Earthquake Data Analysis and Visualization

This repository contains a project that analyzes earthquake data and visualizes the results using Python. The dataset used contains earthquake records with attributes such as date, time, location, magnitude, and depth.

Steps Included in the Project:

• Data Loading & Preprocessing: The dataset (earthquake_data.xlsx) is loaded, and columns like date and time are combined to create a unified timestamp. Missing values in the Magnitude column are cleaned up.
• Statistical Analysis: Basic statistics (counts, means, and distributions) are provided. Missing values in the Magnitude (ML) column are checked, and rows with missing values are removed.
• Visualization:
  • A plot showing the number of earthquakes per day.
  • A histogram displaying the distribution of earthquake magnitudes.
  • A scatter plot showing the relationship between depth and magnitude, colored by location.
• Mapping Earthquakes: A geographic visualization of earthquakes is created using Folium. Each earthquake is plotted on an interactive map with markers proportional to the earthquake's magnitude. The map is saved as an HTML file (earthquakes_map.html).

Key Files:

• earthquake_data.xlsx: The dataset containing earthquake records.
• earthquakes_map.html: An interactive map visualizing the locations and magnitudes of earthquakes.

Libraries Used:

• Pandas for data manipulation
• Matplotlib, Seaborn for data visualization
• Folium for creating the interactive map

Instructions for Running the Project:

1. Install the required libraries:

   pip install pandas matplotlib seaborn folium