Air Quality

This dataset from the UCI repository represents hourly averaged measurements of 5 metal oxide chemical sensors embedded in an air quality chemical multisensor device. The certified analyzer was located on the field in a significantly polluted area, at road level, within an Italian city. Data were recorded from March 2004 to February 2005 (one year), representing the longest freely available recordings of on-field deployed air quality chemical sensor device responses (De Vitoet et al., 2008).

Task: The dataset can be used to study causal discovery methods.

Summary: 

• Size of dataset: 9357 x 15
• Task: Causal Discovery
• Data Type: Mixed
• Dataset Scope: Standalone
• Ground Truth: Unknown
• Temporal Structure: Time Series
• License: CC BY 4.0
• Missing Values: No

Missingness Statement: There are no missing values.

Features:

• Date (DD/MM/YYYY)
• Time (HH.MM.SS)
• True hourly averaged concentration CO in mg/m^3 (reference analyzer)
• PT08.S1 (tin oxide) hourly averaged sensor response (nominally CO targeted)
• True hourly averaged overall Non Metanic HydroCarbons concentration in microg/m^3 (reference analyzer)
• True hourly averaged Benzene concentration in microg/m^3 (reference analyzer)
• PT08.S2 (titania) hourly averaged sensor response (nominally NMHC targeted)
• True hourly averaged NOx concentration in ppb (reference analyzer)
• PT08.S3 (tungsten oxide) hourly averaged sensor response (nominally NOx targeted)
• True hourly averaged NO2 concentration in microg/m^3 (reference analyzer)
• PT08.S4 (tungsten oxide) hourly averaged sensor response (nominally NO2 targeted)
• PT08.S5 (indium oxide) hourly averaged sensor response (nominally O3 targeted)
• Temperature in °C
• Relative Humidity (%)
• AH Absolute Humidity

Files: 

• AirQualityUCI.csv: dataset

US Census (1990)

The data represents a one percent sample drawn from the full 1990 census. This was made possible through the Public Use Microdata Samples (PUMS). Furthermore, the few continuous variables were discretized. (UCI Source)

Task: The dataset can be used to study causal discovery methods.

Summary: 

• Size of dataset: 2458285 x 68
• Task: Causal Discovery
• Data Type: Discrete
• Dataset Scope: Standalone
• Ground Truth: Unknown
• Temporal Structure: Static
• License: CC BY 4.0
• Missing Values: No

Missingness Statement: There are no missing values.

Features:

• See the file variable_description_US_Census_1990.txt for a detailed description.

Files: 

• USCensus1990.csv: dataset
  
• variable_description_US_Census_1990.txt: feature details