Is it possible to add plot interactions such as zooming as shown here and panning to charts plotted with the chartseries function from quantmod?
I am trying to find a decent yet simple solution for charting financial data (mainly candlesticks) with R. The standard chartseries plots are ok but severely lack a nice zooming functionality. I've use DYGRaphs and gvis packages but they struggle with plotting a non-continuous timeseries on the x-axis (i.e they have gaps in the data for weekends.) Gvis can over come this by using a discrete x-axis but then you lose the dates as labels. The other issue with these is that they dont have the nice integration of the indicators and trades on the plot that quantmod gives you.
I'm fairly new to R, but after spending several days exploring all the options for charting financial data and not finding a half decent solution, I think I'm barking up the wrong tree. Is there any sort of industry standard that I've completely missed?
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I've created a time series plot in R using the ggplot package, but I wanted to see if I could further customize it by creating target zones. I originally started with an Excel plot that allows me to move a gray box to different areas of the plot as an easier way to point out a range of temperatures. However, I wanted to see if I could replicate this in R. Here's a screenshot of my Excel plot to better explain my goal: Time Series on Excel. On the time series plot, you can see a gray box that you can drag around and change the size of to better define a range of temperatures (in this case, it covers from 15-25C). Is this possible to do on top of my time series plot in R? I'm only starting to code in R so it's been quite hard for me to navigate, and I appreciate any help I could get. Thanks!
My question is about overlaying plots of different x and y scales .The raw data is out of a public weather database in New Zealand called CliFlo, managed by NIWA. I'm not prepared to copy the data for an example because of copyright protections.
I want to reproduce the types of graphs they offer at a fee, shown on this web page. Take the Rainfall graph. There is a cumulative rainfall line graph overlayed on top of a monthly rainfall bar graph. I can generate each graph separately using ggplot2, but I can't find a good way to overlay them like in the example. I've found the gridExtra package to let me print them side-by-side, and I've come across the magick package that might let me do the job, but I'm not sure on how to get the plots lined up properly and how to use the magick package properly. Can anybody help me out on this?
Should I try to scale the month bars to fit the daily line graph but make them spaced out and thicker so they look like months, or would it be easier to use the magick package somehow?
I'd attach an image of what I have so far, but I'm new to this website and it won't let me yet.
I am typically using R to do statistical analysis, and rather new to the data visualization capabilities. I'm trying to figure out if there is some way to marry the motion chart package gvisMotionChart with the mapping package, gvisGeoMap. I'd like to display a video of events over time, appearing on a map on their date of occurrence at lat/lon coordinates and then fading out. Anyone know if it's possible to do this? Any additional concerns if I have over 50,000 records (daily over 5 years) that I want to feed in to be displayed?
Please note that I do not have to use the gvis packages--I am just using these to motivate the idea. If there are other dynamic mapping packages available in R that will just draw on a shapefile and my event records, all the better.
Thanks!
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.