# rsvp/fecon235

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

Repository: https://github.com/rsvp/fecon235
Canonical: https://ross.abutalabs.com/products/fecon235
Homepage: https://git.io/econ
Language: Jupyter Notebook
License: NOASSERTION
License Family: other
Topics: jupyter-notebook, pandas, federal-reserve, gdp, inflation, housing, equities, bonds, fx, gold, time-series, econometrics, statistics, asset-pricing, finance, interest-rates, economics, employment, python, fecon236
Last push: 2023-01-20T06:53:24+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4315, "days_push": 1321, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1275, forks 349 (observed 2026-08-28T04:04:12.948951+00:00)

## What it is
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
- artifact type: learning-resource
- maturity: maintenance
- function: data-science, data-visualization, etl, math, sdk
- domain: data-science, fintech, analytics, time-series, tutorials
- platform: python, jvm, windows, cross-platform
- tags: jupyter-notebooks, econometrics, fred-data, financial-economics, time-series-forecasting, quantitative-finance, pandas, reproducible-research, economics, linux, macos, docker

## Member repositories
- rsvp/fecon235 (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:12.948951+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T05:03:03.720014+00:00, confidence not recorded.
  - readme: https://github.com/rsvp/fecon235 (fetched 2026-08-28T04:04:12.948951+00:00, sha 02658e2730af)
  - homepage: https://git.io/econ (fetched 2026-08-29T12:14:18.033715+00:00, sha 48641a88f436)
- Data as of 2026-08-30T08:39:29.467469+00:00.