EDA of Roller Coasters
Welcome to this exploratory data analysis where we embark on an exhilarating journey through the fascinating realm of roller coasters! This analysis utilizes Python libraries like pandas, matplotlib, and seaborn to conduct a comprehensive exploration of a Kaggle-sourced dataset.
Interactive Interface: Designed a user-friendly Streamlit application for real-time email classification.
Data Cleaning:The project meticulously details the steps taken to clean and preprocess the provided data. This ensures a robust and reliable foundation for subsequent analyses.
Basic Analysis using Pandas and Matplotlib:Leveraging the power of pandas dataframes, we perform straightforward yet insightful analyses. Matplotlib aids in visually representing key trends and patterns, making the exploration accessible and engaging.
Advanced Analysis with Seaborn:Seaborn takes center stage for more sophisticated analyses, providing visually appealing and informative plots. This advanced exploration includes in-depth examinations of relationships, distributions, and trends within the dataset.
Technologies Used:
- Python
- Pandas: For data manipulation and preprocessing.
- Matplotlib and Seaborn:For data visualization.
