This project is a notebook that analyzes and forecasts weather patterns using the NOAA Weather Dataset from JFK Airport in New York. The notebook demonstrates an end-to-end data science workflow, from raw data cleaning to advanced time-series forecasting.
The project is structured into three main parts, mirroring the data science lifecycle:
- Data Cleaning: Prepares the raw data by handling inconsistencies, converting data types, and engineering new features from the existing data.
- Exploratory Data Analysis (EDA): Visually and statistically explores the cleaned data to gain insights and understand its characteristics.
- Time-Series Forecasting: Uses the processed data to build and evaluate predictive models for future temperature values.
To run this notebook yourself, follow these steps:
- Clone the repository to your local machine.
- Open the Jupyter Notebook file, main_file.ipynb, and execute the cells in a sequential order.
- Save the style.css file within a new directory named assets.
- Run the dashboard application by executing the command python dashboard_app.py in your terminal.
- Access the dashboard by navigating to the address displayed in your terminal.