Enriched Traffic Datasets for Madrid

-Description of the Research and Data: This work includes two datasets of traffic in Madrid, "DADAS" and "MLDAS", collected between June 2022 and February 2024. These datasets combine traffic sensor data, weather data, calendar data, road infrastructure data and localization data to facilitate detailed analysis of urban mobility and prediction of traffic patterns. -DADAS (Descriptive Analysis DAtaSet): "DADAS" is a dataset oriented towards descriptive analysis, capturing traffic intensity in 15-minute intervals from urban sensors and roads. Data processing includes meticulous cleaning and filtering to remove inconsistencies and outliers. Additionally, the k-means algorithm is used to group data from multiple sensors. -MLDAS (ML-oriented DAtaSet): "MLDAS" is designed for predictive analysis and modeling of traffic patterns. Derived from the "DADAS" dataset, this dataset has been processed to include temporal transformations and encoding of categorical and ordinal features, specifically preparing it for advanced machine learning applications. -Data usage: These datasets are crucial for infrastructure planning and sustainable traffic policies, providing valuable resources for researchers and urban planners interested in mobility studies and their environmental impact. For more details, see [Submitted to Data in Brief].