Weather Forecast Analysis

This Python project provides a comprehensive analysis of weather data from around the world. Using data from various countries, seasons, and months, users can query specific weather conditions and visualize the results. The project leverages the power of pandas, matplotlib, and numpy to process and display the data.

Features

• Data Analysis: Analyze weather data from different countries and seasons.
• Custom Queries: Input specific queries to get tailored weather insights.
• Visualizations: Generate charts and graphs to visualize weather patterns.

Requirements

• Python 3.x
• pandas
• matplotlib
• numpy

You can install the required libraries using pip:

pip install pandas matplotlib numpy

Usage Prepare Your Data: Ensure your weather data is in a CSV format. The CSV file should have columns like Country, Season, Month, Temperature, Humidity, etc.

Running the Script:

Clone the repository:

git clone https://github.com/yourusername/weather-forecast-analysis.git

Navigate to the project directory:

cd weather-forecast-analysis

Run the Python script:

python weather_analysis.py

User Input: The script will prompt you to input your choice of data. You can specify:

Country Season Month Based on your input, the script will display relevant weather data and generate visualizations.

Example Here is an example of how to use the script:

Enter the country: Canada
Enter the season: Winter
Enter the month: December

The script will output the weather data for Canada in December during the Winter season and provide a graphical representation of the data.

Code Structure weather_analysis.py: Main script to handle user input and generate results. data/: Directory containing CSV files with weather data. visualizations/: Directory where plots and charts are saved. Contributing If you'd like to contribute to this project, please follow these steps:

Fork the repository.

Create a new branch for your feature or bug fix.

Make your changes and commit them.

Push your branch to your forked repository.

Open a Pull Request with a description of your changes.

License:

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgements

pandas for powerful data manipulation and analysis.

matplotlib for creating static, interactive, and animated visualizations in Python.

numpy for support of large, multi-dimensional arrays and matrices.

Contact

For any questions or suggestions, feel free to contact me via GitHub Issues.