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How can I produce plots like this?
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Closed 9 years ago.
Just read the "Mining time series data" pdf by Ratanamahatana, Lin, Gunopulos and Keogh. Did someone know how to visualize time series clusters in R like in the Figure 1.7?
You can visualize 100s of Time Series sequences with Sparklines. If you also want to the Hierarchical ordering, the you could attain that in 2 steps.
Sort your data.frame of Times Series sequences by their multi-level clusters. (This assumes that you have computed the cluster hierarchy for each series.)
Download and install the SparkTable in your R setup. Now plot the Sparklines for your TS sequences. Take a look at this Inside-R page for SparkEPS.
This answer on statExchange is exactly what you need for the plotting part, so I am not reproducing the same example here.
Hope that helps.
This figure most likely is made with a drawing program, not with a data mining software.
Nobody would run cluster analysis on 6 observations like this. It's easier to look at them visually and do it manually than figuring out how to have a program visualize it this way.
Related
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Scatterplot matrixes with boxplots for categorical data
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Create a matrix of scatterplots (pairs() equivalent) in ggplot2
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Closed 29 days ago.
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I’m fairly sure I saw a package that did this, but I cannot find its name in my notes.
This package produces a plot for each pair of variables in a data frame, but chooses the plot based on the columns’ types. So, two numeric variables would produce a scatterplot. A numeric y and categorical x would produce side-by-side box plots. Like that. It’s this multiple column type ability that distinguishes it from the packages I can find by Googling.
Perhaps I should say that I’m certain I saw it, and didn’t see a bunch of surrounding code with loops or purr calls looping over the data, so I’m guessing there was a package that did it.
You're probably thinking of GGally::ggpairs:
library(GGally)
ggpairs(iris)
[Hey, I am sorry if this question might be too easy for this forum! My task was to decompose a time series to break it into the different components. Then plot it in R.
However, the correct solutions included the part that I uploaded as a picture. We are trying to identify the monthly data right? but why are we using the cbind and the data.frame function? than you very much in advance[enter image description here]1 ][2]
Community,
I have a question regarding the STM package for R and hope that you can help me find an answer.
In figure 7 of the vignette the authors present a graph, where the topic prevalence (for topic 7) over time can be seen. Is it possible to plot the same graph by adding two further lines: one for liberal and one for conservative?
Liberal and conservative are attributes of the variable "rating"
The plot in figure 7 shows you the topic proportion of one topic (in this case topic 7) over a time span of January 2008 to December 2008. Basically, this graph shows you how your topic is distributed over a specific time frame. You can plot other topics in this graph, so yes, you can add more lines, but you cannot add a variable, like liberal/conservative, to plot in this graph.
Also, you might want to have a look at this -- it would be useful to add a reproducible example for clarity
How to make a great R reproducible example
i have a problem with clustering time series in R.
I googled a lot and found nothing that fits my problem.
I have made a STL-Decomposition of Timeseries.
The trend component is in a matrix with 64 columns, one for every series.
Now i want to cluster these series in simular groups, involve the curve shapes and the timely shift. I found some functions that imply one of these aspects but not both.
First i tried to calculte a distance matrix with the dtw-distance so i
found clusters based on the values and inply the time shift but not on the shape of the timeseries. After this i tried some correlation based clustering, but then the timely shift
we're not recognized and the result dont satisfy my claims.
Is there a function that could cover my problem or have i to build up something
on my own. Im thankful for every kind of help, after two days of tutorials and examples i totaly uninspired. I hope i could explain the problem well enough to you.
I attached a picture. Here you can see some example time series.
There you could see the problem. The two series in the middle are set to one cluster,
although the upper and the one on the bottom have the same shape as one of the middle.
Have you tried the R package dtwclust
https://cran.r-project.org/web/packages/dtwclust/index.html
(I'm just starting to explore this package, but it seems like it covers a lot of aspects of time series clustering and it has lots of good references.)
you can use the kml package. It is used specifically to longitudinal data. You can consult its help. It has the next example:
### Generation of some data
cld1 <- generateArtificialLongData(25)
### We suspect 3, 4 or 6 clusters, we want 3 redrawing.
### We want to "see" what happen (so printCal and printTraj are TRUE)
kml(cld1,c(3,4,6),3,toPlot='both')
### 4 seems to be the best. We want 7 more redrawing.
### We don't want to see again, we want to get the result as fast as possible.
kml(cld1,4,10)
Example cluster
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Closed 12 years ago.
Possible Duplicate:
Multiple Bar plot in one graphs in R
Hi,
I'm a beginner to R.
I need to create a graph like
http://i.stack.imgur.com/az56z.jpg
I dont know how to produce my entire dataset. The basic idea is some exon id would have more than one subgroups. I need to plot all the values in bar plots within that exon id
How can I do that in R?
I had to do R in my stats class last semester. For the future if you google r-code it yields better results. I know that just searching for r always makes annoying results.
If you set up your dataset as a value say
library(gdata)
dataset = read.csv('blahh.csv')
barplot(dataset, main="blahh",
xlab="blahh")