Electricity Dataset

The ElectricityDemand.csv dataset contains monthly observations of residential electricity sales along with a variety of explanatory variables related to electricity pricing, weather, climate, and economic conditions. The target variable, SALES, represents trend-adjusted residential electricity sales (GWHr). Predictor variables include electricity price, temperature measurements, precipitation statistics, visibility, wind speed, unemployment rate, and real gross state product (GSP). This dataset is designed for developing and evaluating multiple linear regression models to understand how environmental and economic factors influence electricity demand.

Data and Resources

Field Value
catalogTarget ckan
cndp NDP
currentStep 0
dataAuthType public
isSpatial none
isTemporal false
lang en
lastUpdateDate 2026-08-04
ndp_creator_md5 983636c004fe124a832e1fdbe17cade2
pocEmail pagarw05@calpoly.edu
pocName Puneet Agarwal
pocWebsite https://ime.calpoly.edu/puneet-agarwal/
publisherEmail pagarw05@calpoly.edu
publisherName Puneet Agarwal
publisherType person
status submitted
uploadType dataset
Groups
  • NSF
  • United States
Tags
  • NSF
  • United States
  • machine learning
  • regression
isopen False
metadata_created 2026-10-30T17:29:18.936063
metadata_modified 2026-10-30T17:29:18.936068
notes The ElectricityDemand.csv dataset contains monthly observations of residential electricity sales along with a variety of explanatory variables related to electricity pricing, weather, climate, and economic conditions. The target variable, SALES, represents trend-adjusted residential electricity sales (GWHr). Predictor variables include electricity price, temperature measurements, precipitation statistics, visibility, wind speed, unemployment rate, and real gross state product (GSP). This dataset is designed for developing and evaluating multiple linear regression models to understand how environmental and economic factors influence electricity demand.
num_resources 1
num_tags 4
title Electricity Dataset