Energy Consumption Dataset

Smart meter energy consumption dataset with hourly electricity usage patterns

About This Dataset

This dataset contains hourly energy consumption data from smart meters with seasonal patterns, peak hours, and consumption trends. Perfect for energy demand forecasting, load prediction, and smart grid applications.

Key Features

Hourly consumption data
Seasonal patterns
Peak hour identification
Multiple households
Time series ready format

Data Visualizations

Hourly Patterns

Seasonal Patterns

Household Comparison

Advanced Features

Machine Learning

Forecasting models including Linear Regression and Random Forest

Anomaly Detection

Multiple detection methods: IQR, Z-score, Isolation Forest, Time Series

Time Series Analysis

Decomposition, autocorrelation, trend detection, and stationarity tests

Technologies

CSV JSON Pandas Time Series Python Data Analysis

Download Dataset

Get the complete dataset in CSV or JSON format

Download CSV Download JSON

Advanced Scripts

forecasting.py - ML Models anomaly_detection.py advanced_analysis.py preprocessing.py

Usage Example

import pandas as pd

# Load the dataset
df = pd.read_csv('energy_consumption.csv')

# Basic statistics
print(df.describe())

# Peak hour analysis
hourly_avg = df.groupby('hour')['consumption_kwh'].mean()
print(hourly_avg.sort_values(ascending=False).head())