search for: mf_equiti

Okay. Here is a modification that does four single line plots. 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

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

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

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

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

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

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,

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 <anuptyagi at gmail.com> wrote: > Hi John: > > Thanks! Below is the data using your

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

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 =

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.pikal at precheza.cz> wrote: > Hallo Anupam > > I do not see much difference in ggplot or lattice, they seems to me > provide almost identical