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".
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%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@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]]
______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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