FW: About linked-brushing features in Matplotlib

Dear contributors,

I am Jerry, a developer relying on Python to analyze data.
I searched through Matplotlib webpage trying to find a hint about how to make "linked brushing" feature across graphs and data, however it is not successful so far. The "linked-brushing" feature means: taking a scatter plot and a histogram based on the same data for example, when some of the points on the scatter plot are selected, since those points are linked to some data from which the plot is built, the parts of the same data on the histogram will be automatically selected and highlighted too.
The attached is an example from Bokeh plots.

Could I ask:
1. where can I find hints about how to realize this feature with Matplotlib?
2. As there is other visualization packages based on Matplotlib, taking Seaborn as an example, if this feature is realized with Matplotlib, can it be used directly into Seaborn? If yes, could you please share a few hints on how to do that if possible?

Thank you all very much in advance!

Jerry Li
                                  
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Glueviz has implemented linked brushing.

Have a look at the lasso demo (
http://matplotlib.org/examples/event_handling/lasso_demo.html), only change
what artist the call back changes.

Tom

···

On Thu, Oct 29, 2015 at 10:25 PM Jerry li <jerry.li at outlook.com> wrote:

Dear contributors,

I am Jerry, a developer relying on Python to analyze data.
I searched through Matplotlib webpage trying to find a hint about how to
make "linked brushing" feature across graphs and data, however it is not
successful so far. The "linked-brushing" feature means: taking a scatter
plot and a histogram based on the same data for example, when some of the
points on the scatter plot are selected, since those points are linked to
some data from which the plot is built, the parts of the same data on the
histogram will be automatically selected and highlighted too.
The attached is an example from Bokeh plots.

Could I ask:
1. where can I find hints about how to realize this feature with
Matplotlib?
2. As there is other visualization packages based on Matplotlib, taking
Seaborn as an example, if this feature is realized with Matplotlib, can it
be used directly into Seaborn? If yes, could you please share a few hints
on how to do that if possible?

Thank you all very much in advance!

Jerry Li
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