Shaw Crime Rate Trends — Washington DC
Shaw is the Northwest neighborhood bracketed by U Street to the north and Mount Vernon Square to the south, with rowhouses, the convention center's eastern edge, and the 9th Street commercial corridor anchoring its identity. The cluster includes Logan Circle, where the namesake park is ringed by Victorian rowhouses and a 14th Street restaurant strip runs along its western flank.
Five signals surfaced in Shaw this June — two one-month below-trend readings and three sustained structural shifts. The overall shape is broadly downward: every tracked category with a signal is running below its prior-year pace, and the sustained-shift count indicates this isn't a single quiet month but a multi-month structural move across the neighborhood.
Robbery is the sharpest story: 21 incidents in the current 12-month window against 61 in the year prior — a 65.6% reduction — and it appears both as a one-month drop and a sustained shift, meaning the decline has been building for some time. Other Larceny also registered a one-month below-trend reading, with 340 incidents against 559 the prior year, down 39.2%. Motor Vehicle Theft and Theft from Vehicle round out the broader picture, down 52.1% and 23.1% respectively against prior 12-month totals, though neither crossed a threshold this month.
Notable signals 2
Robbery
The past 12 months saw 21 incidents — about 68% below the 65 average from prior years.
Other Larceny
The past 12 months saw 340 incidents — about 33% below the 508 average from prior years.
All categories, last 24 months
Each panel: recent monthly count vs. trailing 12-month context. MoM is the most recent month vs. the one before; 12mo YoY compares the trailing year to the year before that.
What's been quietly true for a year
Spikes get attention. Sustained shifts shape policy. These are multi-quarter patterns where the past 12-month total differs meaningfully from the year before — they often precede the baseline resetting.
- Other Larceny has reset to a lower baseline.
The trailing 12-month count is 340, down 39% from 559 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
- Motor Vehicle Theft has reset to a lower baseline.
The trailing 12-month count is 58, down 52% from 121 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
- Robbery has reset to a lower baseline.
The trailing 12-month count is 21, down 66% from 61 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
What next month likely looks like
Forecasts trained through June 2026, with a likely range we're 95% confident the actual count will fall inside. Categories with too little recent volume — or violent categories at the neighborhood level — show no forecast and are surfaced through signals above instead. See the methodology page for the gating rules.
Aggravated Assault
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Burglary
Below the volume threshold for a reliable forecast — too few incidents in recent months to project from.
Homicide
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Motor Vehicle Theft
Other Larceny
Robbery
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Sexual Assault
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Theft from Vehicle
How Shaw compares
Peer neighborhoods picked by closest 12-month robbery volume — a pragmatic v1 of peer matching. Demographic / housing-stock peer matching isn't built yet (we deliberately don't ingest income or race data alongside crime). Volume similarity has the right intuition: “neighborhoods experiencing comparable robbery levels.”
Recurring local terms (last 12 months)
Top terms in incident descriptions for Shaw, excluding generic crime taxonomy. Useful as texture — what kinds of specifics show up here that don't show up elsewhere.
Hour-of-day, day-of-week, and seasonality
Distribution of bucketed incidents in this neighborhood across the full analysis window. Useful for routine context — shopping-strip thefts vs. late-night assaults read very differently when you can see when each typically happens.
How we built this page
Data → Anomalies → Forecast → Page
Incident data is pulled from DC Open Data — MPD's per-year Crime Incidents layers on the DCGIS ArcGIS Hub — mapped to 8 UCR Part 1 categories (vandalism and arson are not exposed in MPD's public feed and are excluded). The feed covers 2018-current and updates daily. Aggregated to neighborhood cluster × category × month, with each cluster page identified by its colloquial lead constituent (Adams Morgan, Petworth, Capitol Hill, etc.) rather than the numbered 'Cluster N' identifier.Anomalies are surfaced using strict thresholds (~p < 0.01). Forecasts are Prophet with low-count gating; violent categories at the neighborhood level skip the forecast and show rare-event / streak signals instead.
Spike rule: 12-mo total > baseline mean + 2.5σ AND ≥ 20 incidents AND 6-mo confirms. Drop rule: 12-mo total < baseline mean − 2.5σ AND baseline mean ≥ 20. Rare event: any incident in the last 90 days, no prior comparable in ≥ 5 years.