- npm install
- node data.js
- open local server to index:html
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https://canvas.newschool.edu/courses/1525001/assignments/8211912
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Dataset:
https://www.basketball-reference.com/playoffs/series.html https://teamcolorcodes.com/nba-team-color-codes/
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combine sports data w/
- underdog vs favorite?
- team/fan base sentiment?
- mascots?
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could keep it as smaller focus first (eg one year)
- then could expand across years/sports
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doesn't have to be just code, can explore other mediums (photoshop, AI, etc)
this exercise
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*Alternate dataset if you choose - Census data
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could iterate by end of semester and maybe revisit grade for projects!
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Project Approach Answer project questions as you go along
- Audience questions
- Check + prep data (acquire, parse, filter)
- Mine/explore/sketch/iterate several simple graphics, re: stories (same or diff?), pick one
- Code initial draft (pseudo first?)
- Refine/declutter/clean/annotate/clarify (color, labels, titles, legend, summary, etc)
- Interactivity (more than tooltips, eg: scrolling)
- Share
Project Questions
- Why are we doing this?
- What are questions that you want to explore with this visualization?
- What are you hoping to achieve?
- What will I be looking at(title)?
- Who are we targeting?
- How is the end product going to be used?
- How are we publishing?
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- What data do we have available?
- Which quantitative dataset is used?
- What are the properties of the data set?
- How many data points
- What's the quality of the data?
- Which other existing materials should we take into account?
- Which constraints do we have?
- use R to explore data?
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- Which visualization method is used and why?
- What does the visualization enable?
- Is this a static visualization? Is it interactive?
- color: Is it intentional and intuitive? data decodable by audience?
- legends, annotations
- clear text hierarchy?
- link to data?
- links
https://www.data-to-viz.com/ https://www.d3-graph-gallery.com/ https://observablehq.com/@d3/gallery https://d3-legend.susielu.com/ https://colorbrewer2.org/
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- Who else is doing something similar?
- Abstract/summary/about, re: methodolgy? (1-2 pars)
- What were your considerations?
- What tools did you explore?
- What challenges did you run into?
- How did you iterate?
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Project Concept 1. - Who's winning? - Colors of underdog winners?
- inspo:
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https://www.d3-graph-gallery.com/ https://python-graph-gallery.com/ https://www.r-graph-gallery.com/ https://bl.ocks.org/ https://observablehq.com/@d3/bubble-map https://bost.ocks.org/mike/bubble-map/ https://www.d3indepth.com/scales/ https://d3-legend.susielu.com/ https://www.d3-graph-gallery.com/graph/bubble_tooltip.html https://www.d3-graph-gallery.com/graph/interactivity_tooltip.html https://www.d3-graph-gallery.com/graph/line_select.html
- Methodology influences:
- Ben Fry, Amanda Cox, Alberto Cairo, Mike Bostock