Part 2 — Grade 9: Data wranglers¶
Spreadsheets → SQL → first Python → pandas.
Real data arrive messy and in large tables. Grade 9 teaches you to wrangle them: keep tables tidy, clean errors with a log, ask questions of a database in SQL, take your first steps in Python, and do in pandas what you did with pivot tables. You will also make charts in code and master rates — the arithmetic behind most news about Nepal.
| Unit | Title | Lessons | Project |
|---|---|---|---|
| 1 | Tidy data and spreadsheets | 3 | Spreadsheet fact sheet |
| 2 | Cleaning data | 4 | Clean it and log it |
| 3 | SQL basics on district data | 5 | Which districts are changing? |
| 4 | First steps in Python | 3 | My first data script |
| 5 | Tables in pandas | 4 | Same question, SQL and pandas |
| 6 | Charts that work | 3 | One chart, one claim |
| 7 | Percent, rate and per-capita | 3 | Rate detective |
| 8 | Grade 9 project: which districts are changing? | 2 | flagship project |
Tracks: Units 1, 2 and 7 work with a spreadsheet (Track A); Units 3–6 need computers (Track B: SQL and Python in the browser, offline). Schools without a lab can run Unit 3 "unplugged" with printed cards.
Pacing: 27 lessons + projects ≈ 42 periods.
Key idea of the year: the same question can be answered with a pivot table, an SQL GROUP BY and a pandas
groupby — the tools change, the thinking does not.