L02 WIP

00.value-of-dataviz/slides.md

@@ -335,7 +335,7 @@ Use of Altair is **strongly** recommended, but other libraries allowed.
 
 ---
 
-## Acknowledgements
+## Acknowledgements & References
 
 Thanks to Alex Hale, Andrew McNutt, and Jessica Hullman for sharing their materials.
 

01.gog-altair/slides.md

@@ -6,9 +6,9 @@
 
 ## Today
 
-- Grammar of Graphics
-- Types of Data
-- Intro to Altair
+- What is a **grammar of graphics** and how do we use it in practice?
+- What **types of data** do we encounter, and how does that affect visualizations?
+- Introduction to **Altair**
 
 ---
 

02.perception-and-color/slides.md

@@ -0,0 +1,211 @@
+---
+theme: custom-theme
+---
+
+# Perception & Color
+
+## CAPP 30239
+
+---
+
+## Today
+
+- What matters most when creating a visualization?
+- How does human **perception** factor into visualization design?
+- Understanding **color**, and computational representations of it.
+
+---
+
+## What is the most important question when creating a visualization?
+
+---
+
+## What is the most important question when creating a visualization?
+
+<ul>
+<li><s>Where will the data come from?</s>
+<li><s>What type of chart do I use?</s></li>
+<li>Who is the audience?</li>
+</ul>
+
+---
+
+## Audience First
+
+- Who are you presenting to?
+- How familiar are they with the data?
+- What is their numerical & visualization literacy?
+- Via what medium will they receive the information?
+- What are you trying to do? (Persuade, Inform, Inspire?)
+
+*Only now can we start thinking about data and presentation.*
+
+---
+
+## Perception
+
+- **Selective** - We can only pay attention to so much.
+- **Patterns** - Our brains are pattern-matching machines, audience will benefit from intentional patterns & be distracted by unintentional ones.
+- **Limited working memory** - We hold a very limited set of information in our minds at once.
+
+---
+
+## What do you see?
+
+<div class="container">
+<div class="col">
+
+![](example1a.png)
+
+</div><div class="col">
+
+```python
+alt.Chart(random_df).mark_point().encode(
+    alt.X("a"),
+    alt.Y("c"),
+    alt.Color("b"),
+    alt.Size("c"),
+    alt.Shape("a:N"),
+    alt.Fill("b"),
+    alt.Opacity("b"),
+) 
+```
+</div>
+</div>
+
+---
+
+## What do you see?
+
+<div class="container">
+<div class="col">
+
+![](example1b.png)
+
+```
+alt.Chart(random_df).mark_line().encode(
+    x="a",
+    y="c",
+)`
+```
+
+</div>
+</div>
+
+---
+
+## Effectiveness Revisited
+
+![width:800px](effectiveness.png)
+
+---
+
+<div class="container">
+
+<div class="col">
+
+**Altair Channels**
+
+- Position (`X, Y`)
+- Angle (`Angle`)
+- Area (`Radius`, `Size`)
+- Hue, Saturation (`Color`)
+- Texture (`Opacity`, `Fill`)
+- Shape (mark type, `Shape`)
+</div>
+
+<div class="col">
+
+**What about?**
+- Length
+- Slope
+- Volume
+- Density
+- Connection
+- Containment
+</div>
+</div>
+
+---
+
+**Derived Properties**
+
+
+- Length/Area - size of bars (`X`, `Y`)
+- Slope & Density - affected by scale
+- Connection - ex. layering of lines w/ points
+- Containment - achieved with layering
+
+What about *volume*?
+
+---
+
+## Stevens' Power Law
+
+Stevens (1975): Human response to sensory stimulus is characterized by a power law with different exponents with different stimuli. 
+
+perception = (magnitude of sensation)<sup>a</sup>
+
+Smaller <sup>a</sup> exponent: harder to perceive changes.
+
+Stevens measured values of a by exposing people to varied stimulus and asking them to compare magnitudes.
+
+---
+
+
+<div class="container"><div class="col">
+
+![](stevens.png)
+
+</div><div class="col">
+
+
+| Continuum | Exponent |
+|-|-|
+| Color Brightness| 0.33-0.5 |
+| Smell| 0.6 |
+| Loudness | 0.67 |
+| **Depth Perception** | 0.67 | 
+| Area | 0.7 |
+| 2D Planar Position | 1.0 |
+| Warmth | 1.3-1.6 |
+| Color Saturation | 1.7 |
+| Electric Shock | 3.5 |
+
+</div></div>
+
+---
+
+## 3D Graphs
+
+![](stunning-3d-chart.jpg)
+
+---
+
+![](datavizproject.png)
+
+---
+
+![](3d-scatter.png)
+
+---
+
+## Instead of 3D Graphs
+
+- Find other channels: hue & size are good candidates.
+- Combine different dimensions into side-by-side 2D graphs.
+
+TODO: example of 2D decomposition of a graph
+
+---
+
+## Color
+
+---
+
+## Acknowledgements & References
+
+Thanks to Alex Hale, Andrew McNutt, and Jessica Hullman for sharing their materials.
+
+- https://www.math.csi.cuny.edu/~mvj/GC-DataViz-S23/lectures/L6.html
+- https://en.wikipedia.org/wiki/Stevens%27s_power_law

custom-theme.css

@@ -0,0 +1,11 @@
+/* custom-theme.css */
+/* @theme custom-theme */
+
+@import "default";
+
+.container {
+  display: flex;
+}
+.col {
+  flex: 1;
+}