A Toolkit of Techniques

Dr. Nathaniel Cline

Agenda

1

A Toolkit of Techniques

2

Your Job

3

Choose Your Own Adventure

Scenario

  • imagine you work as an analyst in consumer credit risk management.

  • Once loans become 180 days past due, they are categorized as “Non-Performing Loans.”

  • Banks have to reserve money for these potential losses.

  • You’ve been asked to create a graph showing how Non-Performing Loan (NPL) volume compares to the Loan Loss Reserves over time.

R

So far we have focused on the R programming language, which has major advantages:

  • Imagine dealing with our county data set (3,000+ rows, 100+ columns) in Excel!

  • R can produce stunning graphics

  • Because R is useful but hard to learn, it is a rare and valuable skill

There is more than R

But, there are many more ways to not only create charts, but to make data meaningful (R may still be useful in getting data ready)

Today I’d like to talk about some of the ways we can can communicate data and then discuss your final projects

What else?

We often think of:

  • Infographics
  • Slide decks
  • Reports

Maybe now you are thinking of

  • Scrollytelling articles
  • Interactive charts

What else is there?

Video!

Webpage!

Laser Cut Food

Corporate Social Media

Board Game!

Buzzfeed Quiz!

Data Physicalization 1

Data Jewlery

Data Physicalization 2

Data Art Installations

Data Mural

Data Comics

And of course, if you’ve enjoyed R…

Create something

Remarkable

Rules

  1. Insightful, data-based story with a clear connection to the “American Dream” broadly interpreted (work with raw data)
  2. Presentation of that story with a well defined audience and goals
  3. Methodology write up
  4. Audience assessment tool
  5. Presentation of the project to our class

Steps

  • identify a topic and your audience

  • identify data sets

  • clarify the big idea

  • decide on a tool

  • execute!

  • collect feedback

Groups

  • In order to produce something remarkable it is likely that you will need to work with partners.

  • Some of you may already have partners in mind - others may not

  • If you have a sense of who you’d like to work with - email me by Friday

  • If you do not have a sense of who you’d like to work with - we will see if interests align.

Key Dates

  • Topic, audience and data set: 10/9

  • The big idea and proposed tool: 10/16

  • Final product: 11/27

How would you like to proceed?

  • Advanced R visualizations!

  • Data stories in a business/
    non-profit context

  • Creative data products

  • A secret 4th thing!

Let me know!

Econ 255 - Data Storytelling