Is there a way to make a forest plot have alternating translucent grey and white boxes for each variable in a forest plot in ggplot or sjplot similar to this formatting (preferably for sjplot)? I'd ideally like to do this using only a model object provided as the input and then the set the zebra theme
It's basically just the zebra format from the r package table1 seen in this link here
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I want to generate a forest plot using the forestplot package in R that looks like the following image
I have several sections I want to join together in a single long plot with a single axis at the bottom, but with the section headings separating each one. I can generate each forestplot independently and put them together, but the elements do not line up.
How do I generate the plot like this?
There is any package that could give me plots output like pencil style?
Like this below? Not only for maps but also for statistical analysis? Histogram, scatterplot and so on?
I have conducted an IRT analysis using package ltm in R 3.41. In plotting the curves using the plot command, the default is to use colors for the lines of the items. Unfortunately, I need to use a scheme that differentiates item lines using a line type, not color (journal where figure will be published will only publish black/white for free). Is it possible to tweak this using the native ltm plot command?
Using R I would like to replace the points in a 2d scatter plot by a pie chart displaying additional values.
The rational behind is that I have time series data for hundreds of elements (proteins) derived from a biological experiment monitored for 4 conditions. I would like to plot the elements (categorial data) on the y axis and occurrence of a event in time on the x axis. To visualize the relative occurrence between the 4 conditions I would like to visualize this in form of a pie chart or doughnut chart overplayed onto the respective point in the scatter plot.
The overall data density is low so overlapping won't be an issue.
Is this possible in R?
I was thinking of using a manual scale in ggplot2 but could not figure out how to define a pie chart as a scale.
Also of interest would be how to best cluster this data and sort it accordingly.
Yes. pieGlyph() is one ready-to-go function from the Rgraphviz package.
Also, I would check out this Q/A for how to do things like this more generally:
How to fill a single 'pch' point on the plot with two-colours?
Especially check out ?my.symbols from the TeachingDemos package.
Lastly, in regards to ggplot2, you should check out this blog post about possible upcoming features:
http://blog.revolutionanalytics.com/2011/10/ggplot2-for-big-data.html
See also Paul Murrell. Integrating grid graphics output with base graphics output. R News, 3(2):7-12, October 2003. http://www.r-project.org/doc/Rnews/Rnews_2003-2.pdf
The code on pp 10-11 sets up the main plot axes, labels and legend, and then opens a series of smaller windows centered at each individual point on the plot and plots a small graph in each window. I've tried pie charts, mosaics and barplots, but the method is not limited to these types.
It is possible to use the shingles to define specific ranges in ggplot2. As far as i understand shingles are a way to generate groups. Can we create such shingles and use them in ggplot2 facet_grid to obtain graphs?
Following up from the comments, ggplot can't draw shingles (in the way lattice draws shingles with special indicators in the strip) and by default doesn't have a means of producing the overlapping groups.
However, I cam across this excellent PDF document which aims to produce a gpplot2 version of every figure in Depayan's excellent Lattice book (Lattice: Multivariate Data Visualization with R).
Page 31 contains a custom function fn() which replicates the behaviour of equal.count(), as far as I can tell, to provide the correct data structure to plot with overlapping shingles. The PDF contains plenty of examples of "shingles" in ggplot that you can play with.
So not sure if this answers the Q - but at least it appears one can fudge ggplot into producing plots that use the shingle concept.