Schedule
Daily Organization
The data structure for each class meeting below is a class section with a rough plan for what we intend to do with our meeting time; and other sections (not necessarily all of them every time) for items to read before (or watch in the case of video links); due in class for assignments that are due at the start of class (because they will be the subject of discussion in class) and do after class.
Two hours a week is not a large amount of time for a developer to spend in meetings, rather than coding, reading, or doing other stuff. We will use some of this time like development meetings: going over specifications (assignments), making tasks (writing down acceptance criteria), having detailed code reviews of various forms, and discussing blocking issues and potential solutions.
You should be prepared at any class to give a very brief summary of your status on all the projects you're working on. Knowing and alerting others that you are stuck on something is vital.
2014-09-04:
During class:
Overview, principles, goals, objectives.
After class:
- Make a Github account if you don't already have one
- Fork the repo — your assignments will be in the form of pull requests
- Git intro
- Git workflow for beginners
- Git branching game!
- Git intro
- Another intro video
- Forking
- Training and Guides
- Sharing and Collaborating
2014-09-11:
Read, watch, peruse before class:
- Gelman and Unwin (recommended: responses to it)
- Yann LeCun on Data Science
- Tufte ch. 1–3
During class:
- Lab: gentle R intro, by Yang & Huei-yi
- Lab: gentle git intro, by Malecki
2014-09-18: Making graphics; formats and tools; theory
Read, watch, peruse before class:
- Grammer of Graphics skim at least ch. 1,2,5 (SpringerLink)
- Data science workflow
- Climate change, crowbars, and strikeouts
- Heer et al, Visualization Zoo (note: fixed link)
Due before/in class:
Homework 1— Rmarkdown, ggplot2, and github
During class:
- Code review of Homework 1
- knitr doc
- discuss reproducible research, publishing replication data, versioning, &c
2014-09-25: color
Read, watch, peruse before class:
- HCL color space
- I want Hue
- Semantically resonant colors
- Rec: Color naming
- Rec: HCL in R
- Rec: Quantitative and Ordinal scales in D3
- Rec: Motley
2014-10-02: Data are ugly
Read, watch, peruse before class:
During class:
Strategies for dealing with ugly data; "the 'csv' api"
2014-10-09: R, ggplot2
Read, watch, peruse before class:
During class:
- R Packaging
- gglot2 book (SpringerLink)
- ggplot2 doc web site
- ggplot in Python
- ggplot2 data contract
- Building R Extensions
2014-10-16: Mapping
Read, watch, peruse before class:
- The rest of Tufte, VDQI
- Roth et al., Value-by-Alpha Maps
- Bostock, Let’s Make a Map
- Choropleth
- Rmaps
- Malecki's quick Notes on maps
During class:
Lab: Choropleths
2014-10-23: Gentle introduction to D3; Beaker
Read, watch, peruse before class:
- D3 paper
- Murray, Interative data Visualization for the Web (O'Reilly Safari)
- beaker notebook / source
Due before/in class:
Homework 3, survey analysis
During class:
Gentle introduction to d3; demo and discussion of Beaker Notebook
2014-10-30: Interactivity and Animation
Read, watch, peruse before class:
2014-11-06: Dealing with text
Read, watch, peruse before class:
- Spolsky, The Absolute Minimum Every Software Developer Absolutely, Positively Must Know About Unicode and Character Sets (No Excuses!)
- Shaw, The (mostly) true story of helvetica and the new york city subway (The book is excellent, by the way, as is the documentary Helvetica)
- Strings – Dive into Python3
- Shady Characters (blog and book both recommended)
During class:
Lab, working with text
2014-11-13: Social/Network Visualization
Read, watch, peruse before class:
Due before/in class:
Homework 3— Interactive data application
During class:
Lab: Gephi/Network viz