This project performs exploratory data analysis (EDA) on event-based datasets to discover meaningful patterns and trends using Python.
The goal is to clean, explore, visualize, and interpret structured data to support analytical understanding and decision-making.
- Load and inspect event datasets
- Clean and preprocess data
- Conduct exploratory analysis to uncover patterns
- Visualize key insights using charts
- Summarize findings for interpretation
- Python
- Pandas
- NumPy
- Matplotlib
- Seaborn
- Jupyter Notebook
- Data loading and inspection
- Data cleaning and handling missing values
- Exploratory data analysis (EDA)
- Visualizing trends and distributions
- Interpretation of results
- Identified patterns and variations across event types
- Observed trends based on time and event categories
- Visualizations helped support analytical understanding
This project strengthened data analysis skills and showcased structured analytical thinking using real event data.
Eldho Joshy