similar to: Plotting two lines on a graph when using par(mfrow=)

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

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 =

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

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

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

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

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

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

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

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

I have 2 zoo objects - 1) Interest rate spread between 10-YR-US-Treasury and 2-YR-US-Treasury (object name = sprd) 2) S&P 500 index (object name = spy) > str(spy) ?zoo? series from 1976-06-01 to 2011-03-31 Data: num [1:8791] 99.8 100.2 100.1 99.2 98.6 ... Index: Class 'Date' num [1:8791] 2343 2344 2345 2346 2349 ... > str(sprd) ?zoo? series from 1976-06-01 to 2011-03-31

Hi All! I am interested in testing whether the means for the data I am investigating are equal to a specific value - let's say 0.01. I have already run a one-way ANOVA and know that the differences in the means are not significant, so now I want to know what values the means take on. "otestme" is the data I am working with (it would be hard for me to get into a form that would be

I am trying to plot two 3-dimensional time series in one window (such that there will be 3 rows and 2 columns). For zoo and ts objects the par(mfrow...) option does not work. I can get xyplot to make the plots, but data are on widely different scales in the three dimensions, and xyplot uses the same scale on all y-axis which means that in some dimensions the curves will be almost horizontal lines.

Hi All! I have been messing around with this problem for about a week but to no avail! The following data has been cut down in order to make my question reproducible. The alldat data frame includes 2 columns: 1 date column and 1 factor column (equity names)).

Dear list, I encounter an error when I try to use ddply to generate means as follows: fun3<-structure(list(sector = structure(list(gics_sector_name = c("Financials", "Financials", "Materials", "Materials")), .Names = "gics_sector_name", row.names = structure(c("UBSN VX Equity", "LLOY LN Equity", "AI FP Equity",

Hi, Can anyone shed any light on why "reaper" (whilst seemingly working re restarting my mongrel ruby process) does not pick up changes to my application? (e.g. changing a title in a view for example). It''s like the "mongrel_rails start etc..." is just restarting the current process but ignoring the new details re where the new application directory is. That is

Can we add a note to the documentation that setting par(fig) resets par(mfrow) and par(mfcol) to c(1,1)? Or are mfrow and mfcol now deprecated in favor of all the split screen stuff? (I was spending the morning trying to write some code that plotted multiple subplots within whatever plot region was active at the moment; I was able to set and reset fig successfully, but got very confused as to

help(par) says: 'mfcol, mfrow' ... In a layout with exactly two rows and columns the base value of '"cex"' is reduced by a factor of 0.83: if there are three or more of either rows or columns, the reduction factor is 0.66. In reality, par(mfrow =) *resets* par ('cex'), not reduces it as documented. To reproduce: par(cex = 0.5) par(mfrow = c(2,

Dear R Users, I am doing stats::decompose() on 4 different time series. When I issue csdA <- decompose(tsA) plot(csdA) I get a summary plot for observed, trend, seasonal and random components of decomposed time series tsA. As I understand it, the object returned by decompose() has it's own plot method where mfrow(4,1) etc. is defined. Now suppose I wanted to wrap those mfrow(4,1) into