I want to plot stacked histograms in R; i.e. stack individual histograms in the third dimension.
thank you all for your suggestions, especially the one by Shane.
#hadley, I agree with your points, however, my situation is different: the main point I'm trying to convey by plotting four stacked histograms is that the tails vary significantly....the part that will get obscured is of no consequence in the data I'm presenting....also, being able to read the frequency axis is also not important since I'll be plotting the relative frequencies...
One doesn't. This is a terrible display of data because the front histograms obscure the rear histograms and the perspective makes it just about impossible to read the values off the y-axis.
You could try using either rgl (see here) or 3dscatterplot (as in this example). Lattice also supports this:
library(lattice)
library(latticeExtra)
?panel.3dbars
You can see an example of this on the Learnr blog.
I don't believe that's technically a stacked histogram (a stacked histogram stacks the bars on top of each other). Moreover, a different kind of histogram could be more informative: look at the ggplot2 the documentation here for some examples.
hist_cut <- ggplot(diamonds, aes(x=price, fill=cut))
hist_cut + geom_bar() # defaults to stacking
Another option is to use latticing instead, with facet_wrap in ggplot2 (see this post as an example).
Related
I have a bar graph which looks like the following:
Problem: If I facet it by the same variable as the color, the x-axis has space for plotting all the bars even though I don't need them.
My Solution: I used multiplot function from the Rmisc to separately make bar graphs for each partner but then a lot of individual customization is needed to make the graphs go cohesively together.
Question: Is there another way that I can use to get closer to plot 2 without the extra spaces for the variables that don't apply.
I'm using ggplot to plot.
use:
+ facet_wrap(~variable_to_facet_by,
scales = 'free')
as part of your ggplot code and that should get you what you want.
I have created a similar plot following the instructions from this link regarding the plot with facets:
(source: statmethods.net)
I would like to add a trend line for every facet of the chart and also would like to arrange the facets for the y axis (3 gears, 4gears and 5 gears) manually. Same thing for x axis (4cyl, 6vyl and 8cyl) facets so they are arranged the way I want it rather than being sorted/arranged automatically.
I tried looking for a solution here in StackExchange and Googling around and found ways to add trendiness for charts that do not involve facets, but not how add trend lines for charts with multiple facets.
I am attempting to plot lots of graphs on the fly and I chanced upon the facet_wrap functionality. It produced the desired results until I realised that it was not assigning individual axes headings. There was just a single X and Y axis heading for a whole set of graphs. What I'm looking for is a way to assign individual axes headings for each graph.
Is this possible using the facet_wrap functionality at all?
Looking forward to any suggestions and advice.
EDIT:
(removed previous, incorrect, answer)
It is my understanding that if the axes of your plots are not the same (i.e. require different labels), the way to go would be with multiple separate plots (on the same page), and not with facet_wrap.
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.
I have a primary graph and some secondary information that I want to facet in another graph below it. Facetting works great except I do not know how to control the relative space used by one facet versus another. Am aware of space='free' but this is only useful if the ranges correspond to the desired relative sizing.
So for instance, I may want a graph where the first facet occupies 80% and the second 20%. Here is an example:
data <- rbind(
data.frame(x=1:500, y=rnorm(500,sd=1), type='A'),
data.frame(x=1:500, y=rnorm(500,sd=5), type='B'))
ggplot() +
geom_line(aes(x=x, y=y, colour=type), data=data) +
facet_grid(type ~ ., scale='free_y')
The above creates 2 facets of equal vertical dimension. Adding in space='free' in the facet_grid function changes the dimensions such that the lower facet is roughly 5x larger than the upper (as expected).
Supposing I want the upper to be 2x as large, with the same data set and ordering of facets. How can I accomplish this?
Is the only way to do this with some trickery in rescaling the data set and manually overriding axis labels (and if so, how)?
Alternative
As indicated below can use viewports to render as multiple graphs. I had considered this and in-fact had implemented using this approach in the past with standard plot and viewports.
The problem is that it is very difficult to get x-axis to align with this approach. So if there is a way to fix the size of the y-axis label region and the size of the legend region, can produce 2 graphs that have the same rendering area.
You don't need to use facets for this - you can also do this by using the viewport function.
> ratio = 1/3
> v1 = viewport(width=1,height=ratio,y=1-ratio/2)
> v2 = viewport(width=1,height=1-ratio,y=(1-ratio)/2)
> print(qplot(1:10,11:20,geom="point"),vp=v1)
> print(qplot(1:10,11:20,geom="line"),vp=v2)
Ratio is the proportion of the top panel to the whole page. Try 2/3 and 4/5 as well.
This approach can get ugly if your legend or axis labels in the two plots are different sizes, but for a fix, see the align.plots function in the ggExtra package and ggplot2 author Hadley Wickam's notes on this very topic.
There's no easy way to do this with facets currently, although if you are prepared to go down to editing the Grid, you can modify the ggplot graph after it has been plotted to get this effect.
See also this question on using grid and ggplot2 to create join plots using R.
Kohske Takahashi posted a patch to facet_grid that allows specification of the relative sizing of facets. See the thread:
http://groups.google.com/group/ggplot2/browse_thread/thread/7c5454dcc04bc7b8
With luck we'll see this in a future version of ggplot2.