truewise-data
Clean, ready-to-use data on the economic value of US college programs, median earnings versus a typical high-school graduate, derived from the U.S. Department of Education's College Scorecard. No API key, no 178-column bulk files, no decoding suppression flags: one clean table, offline.
pip install truewise-data
import truewise_data as tw
df = tw.load_value_check() # one row per school x field of study x credential
df = tw.load_value_check(decided_only=True) # drop insufficient-data rows
# Which programs leave graduates earning less than a typical HS grad?
fails = df[df.value_flag == "fails_earnings_premium"]
fails.groupby("cip_desc").size().sort_values(ascending=False).head(10)
tw.load_summary() # national + state summary stats
tw.meta() # dataset version, source release, license
What's in it
One row per institution × 4-digit CIP code × credential level. Key columns:
| column | meaning |
|---|---|
earnings |
median earnings 4 years after completion (USD) |
earnings_threshold_state / _national |
typical high-school-graduate earnings benchmark |
earnings_premium_state / _national |
earnings minus the threshold (negative = below) |
value_flag |
passes_earnings_premium / fails_earnings_premium / insufficient_data |
debt_median, debt_to_earnings_ratio |
median debt at graduation; debt ÷ annual earnings |
Suppressed small-cohort values are NULL, never imputed. Earnings mirror what ED
publishes on the consumer College Scorecard site (4-year measure). Full methodology and
an accuracy audit: https://github.com/ndranandraj/truewise.
License
Code MIT. Data is CC-BY-4.0, free to use with attribution to Truewise (https://truewise.dev). Underlying figures are US federal public-domain works.
Citation
If you use this dataset, please cite it (a DOI is minted per release via Zenodo, see the repository releases page).
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