> Thanks, Pikal and Jim. Yes, it has been a long time Jim. I hope >> > > > >>> you have been well. >> > > > >>> >> > > > >>> Pikal, thanks. Your solution may be close to what I want. I did >> > > > >>> not know that I was posting in HTML. I just copied the data from >> > > > >>> Excel and posted in the email in Gmail. The data is still in >> > > > >>> Excel, because I have not yet figured out what is a good way to >> > > > >>> organize it in R. I am posting it again below as text. These are >> > > > >>> rows in Excel: 1,2,3,5,9 after MF are income categories and No >> > > > >>> Answer category (9). Down the second column are categories of MF >> > > and Bank AC. Rest of the columns are percentages. >> > > > >>> >> > > > >>> Jim, thanks for the graph. I am looking to plot only one line >> > > > >>> (category) each in many small plots on the same page. I don't >> want >> > > > >>> to compare different categories on the same graph as you do, but >> > > > >>> see how each category varies by income, one category in each >> > > > >>> graph. Like Excel does with Sparklines (Top menu: Insert, >> > > > >>> Sparklines, Lines). I have many categories for many variables. I >> > am only >> > > showing two MF and Bank AC. >> > > > >>> >> > > > >>> Income $10 $25 $40 $75 > $75 No Answer >> > > > >>> MF 1 2 3 4 5 >> > 9 >> > > > >>> None 1 3.05 2.29 2.24 1.71 1.30 >> > > > >>> 2.83 >> > > > >>> Equity 2 29.76 28.79 29.51 28.90 31.67 >> > > > >>> 36.77 >> > > > >>> >> > > > >>> Debt 3 31.18 32.64 34.31 35.65 37.59 >> > > > >>> 33.15 >> > > > >>> >> > > > >>> Hybrid 4 36.00 36.27 33.94 33.74 29.44 27.25 >> > > > >>> >> > > > >>> Bank AC None 1 46.54 54.01 59.1 62.17 67.67 60.87 >> > > > >>> >> > > > >>> Current 2 24.75 24.4 25 24.61 24.02 21.09 >> > > > >>> >> > > > >>> Savings 3 25.4 18.7 29 11.48 7.103 13.46 >> > > > >>> >> > > > >>> No Answer 9 3.307 2.891 13.4 1.746 1.208 4.577 >> > > > >>> >> > > > >>> >> > > > >>> On Wed, 28 Jun 2023 at 17:30, Jim Lemon <drjimle...@gmail.com> >> > > wrote: >> > > > >>> >> > > > >>> > Hi Anupam, >> > > > >>> > Haven't heard from you in a long time. Perhaps you want >> > > > >>> > something like >> > > > >>> > this: >> > > > >>> > >> > > > >>> > at_df<-read.table(text= >> > > > >>> > "Income MF MF_None MF_Equity MF_Debt MF_Hybrid Bank_None >> > > > >>> > Bank_Current Bank_Savings Bank_NA >> > > > >>> > $10 1 3.05 29.76 31.18 36.0 46.54 24.75 25.4 3.307 >> > > > >>> > $25 2 2.29 28.79 32.64 36.27 54.01 24.4 18.7 2.891 >> > > > >>> > $40 3 2.24 29.51 34.31 33.94 59.1 25.0 29 13.4 >> > > > >>> > $75 4 1.71 28.90 35.65 33.74 62.17 24.61 11.48 1.746 >> > > > >>> > >$75 5 1.30 31.67 37.59 29.44 67.67 24.02 7.103 1.208 >> > > > >>> > No_Answer 9 >> > > > >>> > 2.83 36.77 33.15 27.25 60.87 21.09 13.46 4.577", >> > > > >>> > header=TRUE,stringsAsFactors=FALSE) >> > > > >>> > at_df<- >> > > at_df[at_df$Income!="No_Answer",which(names(at_df)!="Bank >> > > > >>> > _NA")] >> > > > >>> > png("MF_Bank.png",height=600) >> > > > >>> > par(mfrow=c(2,1)) >> > > > >>> > >> matplot(at_df[,c("MF_None","MF_Equity","MF_Debt","MF_Hybrid")], >> > > > >>> > type="l",col=1:4,lty=1:4,lwd=3, main="Percentages by Income >> > > > >>> > and MF type", xlab="Income",ylab="Percentage of >> group",xaxt="n") >> > > > >>> > axis(1,at=1:5,labels=at_df$Income) >> > > > >>> > legend(3,24,c("MF_None","MF_Equity","MF_Debt","MF_Hybrid"), >> > > > >>> > lty=1:4,lwd=3,col=1:4) >> > > > >>> > matplot(at_df[,c("Bank_None","Bank_Current","Bank_Savings")], >> > > > >>> > type="l",col=1:3,lty=1:4,lwd=3, main="Percentages by Income >> > > > >>> > and Bank type", xlab="Income",ylab="Percentage of >> > > > >>> > group",xaxt="n") >> > > > >>> > axis(1,at=1:5,labels=at_df$Income) >> > > > >>> > legend(3,54,c("Bank_None","Bank_Current","Bank_Savings"), >> > > > >>> > lty=1:4,lwd=3,col=1:3) >> > > > >>> > dev.off() >> > > > >>> > >> > > > >>> > Jim >> > > > >>> > >> > > > >>> > On Wed, Jun 28, 2023 at 6:33 PM Anupam Tyagi >> > > > >>> > <anupty...