SQL plus Python and pandas for Analysis Workflows

About 75-95 minutes of guided work.

By the end of this module you can decide what belongs in SQL and what belongs in pandas, write queries that cannot be broken by their inputs, catch a silent type change on load, and produce a notebook that reruns to the same answer.

Units

1. Unit 11.00: Deciding what to aggregate in SQL versus pandas
2. Unit 11.01: Parameterised queries and why concatenation breaks
3. Unit 11.02: Checking dtypes and row counts after loading
4. Unit 11.03: Keeping SQL in reviewable files, not buried in code
5. Unit 11.04: Making the notebook rerun cleanly top to bottom

Module work

• Activity
• Knowledge check
• Summary