Australian Crop Report No. 185 (February 2018) — Grain and Oilseed Prices by Quarter
One row per price series in the prices table of ABARES' Australian Crop Report No. 185 (February 2018), covering wheat, barley, grain sorghum, oats, corn (maize), oilseeds (canola, rapeseed, soybeans) and pulses (lupins, chickpeas, field peas). Each series is a domestic, export or international quote (e.g. 'Domestic: feed, del. Sydney', 'International: US no. 2 hard red winter, fob Gulf'); quarterly columns c_2016_q2 through c_2017_q4 hold average prices in Australian dollars per tonne (A$/t), where Q1=Jan-Mar through Q4=Oct-Dec, excluding GST. Frozen 29-row snapshot of a single report spreadsheet: all columns are stored as strings and include an embedded unit row ('A$/t'), blank commodity-group header rows and a trailing footnote row carried over from the original Excel layout.

Source: ABARES · connector code
Get this dataset on your machine
subsets sync --bundle medium clones the mid-size tiers as queryable local tables — use --bundle large for the widest tier
pip install subsetsiosubsets sync --bundle small # or medium, or largesubsets serve # search + SQL at http://localhost:8080Free and open — the data syncs straight from the public bucket, and search + SQL run entirely on your machine. See docs →
Query it locally
Full docs →subsets serve # local API on http://localhost:8080
curl -s -X POST "http://localhost:8080/query" \
-H "Content-Type: application/json" \
-d '{"sql": "SELECT * FROM \"abares-australian-crop-report-february-2018-no-185\" LIMIT 5"}'No account, no API key — the data syncs straight from bundles.subsets.io and every query runs on your machine. See the local API reference.