EV Market Exploratory Data Analysis šā”
šš» Conducted an in-depth analysis of the rapidly growing Electric Vehicle (EV) market using data visualization techniques, addressing key areas like consumer behavior, product optimization, and strategic planning.
1ļøā£ Data Transformation:
šš» Cleaned and processed 3 datasets (ev_main, ev_efficiency, ev_manufacturing) involving 1,000+ records to ensure consistency and reliability.
šš» Resolved brand-model inconsistencies (e.g., fixing a critical 16-brand duplication issue for the BMW i3) using custom mapping and validation.
2ļøā£ Visualization Insights:
šš» Built 7+ impactful visualizations including:
- Scatter plots analyzing the price vs. range relationship across 50+ EV models.
- Bar plots comparing brand-wise efficiency, manufacturing locations, and price segmentation.
- Box plots revealing price distribution across top 10 brands.
- Pie charts highlighting sales-based market shares.
- Time-series plots simulating launch trends to identify peak innovation periods.
3ļøā£ Impact:
šš» Identified that 20% of brands control nearly 65% of the EV market based on sales distribution.
šš» Uncovered a positive correlation (~70%) between vehicle range and pricing, influencing strategic product positioning.
šš» Highlighted efficiency leaders where top brands achieved 10ā15% higher range per unit price compared to industry averages.
4ļøā£ Tools & Technologies:
šš» Python (Pandas, Matplotlib, Seaborn)
šš» Data Cleaning & Feature Engineering
šš» Advanced Data Visualization
šš» Through this project, I strengthened my skills in data storytelling š, problem-solving, and strategic data-driven decision-making, positioning me to deliver impactful insights in real-world business scenarios.