Modern data visualization is largely a product of the sheer amount of data we produce.
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In part this is a function of the digitization of most of our lives.
15 years ago there was no data.gov, it has added 300k data sets since then.
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As technology advances, our data gets to be incredibly fine grained.
This is a sample of ride share rides over a six year period. Each pixel is a pick up or drop off.
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OK, there is **a lot** of data, but isn't that a **good thing**?
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"What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention, and a need to allocate that attention efficiently among the overabundance of information sources that might consume it."
~Herb Simon
_as quoted by Hal Varian. Scientific American, September 1995_
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## What is Visualization?
“... finding the **artificial memory** that best supports our natural means of perception.”
_[Bertin 1967]_
“Transformation of the symbolic into the geometric”
_[McCormick et al. 1987]_
“The use of computer-generated, interactive, visual representations of data to **amplify cognition**.”
_[Card, Mackinlay, & Shneiderman 1999]_
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## Information Visualization
"The use of computer-generated, interactive, visual representations of (abstract) data to **amplify cognition**."
What does it mean to amplify cognition?
Why do we often seek visualizations?
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## Why do we create visualizations?
- What visualizations have you created?
- What visualizations have you seen that you remember?
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## Reasons for Data Visualization
- Means of reasoning about large quantities without reduction/over-simplification.
- Assist in gaining unique insights into data: clustering, correlation, trends, etc.
We will be learning Altair, which generates Vega JSON, which in turn is drawn using D3.
D3 underpins dozens of other charting libraries as well, and D3's own documentation says:
D3 makes things possible, not necessarily easy; even simple things that should be easy are often not. To paraphrase Amanda Cox: “Use D3 if you think it’s perfectly normal to write a hundred lines of code for a bar chart.”
Learning D3 both requires working in an unfamiliar environment (JavaScript) and with a very unique style of programming based around their concept of the ["data join"](https://d3js.org/d3-selection/joining), which requires a decent understanding of the HTML Document Object Model.
So, if you are here to learn visualization, I think that it is fair that you can succeed in this class without putting yourself through that.
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## Course Structure
- **Lecture and Discussion**: Introduce and explore key concepts, mostly focused on theory.
- **Readings**: Supplement course materials with more examples, technical tutorials.
- **2 "minor" assignments: Altair & D3** - Gain practice with commonly used tools in a structured setting.
- **Projects**: Learn to explore a topic on your own from conception to practice. Leave here with a portfolio you can show off.
