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Introduction to data visualization
========================================================
author: John M. Drake & Ana I. Bento
date:
autosize: true
Why this workshop?
========================================================
"Coding is a basic science skill"
- Dr. James Olds, Assistant Director for Biological Sciences, National Science Foundation
Overview
========================================================
- Data visualization
- Writing computer programs
- Data wrangling
- Modeling
- Project management
R/RStudio
========================================================
***
<http://www.r-project.org/>
Why look at data?
========================================================
How to look at data?
========================================================
- Scatterplot
- Box-and-whisker diagram
- Barplot
- Map
- Network
A grammar of graphics
========================================================
Grammar - The fundamental principles or rules of an art or science
- OED, quoted in Wickham (2010)
***
A plot
========================================================
Consists of
- A dataset and mappings from *variables* to *aesthetics*
- One or more *layers*
- A *scale* for each mapping
- A *coordinate system*
- A *facet specification* (usually for multi-panel plots)
A layer
========================================================
Consists of
- Data and aethetic mapping
- A statistical transformation
- A geometric object
- Position adjustment
***
A graphing template
========================================================
`ggplot(data=<DATA>) + <GEOM_FUNCTION>(mapping=aes(<MAPPINGS>))`
```{r, fig.width=6, fig.height=4}
library(ggplot2)
ggplot(data=diamonds) +
geom_bar(mapping=aes(x=cut, fill=clarity))
```
Aesthetics
========================================================
An *aesthetic* is a visual property attached to some data in a plot, e.g.
* Size
* Shape
* Color
```{r, fig.width=6, fig.height=4, echo=FALSE}
library(ggplot2)
ggplot(data=diamonds) +
geom_bar(mapping=aes(x=cut, fill=clarity))
```
Exercises
========================================================
**Notes**
- This workshop addresses visualization, programming, and data wrangling separately, but they're inevitably intertwined. You will have to do some data wranging (e.g. with the package `lubridate`) and minor programming (e.g. assignment operation) to complete this exercise. This may be frustrating. **Stick with it -- it's worth it!**
- A good strategy: Find an example -> Modify -> Compute. Repeat.
- Google is very helpful (especially **Stack Overflow** and **Cross Validated**)
References
========================================================
Wickham, H. 2010. A layered grammar of graphics. *Journal of Computational and Graphical Statistics* 19:3–28