Data Appendix

Every dataset used in this book, in one place. The files live in the book’s practice/data/ folder; click a file name to download it. Put downloaded files in your own project’s data/ folder, untouched, and do all your work in a script.

The datasets fall into two groups. The first group is real data, drawn from the agencies cited with each entry. The second group is synthetic data constructed for this course; those files look like real farm records but the values are generated, so nothing in them describes an actual farm.

Real datasets

Saskatchewan RM crop yields

Average yields for every Saskatchewan Rural Municipality. Source: Saskatchewan Crop Insurance Corporation (2025a).

  • rm_yields_1990_2025.csv – the long form: 71,104 rows, one per RM-year-crop, for eight crops from 1990 to 2025. Columns Year, RM, Crop, Yield, Unit. Lentils are recorded in pounds per acre and every other crop in bushels per acre; the Unit column says which. Used in the Module 1 and Module 2 test banks.
  • rm_canola_yields_1990_2025.csv – the canola rows only, for the Module 2 test bank’s summary-statistics questions.
  • rm_yields_1990plus.csv – the wide form: 10,649 rows, one per RM-year, with one column per crop. Used in Module 1, where the wide layout suits PivotTables.
  • rm_yields_2015_2024.csv – a wide subset (2,950 rows, ten years, six crops) used in Modules 3 and 4.

Saskatchewan variety yields

Variety-level yields and acres by SCIC risk zone. Source: Saskatchewan Crop Insurance Corporation (2025b).

  • sask_variety_yields.csv – 14,700 rows, one per risk-zone-crop-variety-year, risk zones 1 to 23, 2021 to 2025. Columns Risk_Zone, Crop, Variety, Year, Acres, Yield. Suppressed observations have missing acres and yield. The charts in Module 4 and the AI exercises in Module 5 are built from this file.
  • sask_barley_2025.xlsx / sask_barley_2025.csv – 2025 barley varieties, provincial acres and average yield. The workbook version has the title rows and multiple sheets that Module 3’s Excel-import section works through.

Manitoba wheat variety yields

MASC’s variety-level spring wheat yields by municipality, 2020 to 2025. Source: Manitoba Agricultural Services Corporation (2025).

  • mb_wheat_varieties.csv – 5,358 rows, one per municipality-variety-year. Columns Year, Municipality, Variety, Farms, Acres, Yield_bu_ac, Reported. Where too few farms grew a variety the row is suppressed for privacy: Reported is FALSE and the numeric columns are missing. Used in the Module 1 and Module 2 test banks.
  • mb_wheat_reported_2020_2025.csv – the 2,398 reported rows only.

Canada field crops

Statistics Canada’s provincial estimates of seeded area and yield. Source: Statistics Canada (2025).

RM lookup table

  • rm_lookup.csv – one row per Saskatchewan RM (296 rows): name, census division, 2021 population, and the nearest of sixteen weather stations with its distance. Compiled for this course from Statistics Canada 2021 Census counts. Used in Module 3’s merging chapter.

Station precipitation

  • station_precip.csv – May-to-August precipitation for sixteen Saskatchewan weather stations, 2015 to 2024 (160 rows), with a count of days missing a reading. Compiled from Environment and Climate Change Canada historical climate records. Used in Module 3’s merging chapter.

Synthetic datasets

Canola trial

  • canola_trial.csv – 120 canola fields with fertilizer rate, growing-season rainfall, variety, and yield. Three fields have missing rainfall values, on purpose. This is the running example in Module 2’s data chapters and returns in Modules 3 and 7.

Field yields

  • field_yields.csv – sixty hypothetical canola fields with region, variety, acres, yield, and seeding date.

Saskatchewan wheat fields, 2025

  • sask_wheat_2025.csv – field-level wheat records with soil zone, variety, acres, yield, protein, and seeding rate. Constructed for the course; the soil-zone yield differences are patterned on real ones. Used in Module 6’s reporting examples and the Module 2 practice pages.

Grain deliveries (messy)

  • grain_deliveries_messy.csv – elevator delivery tickets constructed to contain the problems Module 3’s cleaning chapter works through: inconsistent crop names, stray spaces, impossible values, duplicates.

Elevator tickets

Crop prices

  • crop_prices.csv – a handful of illustrative crop prices used in Module 5’s examples. Not market data.