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Ev-Charging-Analysis--Python-Pandas-

About the Project In this project, I analyzed EV charging session data to understand charging patterns, vehicle model usage, and daily charging trends. The objective was to explore how electric vehicle users interact with charging infrastructure and identify meaningful insights using data analysis techniques.

Tools Used

Python Pandas NumPy Matplotlib Seaborn Jupyter Notebook

Analysis Performed

Top vehicle models by charging sessions Charging sessions by day of the week Trend analysis using visualizations Distribution of charging usage patterns

Key Insights

Certain vehicle models have significantly higher charging frequency. Charging sessions vary across different days of the week. Usage patterns indicate peak charging periods.

Conclusion

This project helped me understand EV charging behavior and usage trends through exploratory data analysis. By visualizing charging sessions and vehicle model distribution, I was able to identify important patterns that can help optimize charging infrastructure planning and energy management strategies. Overall, this project strengthened my data analysis and visualization skills using Python.

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EV Charging Data Analysis using Python to explore vehicle usage patterns, charging sessions, day-wise trends, and model-wise charging distribution through data visualization and EDA.

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