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##Name: Joel D. Rodriguez-Ortiz Above are the results of working through the D3 tutorial. Refreshing serveral times will produce the same bar graph with randomized data.
A sampling of the randomized data was logged, to produce the same bar graph in R (shown below).
###R Source Code
###Group Members: Joel D. Rodriguez-Ortiz
#Part 1A - Task Analysis
###Olympic Data
The visualization being considered for this part is my ICW1.
###What?
##Name: Joel D. Rodriguez-Ortiz
##Tableau Charts
###Chart 1
The dataset selected for this analysis is the 2015 College Football Statistics.
Domain Specific:
The rushing statistics of various players are provided. A rank is given to each player based on
Rushing Yards / Rushing Attempts. Other domain specifics characteristics are provided such as
player name, school, conference, rushing touchdowns, touchdowns from scrimmage, etc.
| Just want to get rid of LICENSE warning in `bl.ocks.org`. |
###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,
#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
##Name: Joel D. Rodriguez-Ortiz
##Node-Link Diagram Insights
Insights gained from this graph include:
