App gallery / Money
Shown in Electric Lime Noir · 16 featured looks, 520+ more to choose from
Side-hustle earnings calculator
Pay for every occupation from the Bureau of Labor Statistics (OEWS, May 2025): employment and the hourly and annual mean, 10th, 25th, median, 75th and 90th percentile wages, for the nation and every state. Each occupation is joined to its O*NET occupations, with what the work involves (tasks) and how much each skill matters. Pick a skill you have, see the jobs that use it and what they pay where you live, and work out what a few hours a week could earn.
Database app · 7 tables · design: Clay Graph Atelier
Making an app from a pack is for subscribers. Sign in
Tables
- areas5 columns · 55 rows in the full data
- occupations7 columns · 1,104 rows in the full data
- onet_occupations6 columns · 1,016 rows in the full data
- tasks5 columns · 18,838 rows in the full data
- skills4 columns · 35 rows in the full data
- occupation_skills5 columns · 31,850 rows in the full data
- wages8 columns · 500,656 rows in the full data
Sources and licences
- BLS Occupational Employment and Wage Statistics (OEWS) — US government, public domain (Free to use)
- O*NET — CC BY 4.0 (Free with credit)
- Own packs (ours) — Ours (Free to use)
Shown in the app and its export: Wages from the Occupational Employment and Wage Statistics (OEWS, May 2025), US Bureau of Labor Statistics (public domain). This app includes information from the O*NET 31.0 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). O*NET® is a trademark of USDOL/ETA. CreativePower has modified all or some of this information. USDOL/ETA has not approved, endorsed, or tested these modifications. Retrieved 2026-10-22.
Sample: the whole source. Full data: 553,554 rows, 345 MB. Measured 2026-10-22.
Data from www.bls.gov, imported 2026-10-22.
The full data, for your own database
553,554 rows, 7.2 MB to download. CreativePower keeps only the made-up sample rows in your project; load the full data into your own PostgreSQL database (Supabase works): download these files into one folder, unzip the .csv.gz files, then run psql "<your connection string>" -f load.sql.