[R] Plotting factors in graph panel

[Deepayan Sarkar]

On Thu, 6 Jul 2023 at 15:21, Anupam Tyagi <anuptyagi using 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 <anuptyagi using 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 <jrkrideau using 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 <tebert using 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-bounces using r-project.org> On Behalf Of Anupam Tyagi
> >>> Sent: Wednesday, June 28, 2023 11:49 PM
> >>> To: r-help using 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 <drjimlemon using 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 <anuptyagi using 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 using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> >>> > > https://st/
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> >>> > > PLEASE do read the posting guide
> >>> > http://www.r/
> >>> > -project.org%2Fposting-guide.html&data=05%7C01%7Ctebert%40ufl.edu%7C59
> >>> > 874e74164c46133f2c08db7853d28f%7C0d4da0f84a314d76ace60a62331e1b84%7C0%
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> >>> > > and provide commented, minimal, self-contained, reproducible code.
> >>> >
> >>>
> >>>
> >>> --
> >>> Anupam.
> >>>
> >>>         [[alternative HTML version deleted]]
> >>>
> >>> ______________________________________________
> >>> R-help using 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 using 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 using 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.