SO FAR

Coming Up

• Mondays in person, Wednesdays on Zoom
• Wed March 8: No class meeting, Hum 354 11:30-1 Shirts Powdered Red discussion
  • Zoom stream and recording available
• Final project: Think about the process and methods you enjoy, not the topic

Why all the different assignments???

• I select data for its problems
• Different data has different needs
• Human readable vs too big to read
• General principles, not specific mechanics (so you can ask Prof. Google later)

Prepare

Explore

Analyze

Present

Data work is a feedback loop

• Exploration will lead to questions
• Exploration reveals preparation issues
• Preparation differs depending on the question
• Content model enables certain questions
• The content model can change depending on the question

Abstraction

• Everything has a structure (HTML, data table)
• The same structure can be represented in different ways (CSS, data visualization, fruit baskets)
• Data is a representation, not the thing
• Sections of the data can be represented abstractly
  • (File paths, battleship, ranges, facets, filters, parts of text)

Data -> Questions -> Data

• Abstraction means stepping back to ask what you're trying to do, not getting lost in the weeds
• Data type determines what you can do with it
  • Text vs Numbers, Discrete vs Continuous, Categorical vs unstructured

Principles of Cleaning

• Keep an untouched original
• Keep a record of your cleaning (export and save steps when done)
• Create a controlled vocabulary in categorical text
• Explore and find outliers--typos or data?
• One column, one purpose
• One row, one purpose
• One cell, one purpose
• Different questions will need different cleaning
• Only you know when you're done!

Intro to Dataviz

Nominal, Textual, Qualitative or Dimensional

• Textual
• Usually categorical
• Usually mutually exclusive
• Can't be quantified
• Can have a controlled vocabulary
• Can't usually be ordered
• Fruit boxes, marriage status, item type, hair color

Ordinal, Numeric, Quantitative or Measurable

• Numeric
• Usually can be counted or measured
• Can't have a controlled vocabulary
• Orderable

Discrete Measure

• Limited number of possible values
• Whole, non-divisible items
• Countable but not measurable
• Usually orderable
• Dates (1808 vs 1809)
• Counts of items (5 children, 4 beavers, 3 skittles, 1 keg)
• Can find a median, average, and sum

Continuous Measure

• Numeric
• Infinite number of possible values
• Can't have a controlled vocabulary
• Always orderable
• Weight, financial cost, distance, time
• Can find a median or average but can't find a sum (average weight of people in class vs total weight of people in class)