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rsvp/fecon235 resource

Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX bonds TIPS rates currency FX euro EUR USD JPY yen XAU gold Brent WTI oil Holt-Winters time-series forecasting statistics econometrics observed · 2026-08-28

github.com/rsvp/fecon235 · homepage · Jupyter Notebook · NOASSERTION (other) observed · 2026-08-28

Health v2 · maintenance only

32/100

  • Activity 0
  • Release rhythm 35
  • Longevity 100

Flags: no_releases no_license

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 4315
  • days_rel: n/a
  • days_push: 1321
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1275 stars · 349 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A collection of Jupyter notebooks for financial economics research, providing high-level Python interfaces to economic data sources like FRED, Quandl, and pandas_datareader. It integrates numpy, pandas, statsmodels, and matplotlib for econometrics, time-series analysis, and portfolio analysis, with reusable modules refactored into the companion fecon236 repository.

Use cases

  • retrieve and analyze Federal Reserve FRED economic data in Python
  • forecast inflation, GDP, or interest rates with time-series models
  • analyze equity, bond, FX, and gold price data in Jupyter notebooks
  • run econometric analysis on macroeconomic time series
  • build reproducible financial economics research notebooks
  • resample and align financial time series from incompatible data sources
  • learn quantitative economics with Python examples

When to choose

  • you want ready-made Jupyter notebooks for macro and financial data analysis
  • you need free access to FRED and other economic data with simple get/plot commands
  • you are teaching or learning econometrics and quantitative finance in Python

When to avoid

  • you need a maintained production library - active development moved to fecon236
  • you need structured, tested application code rather than research notebooks
  • you require commercial data sources or non-Python environments

Facets

learning-resource · maturity maintenance

data-science data-visualization etl math sdk data-science fintech analytics time-series tutorials python jvm windows cross-platform jupyter-notebooks econometrics fred-data financial-economics time-series-forecasting quantitative-finance pandas reproducible-research economics linux macos docker

2 sources

Member repositories

RepositoryRoleHealth v2
rsvp/fecon235main32

For agents

markdown · JSON · MCP: product_card(name="rsvp/fecon235")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem