Air Quality Monitoring
Dataset
The air quality dataset of Italian cities from the UCI Machine Learning Repository, containing 9,357 hourly sensor records, covering concentrations of pollutants such as CO, NOx, C6H6, and meteorological data, suitable for time series analysis and sensor calibration research.
Dataset Highlights
Real environmental monitoring data, suitable for time series and sensor data analysis
Real Monitoring Data
Data comes from an outdoor air quality monitoring station in a city in Italy, recording complete hourly data for the year 2004-2005.
Multidimensional Sensors
Includes response data from 5 metal oxide sensors (CO, non-methane hydrocarbons, benzene, NOx, NO2).
Meteorological Features
Simultaneously records temperature, relative humidity, and absolute humidity, allowing analysis of the impact of meteorological conditions on sensor performance.
Time Series Structure
Hourly timestamps make it very suitable for time series analysis, seasonal decomposition, and trend forecasting.
Missing Value Handling
The dataset contains missing values encoded as -200, allowing practice in missing value detection and imputation techniques.
UCI Authoritative Source
Originates from the UCI Machine Learning Repository, widely cited in sensor calibration and environmental monitoring research.
Applicable Scenarios
From environmental monitoring to sensor research, the application scenarios are extensive
Pollution Prediction
Predict trends in air pollutant concentration changes based on sensor and meteorological data
Sensor Calibration
Calibrate low-cost metal oxide sensors using reference analyzer data
Time Series
Analyze daily and seasonal variations in air quality, practicing time series decomposition
Missing Value Handling
Handle a large number of missing values encoded as -200, practicing various imputation strategies
Data Preview
The following are the first few rows of the air quality dataset (semicolon separated)
Date;Time;CO(GT);PT08.S1(CO);NMHC(GT);C6H6(GT);PT08.S2(NMHC);NOx(GT);PT08.S3(NOx);NO2(GT);PT08.S4(NO2);PT08.S5(O3);T;RH;AH 10/03/2004;18.00.00;2,6;1360;150;11,9;1046;166;1056;113;1692;1268;13,6;48,9;0,7578 10/03/2004;19.00.00;2;1292;112;9,4;955;103;1174;92;1559;972;13,3;47,7;0,7255 10/03/2004;20.00.00;2,2;1402;88;9,0;939;131;1140;114;1555;1074;11,9;54,0;0,7502 10/03/2004;21.00.00;2,2;1376;80;9,2;948;172;1092;122;1584;1203;11,0;60,0;0,7867
3 Steps to Get Started
From browsing to analysis, you can start your data science project in minutes
Browse the Dataset
View dataset details on the Ace Data Cloud platform, including field descriptions, sample size, and licensing agreements.
Download Data
Download the CSV file (755 KB), noting that the data uses semicolons as separators and commas as decimal points.
Load and Analyze
Use pandas.read_csv(sep=\";\") to load the data, replacing -200 with NaN before starting the analysis.
Start Exploring Air Quality Data
A classic environmental monitoring dataset, open license, available for immediate download. Complete hourly sensor data for a full year, ideal for time series analysis and sensor calibration research.