UCI Datasets: "Air quality" and "US Census (1990)"

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