Case Study · Policy + Data Analysis

Arrest Trends, Policy Reform, and Racial Disparities

A comparative analysis of how policing patterns shift over time, across cities, and across communities when you stop looking only at isolated moments.

This independent project examined public safety data across New York City, Washington, D.C., and Los Angeles to answer a harder question than “did reform work?” It asked what changed, when, for whom, and what remains structurally consistent underneath the headlines.

Portfolio research snapshot Independent research NYC · DC · LA
Data analysis Policy Racial equity Time-series

Public debate moves fast. Structural patterns do not.

Conversations about policing reform often rely on short time windows, anecdotal evidence, or one city at a time. That makes it easy to miss recurring seasonal spikes, policy lag effects, or disparities that remain stable even when total arrests fall. The project set out to build a longer, more comparative view that could support better policy interpretation.

Research owner

I led the project from data cleaning and exploratory work through modeling, visualization, and written policy argument.

Translator

I converted technical findings into a narrative a policymaker, academic audience, or journalist could follow without flattening the nuance.

Python (pandas) Google Colab Time-series analysis Difference-in-differences Data visualization GitHub
01

Prepare the data

Standardized offense categories, dates, and city labels while auditing missingness, outliers, and comparability issues.

02

Surface long-run patterns

Built monthly totals, rolling averages, and seasonal views to distinguish noise from durable movement.

03

Map reforms to the timeline

Aligned major policy changes and enforcement shifts with observed trend breaks rather than assuming a clean before-and-after story.

04

Test the claim

Used difference-in-differences style comparisons to evaluate whether reform periods coincided with meaningful shifts in outcomes.

05

Write the argument

Paired charts with explicit caveats so the narrative stayed persuasive without pretending the data answered more than it could.

Seasonality matters

Summer arrest spikes appeared repeatedly, suggesting that short-window comparisons can misread normal cyclical changes as policy effects.

Reform effects are uneven

Some inflection points aligned with reform periods, but the distribution of impact was inconsistent across cities and racial groups.

Equity cannot be inferred from totals alone

Declines in aggregate arrests do not automatically mean disparities are shrinking; composition and burden still matter.

The strongest evidence here is the combination of reproducible analysis, interpretive writing, and a comparative frame that resists simplistic conclusions.

  • Extend the analysis beyond 2024 and add more metropolitan areas for broader comparison.
  • Bring in neighborhood-level indicators to better capture where disparities concentrate spatially.
  • Translate the work into an interactive dashboard for policymakers, journalists, and public readers.