[R] When is *interactive* data visualization useful to use?

[Liviu Andronic]

On Fri, Feb 18, 2011 at 8:00 PM, Tom Hopper <tomhopper at gmail.com> wrote:
> Tal,
>
> One interactive capability that I have repeatedly wished for (but
> never taken the time to develop with the existing R tools) is the
> ability to interactively zoom in on and out of a data set,
>
I believe that you can do this with playwith. See this [1]. Regards
Liviu

[1] http://code.google.com/p/playwith/wiki/Screenshots#Time_series_plot_(Lattice)


and to
> interactively create "call-outs of sections of the data. Much of the
> data that I deal with takes the form of time series where both the
> full data and small section carry meaningful information.
>
> Some of the capabilities of Deducer approach interactive graphing,
> such as adjusting alpha values or smoothers, though the updates don't
> happen in quite real-time.
>
> - Tom
>
> On Friday, February 11, 2011, Tal Galili <tal.galili at gmail.com> wrote:
>> Hello all,
>>
>> Before getting to my question, I would like to apologize for asking this
>> question here.  My question is not directly an R question, however, I still
>> find the topic relevant to R community of users  - especially due to only *
>> partial* (current) support for interactive data visualization (see here:
>> http://cran.r-project.org/web/views/Graphics.html  were with iplots we are
>> waiting for iplots extreme, and with rggobi, it currently can not run with R
>> 2.12 and windows 7 OS).
>>
>> And now for my question:
>>
>> While preparing for a talk I will give soon, I recently started digging into
>> two major (Free) tools for interactive data visualization:
>> GGobi<http://www.ggobi.org/>
>>  and mondrian <http://rosuda.org/mondrian/> - both offer a great range of
>> capabilities (even if they're a bit buggy).
>>
>> I wish to ask for your help in articulating (both to myself, and for my
>> future audience) *When is it helpful to use interactive plots? Either for
>> data exploration (for ourselves) and data presentation (for a "client")?*
>>
>> For when explaining the data to a client, I can see the value of animation
>> for:
>>
>>    - Using "identify/linking/brushing" for seeing which data point in the
>>    graph is what.
>>    - Presenting a sensitivity analysis of the data (e.g: "if we remove this
>>    point, here is what we will get)
>>    - Showing the effect of different groups in the data (e.g: "let's look at
>>    our graphs for males and now for the females")
>>    - Showing the effect of time (or age, or in general, offering another
>>    dimension to the presentation)
>>
>> For when exploring the data ourselves, I can see the value of
>> identify/linking/brushing when exploring an outlier in a dataset we are
>> working on.
>>
>> But other then these two examples, I am not sure what other practical use
>> these techniques offer. Especially for our own data exploration!
>>
>> It could be argued that the interactive part is good for exploring (For
>> example) a different behavior of different groups/clusters in the data. But
>> when (in practice) I approached such situation, what I tended to do was to
>> run the relevant statistical procedures (and post-hoc tests) - and what I
>> found to be significant I would then plot with colors clearly dividing the
>> data to the relevant groups. From what I've seen, this is a safer approach
>> then "wondering around" the data (which could easily lead to data dredging
>> (were the scope of the multiple comparison needed for correction is not even
>> clear).
>>
>> I'd be very happy to read your experience/thoughts on this matter.
>>
>>
>> Thanks in advance,
>> Tal
>>
>>
>> ----------------Contact
>> Details:-------------------------------------------------------
>> Contact me: Tal.Galili at gmail.com |  972-52-7275845
>> Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il (Hebrew) |
>> www.r-statistics.com (English)
>> ----------------------------------------------------------------------------------------------
>>
>>         [[alternative HTML version deleted]]
>>
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>> and provide commented, minimal, self-contained, reproducible code.
>>
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>



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