25 Recap @ 301

25.1 Previous lectures

Moving from programming to data science

• Basic types and variables
• The pipe operator
• Complex data types
• Data wrangling
  • Data selection
  • Data filtering
  • Data manipulation
  • Join operations
  • Table re-shaping
  • Read and write data

25.2 This lecture

Reproducibility in (geographic) data science

• What is reproducible data analysis?
  • why is it important?
  • software engineering
  • practical principles
• Tools
  • Markdown
  • RMarkdown
  • Git

See also: Christopher Gandrud, Reproducible Research with R and R Studio also available on GitHub