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Name: Joel D. Rodriguez-Ortiz

Usage

The bottom view is a scatterplot matrix of all the numerical values of the football data set. This view can be panned by dragging with the mouse and zoomed in and out with the mouse scroll wheel. Double-clicking on any of the scatterplots in the matrix will update the (upper) juxtaposed view with the selected scatterplot. Points in this plot can also be clicked

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#Summary

Time Maps: Visualizing Discrete Events Accross Many Timescales is an essay written by Max Watson that addresses the visualization of discrete events.
This essay is mainly about the use of time maps to visualize discrete event data.
An initial example is presented to illustrate the problem of using histograms to plot discrete event data. The dataset is "website visits by a certain IP over 7 months". The main problem is that the time scale chosen in the plot (month per month), hides trends and details that are impossible to see in the histogram. Because of this the author proposes the use of time maps.

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##Name: Joel D. Rodriguez-Ortiz

##Node-Link Diagram Insights

Insights gained from this graph include:

  • Maine (ME) is adjacent to a single state, New Hampshire (NH).
  • Neglecting the actual distances of states, the shortest path from ME to Pennsylvania (PA) is { ME, NH, VT, NY, PA }.
  • The distance of the shortest path from ME to PA is 4 (dimensionless)
View blog0.md

#Summary

The use cases for less common graphs is a blog article authored authored by Cole Nussbaumer Knaflic. The article portrays examples of uncommon vis idioms. The motivation for the post actually arose from the author writing about idioms she most often used in practice. She noticed most of these were common idioms, like scatterplots or horizontal bar graphs. Because of this the author proposes situations when the use of uncommon idioms is appropriate via four examples (three effective use cases and an ineffective one).

The first example is an infographic that plots California moisture data. The idiom resembles a scatterplot but focuses on outliers by fading the middle portions of the plot and focuses on trends by plotting trend lines in the faded portion of the plot. It winds up effectively summarizing what would appear like an overwhelming amount of information under different circumstances.

The second exam

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###Members: Joel D. Rodriguez-Ortiz ###Discussion Questions

1. Use an identity channel to express how-much.
a. Describe how this makes the chart difficult to interpret.

We naturally use relative judgement to measure quantities. We can tell A is bigger than B or C and D are more or less the same, but we have a hard time determining precisely by how much. Using the identity channel to encode how-much completely obliterates our relative judgement. Where we would expect bigger quantities to look bigger and smaller quantities to look smaller,

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Just want to get rid of LICENSE warning in `bl.ocks.org`.