▾	Steps: Data Science
	•	Loading dataset
	•	Viewing data
	•	Splitting data
	▾	Modifying data
		•	Set as factor
		•	Transform
	•	Visualising data
	•	Computing descriptive statistics
	•	Checking for assumption
	•	Building model
	•	Performing regression
	•	Performing significance test
	•	Performing post-hoc test
▾	Tasks: Programming
	Process Codes
	•	Writing documentation
	•	Using GUI
	•	Refactoring code
	•	Cloning code
	•	Modifying cloned code or modifying arguments of code
	•	Moving code
	•	Commenting out code
	•	Deleting code
	•	Creating new code/other files
	•	Searching the web/resources
	•	Using version control
	•	Debugging code
	▸	Executing code
		Happens too frequently—ignoring.
	•	Comparing results
	•	Viewing results
	•	Loading libraries
	•	Viewing help
	•	Switching files
		Happens too frequently—choosing this selectively. 
	•	Viewing history
▾	Tasks: Exploratory Workflow
	Process Codes
	•	Generating insights/hypothesis
	•	Preparing code for dissemination
	•	Creating alternative
	•	Searching code for confirmation code
	•	Searching code for new explorations
	•	Searching for previous code 
	•	Creating confirmation code
	•	Pre-empting approach
▾	Findings from eclectic coding
	▾	Semantics
		•	Significance test results
		•	Assumption test results
		•	Data table
		•	Plots
		•	External resources
	•	Data changes -> alternative analysis
	•	Blocks to organize code
	▾	Rationalising analysis
		•	See semantics
		•	Predetermined
		•	Results (assumption tests mostly)
	•	Tracking insights
		See insights memo
	▾	Problems
		•	Missing dependencies
		•	Can’t find code that produced an insight
		•	Sparse documentation
		•	Code won’t run after cloning
		•	Rerun