Welcome to the Earthquake Data Analysis project! This repository contains a mini-project that analyzes the "Significant Earthquakes 1965-2016" dataset. The project involves various data manipulation, reshaping, and visualization tasks to derive insights from the data.
- Filled missing values in the 'Depth' column with the mean depth.
- Removed the 'Time' column as it was not needed for the analysis.
- Split the 'Date' column into 'Year', 'Month', and 'Day' for better date handling.
- Categorized earthquake magnitudes into three categories: 'Low', 'Medium', and 'High'.
- Used the
melt()function to transform the data into a long format. - Applied the
pivot()function to create a summary table of average depths by year and magnitude category.
Created four different types of charts to visualize the data:
- Line Chart: Shows the yearly trend of earthquake magnitudes.
- Bar Chart: Displays the average monthly earthquake magnitudes.
- Scatter Plot: Plots the locations of earthquakes by magnitude.
- Histogram: Illustrates the distribution of earthquake magnitudes.
- Extracted the year and month from the 'Date' column.
- Resampled the data by year to calculate the mean magnitude.
- Python 3.x
- Pandas
- NumPy
- Matplotlib
- Seaborn
Clone the repository:
git clone https://github.com/yourusername/earthquake-data-analysis.git
Navigate to the project directory:
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cd earthquake-data-analysis
Install the required packages:
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pip install pandas numpy matplotlib seaborn
Usage
Run the Python script to perform the data analysis:
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python earthquake_analysis.py
Results
The results of the analysis, including the cleaned data and generated charts, are saved in the project directory.
Contributing
Feel free to fork the repository and submit pull requests. Contributions are welcome!
License
This project is licensed under the MIT License.