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.

abares-australian-crop-report-february-2018-no-185·8 columns·5 KB·Creative Commons Attribution 4.0 International (CC BY 4.0)·updated 2mo ago
ABARES

Source: ABARES · connector code

Schema

cropVARCHAR
c_2016_q2VARCHAR
c_2016_q3VARCHAR
c_2016_q4VARCHAR
c_2017_q1VARCHAR
c_2017_q2VARCHAR
c_2017_q3VARCHAR
c_2017_q4VARCHAR

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subsets sync --bundle medium clones the mid-size tiers as queryable local tables — use --bundle large for the widest tier

pip install subsetsio
subsets sync --bundle small # or medium, or large
subsets serve # search + SQL at http://localhost:8080

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Query it locally

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Bash
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.