Weather Forecasting System Using python and Django Framework

Authors- Abhishek Shinde, Mangesh Janjal, Professor Shashibala Surapaneni

Abstract-– This paper presents the design and development of a weather forecasting web application using Python and Django, utilizing global meteorological data. The system leverages modern data analytics tools, visualization libraries, and machine learning techniques to analyze and predict atmospheric conditions. A user-friendly interface was created using Bootstrap, enabling users to retrieve real- time weather forecasts efficiently. The study aims to aid agriculture, travel, disaster management, and everyday users by delivering timely and accurate weather updates. In the era of climate variability and increasing demand for reliable weather information, accurate weather forecasting plays a crucial role across various sectors such as agriculture, transportation, and disaster management. This research presents the development of a real-time weather forecasting web application using Python and Django, named WeatherBug. The system integrates meteorological data sourced from Kaggle and Open Weather Map API to analyze and predict weather conditions including temperature, humidity, wind speed, and cloud cover. The application utilizes data preprocessing techniques, exploratory data analysis, and trend identification through machine learning algorithms such as neural networks and support vector machines. Visualizations are generated using libraries like Matplotlib and Seaborn, while the frontend is designed with Bootstrap for responsiveness. The project demonstrates the feasibility of deploying a reliable and user-friendly weather monitoring system, offering valuable insights into weather trends and aiding in timely decision-making. Future enhancements include mobile integration for broader accessibility and push notifications for real-time updates. [3]