Australia - Average Weekly Earnings

One row is an SDMX observation for this ABS dataflow, with OBS_VALUE broken down by the table's dimensions. Survey conducted biannually, in May and November, to measure the level of average gross weekly earnings associated with employees. While AWE is not designed to produce movement in earnings data, the frequency of collection supports a time series of these level estimates. Unit of measure: AUD. Geographic coverage: Australia/State. Catalogue number: 6302.0 Profiled coverage: geographic coverage Australia/State. Current profile has 35,517 rows. Dimension values are ABS SDMX codes; use the source code lists for full labels where a label column is not present.

australian-bureau-of-statistics-awe·14 columns·197 KB·Creative Commons Attribution 4.0 International·updated 8d ago
Australian Bureau of Statistics

Source: Australian Bureau of Statistics · connector code

Schema

dataflowVARCHAR
measureBIGINT
estimate_typeBIGINT
sexBIGINT
sectorBIGINT
industryVARCHAR
tsestBIGINT
regionVARCHAR
freqVARCHAR
time_periodVARCHAR
obs_valueDOUBLE
unit_measureVARCHAR
obs_statusVARCHAR
obs_commentVARCHAR

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

Free 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 →
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 \"australian-bureau-of-statistics-awe\" 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.