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Data Analysis — fred_macro.csv

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Data Analysis — fred_macro.csv

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CCurran Kelleher
Last edited Oct 20, 2026
Created on Oct 15, 2026

Created from react-d3-starter template

FRED Macro Dataset — fred_macro.csv

A monthly macroeconomic time-series dataset sourced from Federal Reserve Economic Data (FRED), covering January 2000 through (containment permitting) 2026. It pairs a market indicator (S&P 500) with several core U.S. monetary and labor statistics, making it suitable for studying the interaction between monetary policy, inflation, and the labor market.

Dataset Overview

  • Filename: fred_macro.csv
  • Rows: 313
  • Columns: 8
  • Time coverage: 2000-01-01 to 2026-01-01 (monthly cadence)
  • Subject matter: U.S. macroeconomic indicators — interest rates, inflation, unemployment, output, and equity markets.

Each row is one monthly observation. Because the columns come from FRED series with different native release frequencies (e.g. GDP is quarterly, rates are daily-or-monthly rolled up), several columns have substantial missingness where no monthly value was published.

Column Descriptions

For each column: what it appears to represent, its Tamara Munzner data type, and notes on missing/unusual values. Interpretations are tentative — the column names are strong hints, not verified definitions.

Column Description (tentative) Munzner type Notes
date Calendar month of the observation (first of month). Temporal 313 unique values, no missing. Min 2000, max 2026.
sp500 S&P 500 equity index level at that month. Quantitative 198 missing (the sparsest column). Values range ~2098.86–6849.09. Likely only populated for recent months.
fed_funds_rate Effective/effective-target federal funds rate (%). Quantitative No missing. Range 0.04–6.86; note the long ~0% era (2009–2015, 2020–2022).
cpi Consumer Price Index (index level, not % change). Quantitative 1 missing. Range 169.3–326.588. Monotonically rising index — treat as level, not inflation rate.
unemployment_rate U.S. civilian unemployment rate (%). Quantitative 1 missing. Range 3.4–14.8 (14.8 ≈ COVID-2020 shock).
real_gdp Real GDP (likely billions of chained 2017 dollars, quarterly). Quantitative 208 missing — GDP is quarterly, so only ~1/3 of months have a value; other months are blank. Range ~13878.147–24180.419.
treasury_10y 10-year U.S. Treasury constant-maturity yield (%). Quantitative 1 missing. Range 0.55–6.68.
breakeven_inflation 10-year breakeven inflation rate (%), a market-implied inflation expectation. Quantitative 37 missing. Range 0.11–2.88.

Parsing assumptions

  • Dates are ISO YYYY-MM-DD strings and are parsed with d3.timeParse.
  • All numeric columns are strictly numeric; empty cells are read as null and coerced to NaN on parse. No thousands separators or currency symbols appear in the raw values.
  • The CSV header is the first record and is a single clean line here. It is still parsed with d3.csv() (a real CSV parser) so quoted/embedded-newline headers would be handled correctly if present.
  • Columns with high missingness (sp500, real_gdp) are not interpolated; missing points are simply skipped when drawing lines.

Visualization Mappings

Chart type: Dual-axis time-series line chart.

Why this choice: date is the natural temporal axis and most other columns are quantitative measurements sampled over time, so a time-series is the correct idiom. Fed funds rate and unemployment rate are the two columns that are complete (no meaningful gaps) and have the clearest coupled story: the Fed raises rates when unemployment is low, and cuts when it rises. Showing them together on twin y-axes reveals that policy cycle directly.

Encodings:

  • x → date (temporal), linear time scale.
  • y (left) → fed_funds_rate (quantitative, %), blue line.
  • y (right) → unemployment_rate (quantitative, %), orange line.
  • Axis titles are color-matched to their line so the dual encoding is legible.

Interactions:

  • Hover: a vertical crosshair follows the nearest month and a tooltip shows the date plus both series values, letting the reader inspect exact turning points (e.g. the 2001, 2008, and 2020 unemployment spikes).
  • The chart resizes responsively with its container via a ResizeObserver hook.

Deliberately omitted: no summary cards, no raw data table, no preview, and no auxiliary panels — the deliverable is a single focused visualization.