| --- |
| license: cc-by-nc-4.0 |
| task_categories: |
| - tabular-classification |
| - tabular-regression |
| language: |
| - en |
| tags: |
| - city-data |
| - violations |
| - municipal |
| - citations |
| - synthetic-data |
| - mindweave |
| - govtech |
| - fines |
| - law-enforcement |
| - test-data |
| - civic-data |
| - parking |
| - urban-planning |
| - open-data |
| - transportation |
| pretty_name: City Parking Violations & Citations Dataset (Free Sample) |
| size_categories: |
| - 1K<n<10K |
| configs: |
| - config_name: citations |
| data_files: data/citations.csv |
| default: true |
| - config_name: officers |
| data_files: data/officers.csv |
| - config_name: zones |
| data_files: data/zones.csv |
| --- |
| |
| # City Parking Violations & Citations Dataset (Free Sample) |
|
|
| > **This is a free sample** with 2,070 rows. The full dataset has **14,825 rows** across 3 tables. |
|
|
| Parking citation records for a simulated mid-size US city (population ~350K) |
| over 2 years. 25,000 citations across 50 zones, with officer assignments, |
| violation types, fine amounts, and payment status tracking. |
|
|
| Features location clustering (downtown hotspots), time-of-day patterns |
| (meter violations peak 9-11 AM), repeat offenders, and two anomalies — |
| a parking meter system failure causing a citation surge and a holiday |
| enforcement blitz in December. |
|
|
| Ideal for: civic tech apps, GovTech dashboards, urban planning analytics, |
| fine collection systems, and open data portal demos. |
|
|
|
|
| ## Sample tables |
|
|
| | Table | Sample Rows | |
| |-------|------------| |
| | citations | 2,000 | |
| | officers | 20 | |
| | zones | 50 | |
| | **Total** | **2,070** | |
|
|
| ## Full dataset |
|
|
| The complete dataset includes all tables with full row counts: |
|
|
| | Table | Full Rows | |
| |-------|----------| |
| | citations | 14,755 | |
| | officers | 20 | |
| | zones | 50 | |
| | **Total** | **14,825** | |
|
|
| **Formats included:** CSV, Parquet, SQLite |
|
|
| **[Get the full dataset on Gumroad](https://mindweavetech.gumroad.com)** |
|
|
| ## About |
|
|
| Generated by [Mindweave Technologies](https://mindweave.tech) -- realistic synthetic datasets for developers, QA teams, and data engineers. |
|
|
| Every dataset features: |
| - Enforced foreign key relationships across all tables |
| - Realistic statistical distributions (not uniform random) |
| - Temporal patterns (seasonal, time-of-day, day-of-week) |
| - Injected anomalies for ML training and anomaly detection |
| - Deterministic generation (same seed = same output) |
|
|
| Browse all datasets: [https://mindweavetech.gumroad.com](https://mindweavetech.gumroad.com) |
|
|