@gmail.com> >> > > > >>> wrote: >> > > > >>> > > >> > > > >>> > > Hello, >> > > > >>> > > >> > > > >>> > > I want to plot the following kind of data (percentage of >> > > > >>> > > respondents >> > > > >>> > from a >> > > > >>> > > survey) that varies by Income into many small *line* graphs >> in >> > > > >>> > > a panel of graphs. I want to omit "No Answer" categories. I >> > > > >>> > > want to see how each one of the categories (percentages), >> > > > >>> > > "None", " Equity", etc. varies by >> > > > >>> > Income. >> > > > >>> > > How can I do this? How to organize the data well and how to >> > > > >>> > > plot? I >> > > > >>> > thought >> > > > >>> > > Lattice may be a good package to plot this, but I don't know >> > > > >>> > > for sure. I prefer to do this in Base-R if possible, but I >> am >> > > > >>> > > open to ggplot. Any >> > > > >>> > ideas >> > > > >>> > > will be helpful. >> > > > >>> > > >> > > > >>> > > Income >> > > > >>> > > $10 $25 $40 $75 > $75 No Answer MF 1 2 3 4 5 9 None 1 3.05 >> > > > >>> > > 2.29 2.24 1.71 1.30 2.83 Equity 2 29.76 28.79 29.51 >> > > > >>> > > 28.90 31.67 36.77 Debt 3 31.18 32.64 34.31 35.65 37.59 33.15 >> > > > >>> > > Hybrid >> > > > >>> > > 4 36.00 36.27 33.94 33.74 29.44 27.25 Bank AC None 1 46.54 >> > > > >>> > > 54.01 >> > > > >>> > > 59.1 62.17 67.67 60.87 Current 2 24.75 24.4 25 24.61 24.02 >> > > > >>> > > 21.09 Savings 3 25.4 18.7 29 11.48 7.103 13.46 No Answer 9 >> > > > >>> > > 3.307 2.891 >> > > > >>> > > 13.4 1.746 1.208 4.577 >> > > > >>> > > >> > > > >>> > > Thanks. >> > > > >>> > > -- >> > > > >>> > > Anupam. >> > > > >>> > > >> > > > >>> > > [[alternative HTML version deleted]] >> > > > >>> > > >> > > > >>> > > ______________________________________________ >> > > > >>> > > R-help@r-project.org mailing list -- To UNSUBSCRIBE and >> more, >> > > > >>> > > see https://st/ >> > > > >>> > > at.ethz.ch%2Fmailman%2Flistinfo%2Fr- >> > > help&data=05%7C01%7Ctebert >> > > > >>> > > %40ufl >> > > > >>> > > >> > > .edu%7C59874e74164c46133f2c08db7853d28f%7C0d4da0f84a314d76ace6 >> > > > >>> > > 0a6233 >> > > > >>> > > >> > > 1e1b84%7C0%7C0%7C638236073642897221%7CUnknown%7CTWFpbGZsb3d >> > > 8ey >> > > > >>> > > JWIjoi >> > > > >>> > > >> > > MC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3 >> > > > >>> > > 000%7C >> > > > >>> > > >> > > %7C%7C&sdata=xoaDMG7ogY4tMtqe30pONZrBdk0eq2cW%2BgdwlDHneWY >> > > %3D& >> > > > >>> > > reserv >> > > > >>> > > ed=0 >> > > > >>> > > PLEASE do read the posting guide >> > > > >>> > http://www.r/ >> > > > >>> > -project.org%2Fposting- >> > > guide.html&data=05%7C01%7Ctebert%40ufl.ed >> > > > >>> > u%7C59 >> > > > >>> > >> > > 874e74164c46133f2c08db7853d28f%7C0d4da0f84a314d76ace60a62331e1b8 >> > > > >>> > 4%7C0% >> > > > >>> > >> > > 7C0%7C638236073642897221%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4 >> > > wLjA >> > > > >>> > wMDAiL >> > > > >>> > >> > > CJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sd >> > > > >>> > ata=H7 >> > > > >>> > >> > > 6XCa%2FULBGUn0Lok93l6mtHzo0snq5G0a%2BL4sEH8%2F8%3D&reserved=0 >> > > > >>> > > and provide commented, minimal, self-contained, reproducible >> > > code. >> > > > >>> > >> > > > >>> >> > > > >>> >> > > > >>> -- >> > > > >>> Anupam. >> > > > >>> >> > > > >>> [[alternative HTML version deleted]] >> > > > >>> >> > > > >>> ______________________________________________ >> > > > >>> 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. >> > > > >>> ______________________________________________ >> > > > >>> 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. >> > > > >>> >> > > > >> >> > > > >> >> > > > >> -- >> > > > >> John Kane >> > > > >> Kingston ON Canada >> > > > >> >> > > > > >> > > > > >> > > > > -- >> > > > > Anupam. >> > > > > >> > > > > >> > > > >> > > > -- >> > > > Anupam. >> > > > >> > > > [[alternative HTML version deleted]] >> > > > >> > > > ______________________________________________ >> > > > 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. >> > > >> > > ______________________________________________ >> > > 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. >> > >> > >> > >> > >> > -- >> > >> > Anupam. >> > >> >> >> -- >> Anupam. >> ______________________________________________ >> 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. >> > -- Anupam. [[alternative HTML version deleted]] ______________________________________________ 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.