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traffic-eda-project

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# traffic-eda-project

Traffic Collision Analysis – Uncovering Road Safety Patterns in Los Angeles

Urban mobility comes with its share of challenges — and road safety is one of the biggest. I recently worked on an Exploratory Data Analysis (EDA) project to study traffic collision data in Los Angeles, aiming to uncover trends, identify hotspots, and extract insights from real-world data.

Key Highlights:

🔹 Identify High-Risk Areas – Locate collision hotspots in Los Angeles using geospatial analysis.
 🔹 Assess Trends and Patterns – Analyze how traffic accidents vary year-over-year and seasonally.
 🔹 Enhance Road Safety Measures – Derive data-driven suggestions for better infrastructure and safety.
 🔹 Evaluate Policy Impact – Examine the effectiveness of previous traffic regulations and planning.
 🔹 Support Predictive Analytics – Build models to predict accident-prone zones and times.

Tools Used: Python, Pandas, Matplotlib, Seaborn, Jupyter Notebook
Disclaimer: This project is part of an academic learning initiative. Data was used for educational purposes only. Insights are not to be used for official decisions without consulting experts or city authorities.

📂 Dataset Source:
 Data obtained from the official Los Angeles Open Data Portal:
 🔗https://lnkd.in/gHgJTxuV

guided by : Aashima Bansal

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