MEPX
Chapter 12 of 13All chapters
  1. 1What analysis is for
  2. 2Types of data
  3. 3Collecting and sampling
  4. 4Cleaning data
  5. 5Describing the middle
  6. 6Describing the spread
  7. 7Choosing a chart
  8. 8Correlation
  9. 9Getting to causation
  10. 10Hypothesis testing
  11. 11Traps and paradoxes
  12. 12Tools of the trade
  13. 13Communicating results

Chapter 12 of 13

Tools of the trade

Spreadsheets, SQL and code.

Picking one

Spreadsheets are fast for small, one-off work and hard to review. SQL is how you get data out of a database. Python and R handle repeatable analysis and anything statistical.

  • If you would have to do it twice, write it as code.
  • Version control matters as much for analysis as for software.

Reproducibility

Someone should be able to run your work and get your numbers, including you in six months. That means the raw data, the steps and the outputs are separate and the steps are written down.