Skip to content

Latest commit

 

History

History
247 lines (161 loc) · 5.76 KB

lecture11.md

File metadata and controls

247 lines (161 loc) · 5.76 KB
Raw
title layout include_vega
Lecture 11
lecture
true

Data Visualization

## Matthew Turk ## Spring 2018 ## Lecture 11

Warm-Up Activity

  1. What is the visualization trying to show?
  2. What are its methods?
  3. What are the strengths / weaknesses?

https://vimeo.com/239582792

Last Time

  • Maps
  • Idyll

Today

  • Iterative Design
  • Assignment Update
  • Final Project

Three Classes of Visualizations

  1. Viz for Self
  2. Viz for Peers
  3. Viz for Others

Iterative Design: Viz for Self

Let's talk about exploration.

What are characteristics of data that would influence how you visualize it?

Iterative Design: Viz for Self

What do you want to get out of visualization for yourself?

  • Do you want to find meaning?
  • Do you want to understand how to guide further visualizations?
  • Is the story you want to tell already known to you?
  • What shortcuts can you take?

Iterative Design: Viz for Peers

When you change your focus to visualize for others, you have to make different choices about representing the information.

What are some things you might change?

Iterative Design: Viz for Peers

To design a visualization for your peers, you need to step back and think about the common shared language you have with them.

  • What do they know?
  • What conventions will they assume?
  • Are they able to fill in the blanks of information?

Iterative Design: Viz for Others

The hardest type of visualization is for those about whom you know very little.

What common basis can we make for these visualizations?

What is our responsibility with visualizations such as these?

Final Project

Your final project is due on April 30.

That is three weeks.

You will have three components:

  1. Viz for Self (Due April 16)
  2. Viz for Peers (Due April 23)
  3. Viz for Others (Due April 30)

Final Project: Part 1

This will be graded individually. Due by class on Monday, submitted via Moodle. Submit in a Jupyter notebook.

  • Organize yourselves into groups of 4
  • Identify a dataset to explore.
  • Explore the dataset in a Jupyter notebook. Do not delete any cells.
  • Summarize the characteristics of the dataset in words: what does it represent, what are the fields/columns/rows, what data types are they, etc

Final Project: Part 1 (cont)

Your datasets need to be submitted as well. To do this, include this information in your Jupyter notebook:

  • What is the "name" of the dataset?
  • Where did you obtain it?
  • Where can we obtain it? (i.e., URL)
  • What is the license of the dataset? What are we allowed to do with it?
  • How big is it in file size and in items?

Final Project: Part 2

This will be graded per group. Submit in a Jupyter notebook.

  • Using your dataset, generate visualizations that explore the data in a guided way.
  • Your first component was focused on exploring the data in an unguided way. This component is about visualizing the data in a guided way.
  • Construct visualizations that explore each aspect you identified, with discussion and descriptions.
  • If you can identify improvements to the visualizations that come from interactivity, implement that.
  • The visualizations should utilize visual language relevant for "Viz for Peers."
    • Each and every plot should contain all relevant information: appropriate units, labeling, etc
    • Annotate and narrate particular pieces of interest (if there are any)
    • Use standard visual representations and augment these if necessary

Final Project: Part 3

You will submit this as your final project and will present it to the class.

You may submit one or more of the following items, but they must be in a repository that is rendered as HTML. More information will be coming shortly.

This component will include a "for others" visualization that is deeply narrative with appropriate interactive (or static) content and shared on a website.

Some possible ways to approach this:

  • Infographic
  • Idyll
  • Jupyter notebook
  • Raw HTML

Assignment Three

You should have access to assignment three. It is short. It is due by midnight next Monday night.

Idyll Again

Let's return to Idyll. Go to your Jupyter Hub environment. Create a terminal.

source activate /home/shared/sp18-is590dv/conda_envs/is590dv-default/
yo idyll

This will autogenerate a project for you. Go into that directory and type npm start.

This will watch for changes and rebuild. It tells you that you can connect to it in a web browser but this is a lie. You have to browse to the location in your tree view and then go to the directory build and choose index.html in the Jupyter main page.

Breakout: Birth Names (Part 1)

Last week, we talked about how one would represent a birth name browser.

What did you come up with?

Breakout: Birth Names (Part 2)

On the Jupyterhub, you have access to a names directory:

/home/shared/sp18-is590dv/data/names

This has a bunch of files, with the counts of birth names per year and categorized by sex assigned at birth.

Breakout: Birth Names (Part 3)

You are to break into groups and decide how to proceed. We need to:

  1. Explore the data
  2. Generate an interactive visualization
  3. See if we can get it into Idyll

Idyll and Data

What are the barriers to using Idyll with really big, unfiltered data?