DMP: Predicting Air Quality Levels in European Cities Using Environmental Data

This dataset is used for the project “Predicting Air Quality Levels in European Cities Using Environmental Data.” The aim of the project is to analyze environmental indicators and build a machine learning model to classify air quality levels into categories such as Good, Moderate, and Poor.

The dataset was obtained from the European Environment Agency via the European Data Portal. It contains environmental measurements collected from different European cities, including PM2.5 concentration, nitrogen dioxide (NO₂), temperature, and humidity. The dataset is provided in CSV format and structured in a tabular form where each row represents an observation and each column represents an environmental feature.

The data was not collected manually but reused from an open data source. Preprocessing includes handling missing values, selecting relevant features, and normalizing data before model training. The dataset can be processed using standard data science tools such as Python with Pandas and Scikit-learn.

The dataset does not contain personal or sensitive information and can be freely reused for academic purposes. Users should note that basic preprocessing is required before analysis.