Exploratory Data Analysis on Roller Coaster Dataset Using Python

Created an Exploratory Data Analysis (EDA) project to analyze a roller coaster dataset and uncover patterns in coaster design and performance using Python data analysis and visualization tools.

The project includes:

Data cleaning and preprocessing

Handling missing values

Exploratory data analysis of coaster features

Creating multiple visualizations to identify trends and relationships

Key insights explored:

Distribution of roller coaster speeds

Relationship between speed and height

Top years when roller coasters were introduced

Average coaster speeds by location

Correlation between features such as height, inversions, and g-force

Through visualizations such as scatter plots, histograms, KDE plots, and heatmaps, the project reveals interesting patterns in roller coaster development over time.

Tools used:

Python, Pandas, Matplotlib, Seaborn, Jupyter Notebook