# Foundations of Computational Economics #16¶

by Fedor Iskhakov, ANU

## Visualization of data and solutions¶

https://youtu.be/dJdWVkSNNpc

Description: Principles and functions of graphics. Examples of visualization of economic models.

### Why visualize?¶

1. Convey ideas to others Ability to efficiently explain your idea/work to other busy people is crucial element of success in many fields
2. Check your own work Creating of new knowledge using computational tools requires absolute certainty in the code
3. Aggregate large amounts of information Makes it possible to get the big picture and the message behind it

### Matplotlib and other libraries¶

• matplotlib - Python library that abstracts from the graphical backbone of each system and ensures code mobility

Matplotlib thumbnail gallery https://matplotlib.org/gallery.html

#### Plan¶

1. Visualization examples from my own research projects
2. Links to compulsory online learning resources

#### Graphical objects¶

Extensive collection of objects to modify all aspects of the graphics

• figure - axes - subplots
• lines - polygons (patches)
• fill color and edge color
• annotations and other text

#### Types of plots¶

• bar - categorical data, histograms
• scatter - individual data points
• line - continuous measure
• area - dynamics of composition
• pie - static composition
• Sankey - flow diagram

#### How to choose the plot type¶

1. Number of variables to be represented
2. Type of variables
• continuous
• categorical
• ordered
3. What is the message of the graphics?

### General tips¶

1. Less visual clutter!
Every dot, line, shape and label has to convey useful information
2. Read the the manual and change the options
Defaults are good for quick and dirty preliminary runs only
3. Careful with 3D
Much harder to make clear
4. “Animations”
May be useful in cases when there are one too many dimensions in the data to visualize

#### Using many dimensions in one plot¶

• location (x,y,z)
• color
• line or marker style
• size
• animation
• multiple plots in a figure

#### Visual debugging and dashboards¶

Using visual representation to verify the code

• Seeing a bug in a plot is easier than in the code!

Dashboards are ideal for aggregation of large amounts of information

1. Calibration/estimation an moment matching
2. Monitoring computing resources