On Thu, 6 Jul 2023 at 15:21, Anupam Tyagi <anuptyagi at 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 at 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 at 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 at 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 at r-project.org> On Behalf Of Anupam Tyagi > >>> Sent: Wednesday, June 28, 2023 11:49 PM > >>> To: r-help at 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 at 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 at 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 at 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%7C0d4da0f84a314d76ace60a6233 > >>> > > 1e1b84%7C0%7C0%7C638236073642897221%7CUnknown%7CTWFpbGZsb3d8eyJWIjoi > >>> > > MC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%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.edu%7C59 > >>> > 874e74164c46133f2c08db7853d28f%7C0d4da0f84a314d76ace60a62331e1b84%7C0% > >>> > 7C0%7C638236073642897221%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiL > >>> > CJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=H7 > >>> > 6XCa%2FULBGUn0Lok93l6mtHzo0snq5G0a%2BL4sEH8%2F8%3D&reserved=0 > >>> > > and provide commented, minimal, self-contained, reproducible code. > >>> > > >>> > >>> > >>> -- > >>> Anupam. > >>> > >>> [[alternative HTML version deleted]] > >>> > >>> ______________________________________________ > >>> R-help at 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 at 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 at 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.
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-bounces at r-project.org> On Behalf Of Deepayan
Sarkar
> Sent: Thursday, July 6, 2023 3:06 PM
> To: Anupam Tyagi <anuptyagi at gmail.com>
> Cc: r-help at r-project.org
> Subject: Re: [R] Plotting factors in graph panel
>
> On Thu, 6 Jul 2023 at 15:21, Anupam Tyagi <anuptyagi at 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 at
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 at
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
at 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 at r-project.org> On
Behalf Of Anupam
> > >>> Tyagi
> > >>> Sent: Wednesday, June 28, 2023 11:49 PM
> > >>> To: r-help at 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 at
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 at 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 at 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 at 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 at 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 at 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 at 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.
Thanks! Is there a way to reduce font-size of text of x-axis labels and titles of sub-graphs? That will probably make graphs more readable. I am realizing that since the y-axis scales are very different for some graphs, I may have to figure out a way to build the sub-graphs one at a time, manually, and then combine them together. It is going to be very tedious. I have more than 100 sub-graphs to display, more than 50 varying by income and more than 50 varying by education. I may need to combine them in two or four panels of graphs. No journal is likely to want pages full of sub-graphs. On Thu, 6 Jul 2023 at 18:35, Deepayan Sarkar <deepayan.sarkar at gmail.com> wrote:> On Thu, 6 Jul 2023 at 15:21, Anupam Tyagi <anuptyagi at 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 at 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 at 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 at 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 at r-project.org> On Behalf Of Anupam > Tyagi > > >>> Sent: Wednesday, June 28, 2023 11:49 PM > > >>> To: r-help at 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 at 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 at 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 at 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%7C0d4da0f84a314d76ace60a6233 > > >>> > > > 1e1b84%7C0%7C0%7C638236073642897221%7CUnknown%7CTWFpbGZsb3d8eyJWIjoi > > >>> > > > MC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%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.edu > %7C59 > > >>> > > 874e74164c46133f2c08db7853d28f%7C0d4da0f84a314d76ace60a62331e1b84%7C0% > > >>> > > 7C0%7C638236073642897221%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiL > > >>> > > CJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=H7 > > >>> > 6XCa%2FULBGUn0Lok93l6mtHzo0snq5G0a%2BL4sEH8%2F8%3D&reserved=0 > > >>> > > and provide commented, minimal, self-contained, reproducible > code. > > >>> > > > >>> > > >>> > > >>> -- > > >>> Anupam. > > >>> > > >>> [[alternative HTML version deleted]] > > >>> > > >>> ______________________________________________ > > >>> R-help at 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 at 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 at 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. 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