The ranked union of anomalies, changepoints, emerging clusters and forecast breaches. Every explanation is generated from the evidence underneath it — no number appears in the sentence that is not in the evidence.

Terms are TF-IDF weighted against the whole filtered corpus, so a term that is common everywhere ranks below one that is distinctive here. Terms shorter than three characters and stopwords are excluded. Click a sample to read the full report text.

Rule-based extraction of UK postcodes, street names, organisations, dates and quantities from report text. Nothing leaves the API — no external NLP service.

Expected report volume for planning — a council can staff a crew, order a skip or schedule work from it. The shaded band is the 80% interval from residual variance; MAPE is the holdout error over the last horizon days. This is not a prediction about people or places.

Reports without a city name are grouped as “Unknown” and always sorted last. Click a row to filter the dashboard to that city.

Alerts compare the last 7 days with the per-7-day average of the baseline window, so the two sides are like for like. Only groups with at least the minimum number of recent reports and a ratio of 1.5× or more appear. The date range does not apply here — city and category filters do.

Recent counts are compared with the same area × category's own trailing baseline. The method column is the honest part: Poisson is the tail test for rare counts (baseline rate < 5 per window), robust z is median/absolute-deviation for normal counts, so a single blip cannot look like a surge at low volume.

The best single split (SSE minimisation) on each daily series — “when did this structurally change?”, not “is this a spike?”. Values are daily means either side of the split date.

Lift is how much more often a pair appears together than chance. External correlations are Pearson against the cached open-data series; a direction is only shown when it is positive or negative — a coefficient that rounds to zero is omitted by the API rather than called “none”.

EXIF note —

Pyodide and matplotlib are fetched on demand from the URL configured in config.js. If that fails — offline or blocked by CSP — the panel says so and the rest of the dashboard is unaffected. This is the correct sandbox for a hosted product: there is no server-side interpreter to escape from.

Generates synthetic UK reports containing discoverable patterns — a persistent hotspot, an emerging one, seasonality, weather linkage and a one-off burst. Demo rows are flagged is_demo in the database and never appear in the consumer app. Seeding is an administrator action; the generated patterns are listed when it finishes.

Observations are fetched on demand and cached locally, so queries never depend on a third party being up. Refresh fetches the cities in scope; concurrent refreshes are refused by an advisory lock.

Counts are live for the current filter. The graph is what makes “what is connected to what” answerable — reports to areas, categories, themes, mentions, media and external observations.

Small-cell suppression: any area × category × week cell with fewer than minCell reports is withheld and counted as suppressed, so an individual report cannot be identified from the published totals. A higher minCell publishes less but protects more.

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