🚗 Data Analysis Project: Electric Vehicles EDA! 🌍 I am excited to share my latest data analysis project, where I explored vehicle data over the past decade, applied various analytical techniques, and visualized meaningful insights. This project involved: 🔍 Univariate & Bivariate Analysis: Conducted in-depth univariate analysis to understand the distribution of individual features such as State, Electric Range, BaseMSRP, Electric Vehicle Type Clean Alternative Fuel Vehicle (CAFV) Eligibility etc.. Performed bivariate analysis to explore relationships between different variables, revealing key trends over time. 🛠 Data Manipulation: Efficiently cleaned and transformed the dataset using pandas and NumPy, ensuring data integrity and readiness for analysis. 🌍 Vehicle Position Mapping with Folium: Mapped the geographic distribution of vehicles using Folium, providing a visual representation of where the majority of the vehicles are sold and located. 📊 Race Bar Chart Visualization: Created a dynamic race-bar-chart using bar_chart_race to depict year-wise sales of various vehicle models. This engaging visualization helps track how different companies performed over the years. 📂 Tools Used: Python 🐍 Pandas, NumPy Folium for mapping bar_chart_race for dynamic visualizations Jupyter Notebook & Google Colab 👉 Check out the full project here: https://github.com/Pixer007/Pixer007-DataScience_Projects/blob/main/Electric_Vehicle_EDA.ipynb I'm thrilled with the results and look forward to applying these skills in future projects. Please feel free to leave feedback, and if you're interested in data analysis or machine learning, let's connect! #DataScience #Python #DataAnalysis #DataVisualization #MachineLearning #UnivariateAnalysis #BivariateAnalysis #Folium #RaceBarChart #BigData #BusinessIntelligence