# Exploratory data analysis

## Learning objectives

* Define *exploratory data analysis* (EDA) and types of pattern exploration
* Demonstrate types of graphs useful for EDA and precautions when interpreting them
* Practice exploring data

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### Approaches to EDA

- Look for _variation_ and _covariation_
- Don't need to have pretty charts (for publishing purposes, you want to add titles, legends, themes etc.)

#### Variation
- dispersion of one variable
- Histograms
- w/ Rug plot gives 1D marginal distributions (best used with smaller, high-variance datasets)
- Bin width is important!
- Continous variables
- Bar Chart
- Categorical variables

#### Covariation
- multiple variables (x and y axis)
- Categorical on x, continuous on y -> boxplot
- Two continuous -> scatterplots
- Could also facet or layer variables on a single graph
- When layering, use different channels to distinguish patterns