Data Viz Considerations

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## .base_color[Data Viz]

## .base_color[Considerations]

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### .navy[Kelly McConville]

#### .navy[ Stat 108 | Week 1 | Spring 2023]

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## Announcements

* No section, no lecture quiz, no p-set this week.
* Only I will be running office hours this week at the following times:
    + Wednesday 1:30 - 3:00 pm in Science Center 316
    + Thursday 10:30 - 11:30 am in Science Center 316 (this week only)
* Hop into our course Slack

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## Week 1 Goals

**Day 1 Lecture**

* Course overview

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**Day 2 Lecture**

* Develop language to talk about the components of a graphic

* Discuss considerations for good graphical design

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## Let's start with the language we will use to describe the components of a graph:

## The Grammar of Graphics

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## Background

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Leland Wilkinson wrote a book called "The Grammar of Graphics"

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As part of his PhD in Statistics at Iowa State, Hadley Wickham wrote the `R` package `ggplot2`, which we will use to create static graphs.

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## The Grammar of Graphics

* **data**: dataset that contains the data

* **geom**: geometric shape that the data are mapped to
    + point, line, bar, text, ...
    
* **aes**thetic: visual properties of the **geom** 
    + x position, y position, color, fill, shape
    
* **coord**: coordinate system
    + Cartesian, polar, geographic
    
* **scale**: controls how data are mapped to the visual values of the aesthetic
    + EX: particular colors, linear

* **guide**: legend to help user convert visual display back to the data

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## Geoms versus Names

* What are the names of these graphs?

* Focus on the **shapes** (i.e. geoms) and how the variables are **mapped** to those shapes.

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## [Data Viz Example](https://www.nytimes.com/2019/04/11/learning/whats-going-on-in-this-graph-april-17-2019.html)

* Let's practice deconstructing this graph using the grammar of graphics.

.left-column[ 
* Geom(s)?
* **Aesthetic**s of the **geom**?
    + Mapping of variables?
* Coord?
* Scales?
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## [Data Viz Example](https://www.nytimes.com/interactive/2018/01/23/climate/trump-offshore-oil-drilling.html)

.left-column[ 
* Geom(s)?
* **Aesthetic**s of the **geom**?
    + Mapping of variables?
* Coord?
* Scales?
]

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### Choices

For most data, there won't be just **one** way to graph it. Decisions to be made:

* What **geom** to use
    + Point, line, bar, ...
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* For a given geom, how to map variables to its **aesthetics**
    + Size, location, color, ...
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* For each **aesthetic**, what scale to use
    + Linear, diverging colors, ...
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* For the graph, what **coordinate system** to use
    + Cartesian, polar

Let's discuss some considerations that can help guide these decisions.  But...

> "Data visualization is part art and part science. The challenge is to get the art right without getting the science wrong and vice versa." -- Claus Wilke

#### Recommendation: Try out different options and make sure to iterate!

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### Consideration: Consider variable type when picking the aesthetic mapping.

### What aesthetic options do I have at my disposal?

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##Aesthetics: [Position/location](https://www.nytimes.com/2019/04/11/learning/whats-going-on-in-this-graph-april-17-2019.html)

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##Aesthetics: [Length](https://www.nature.com/articles/d41586-019-03305-w)

Hat tip: Grace Benson

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##Aesthetics: [Area](https://www.nytimes.com/2022/04/07/learning/whats-going-on-in-this-graph-april-13-2022.html)

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##Aesthetics: [Angle](https://www.nytimes.com/2018/09/25/learning/whats-going-on-in-this-graph-sept-26-2018.html)

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##Aesthetics: [Shapes](https://clauswilke.com/dataviz/telling-a-story.html/)

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##Aesthetics: [Color Shade](https://fivethirtyeight.com/features/how-you-view-climate-change-might-depend-on-where-you-live/)

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##Aesthetics: [Color Hue](https://www.nytimes.com/2022/03/03/learning/whats-going-on-in-this-graph-march-9-2022.html)

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