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Violation Vision

See the bigger picture of parking tickets

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By: Adam Walid, Tyler Katz, Jack Kester, Brandon Lyubarsky, Will Charrier

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Table of contents

Project & strategy

Data Cleaning and Feature Engineering

Data

Visualization

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Project & Strategy

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Project Planning Summary

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  • Aimed to analyze and visualize trends in parking ticket issuance throughout Syracuse and its surrounding areas.

  • Leverage parking violation data to explore key factors contributing to ticketing patterns, identify hotspots for violations, and highlight temporal trends.

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  • Our visualizations and insights were thoughtfully designed to prioritize the most valuable information for both citizens and city officials, ensuring relevance, clarity, and actionable takeaways for informed decision-making.

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Data Cleaning and Feature Engineering

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Data Cleaning and Feature Engineering

  • Data cleaning was a crucial step in ensuring the accuracy, reliability, and integrity of the dataset used for analyzing parking ticket statistics. Our process focused on addressing three key issues: insufficient rows, missing data points, and outliers.

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  • Feature engineering played a significant role in our project, as we created several new columns to enhance the dataset's predictive power and analytical value. This was achieved through various functions, calculations, and transformations, allowing us to extract meaningful insights and improve the overall quality of our analysis.

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Derived Columns:

  • Ticket Issue Coordinate Correspondence to SYR Town/Area
  • Ticket Issue Month
  • Ticket Issue Week
  • Ticket Issue Day
  • Ticket Issue Hour

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Data Visualization

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Data Visualization

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Tickets vs time ranges (by 3 hour intervals)

Tickets vs Day of the Week

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Data Visualization

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Distribution of ticket prices per month

# of tickets issued vs. Month (broken down by week)

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Data Visualization

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Count of Tickets Closest to Syracuse + Surrounding Areas

Map of all Towns included in Dataset

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Data Visualization

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Data Visualization

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Distribution of issued tickets vs. Price

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