Finland Job Market Visualizer

Explore Finnish occupation data (StatFin PxWeb + Occupational Barometer) and color it by AI exposure.

Quick Start

1. Configure

   cp data/statfin_config.example.json data/statfin_config.json
   # Edit data/statfin_config.json with your PxWeb table IDs and variable codes

2. Build site

   finlandjobs all --barometer-input barometer.csv  # complete pipeline
   # or
   finlandjobs fetch && finlandjobs build

3. Preview

   cd site && python -m http.server 8000

CLI Commands

• finlandjobs fetch – download StatFin data
• finlandjobs infer – add AI exposure estimates (optional)
• finlandjobs build – generate site data files
• finlandjobs all – run complete pipeline

Optional: finlandjobs all --barometer-input barometer.csv includes Occupational Barometer outlook data.

Configuration

• statfin_config.json – required, defines PxWeb tables and variables
• TREE_LEVEL – treemap hierarchy level (default: 4)

See finlandjobs --help for all options.

Notes

• score.py will use Markdown pages if present, otherwise it constructs a prompt from occupations.csv.
• Outlook: if you use the Occupational Barometer, map its demand labels into the CSV outlook_desc field in fetch_statfin.py.
• fetch_statfin.py writes median_pay_source and outlook_source fields for auditability (wages_statfin, outlook_statfin, extras_csv).
• You can enforce outlook completeness in config with min_outlook_coverage (0-1) and strict_outlook_coverage (true/false).
• build_site_data.py uses one hierarchy level only (TREE_LEVEL, default 4) so total jobs are not double-counted across Level 1-5 aggregates.
• Barometer data source: The Occupational Barometer (Työllisyysbarometri) CSV can be obtained from Statistics Finland (PxWeb API) or the Ministry of Employment and the Economy. Look for columns containing occupation codes (ISCO or ammatti_koodi) and outlook categories (balance_label). This data is optional; the pipeline will use extras.csv if barometer data is not provided.

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This project is adapted from karpathy/jobs. Thanks to the original author for the excellent foundation.