Interactive Data Visualization and Exploration Using the Loon R - - PowerPoint PPT Presentation

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Interactive Data Visualization and Exploration Using the Loon R - - PowerPoint PPT Presentation

May 22, 2023 353 likes •706 views

Interactive Data Visualization and Exploration Using the Loon R package Adrian Waddell PhUSE 2016, Barcelona Motivation for new interactive visualization tools Carefully designed, general, and extendable framework simple plots

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Interactive Data Visualization and Exploration

Using the Loon R package Adrian Waddell
 PhUSE 2016, Barcelona

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Motivation for new interactive visualization tools

Carefully designed, general, and extendable framework

  • simple plots
  • attention to high-dimensional data
  • extendable
  • study and compare methodologies visually
  • analysis, research and teaching
  • integrated in popular statistical environment such as R
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Introduction of Loon with the Gapminder Data

data from grapminder.com, for year 2009

  • Western World
  • Long Life & Small Family
  • Third World
  • Short Life & Large Family
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p1 <- l_plot(x=Fertility, y=LifeExpectancy, color=region_cols, size=pop_size, itemlabel=country, linkingGroup="world") p2 <- l_plot(x=Income, y=LifeExpectancy, itemlabel=country, linkingGroup="world") h <- l_hist(x=Income, linkingGroup="world")

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Displays

Others in Development

  • barplot
  • pairs, currently

compound view

  • …
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Interactive Statistical Visualization Toolkit

Direct Manipulation Command Line Control Extendable Toolkit

Widgets

::tk::button ::tk::scale ::loon::plot ::loon::plot_inspector_analysis

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Point Glyphs

Statistical Graphics

Layers Dynamic Linking Inspectors

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Point Glyphs

Statistical Graphics

Layers Dynamic Linking Inspectors

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Point Glyphs

Statistical Graphics

Layers Dynamic Linking Inspectors

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Statistical Graphics

Inspectors Point Glyphs Layers Dynamic Linking

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Inspectors

Statistical Graphics

Point Glyphs Layers Dynamic Linking

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Framework

p <- l_plot(x=Fertility, y=LifeExpectancy, color=region_cols, size=pop_size)

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Framework

p <- l_plot(x=Fertility, y=LifeExpectancy, color=region_cols, size=pop_size) x y color size

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Framework

x y color size p <- l_plot(x=Fertility, y=LifeExpectancy, color=region_cols, size=pop_size) selected active showScales showLabels ...

Plot States n dimensional 1 dimensional boolean ~ 35 other states

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Example Visualizing Adverse Events

  • Generate Adverse Events Data
  • Analysis Data Model (ADaM) Data Structure for Adverse Event Analysis

Name Description USUBJID Unique Subject ID SEX Gender AGE Age ARM Study Arm DISCDEAT Discontinued Study due to Death TRTSDT Treatment Start TRTEDT Treatment End AESEQ Sequence Number AETERM Reported Term for the Adverse Event AESEVN Analysis Severity/Intensity (N) ASTDT Analysis Start Date AENDT Analysis End Date ADURN Duration of Adverse Event

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Example Visualizing Adverse Events

live demo

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Example Visualizing Adverse Events

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waddella.github.io/loon