Georgia Power

Analysis of electricity usage and costs from Georgia Power billing data.

Georgia Power Usage Analysis

A Python script to analyze electricity usage and costs from Georgia Power billing data over multiple years.

Overview

This project analyzes electricity billing data to visualize: - Electricity costs over time - Temperature patterns and their correlation with energy usage - Impact of major life events (moving to a house, installing new windows) on energy consumption

Files

• georgia_power_analysis.py - Main analysis script
• GPC_Usage_2021.csv - 2021 billing data
• GPC_Usage_2022.csv - 2022 billing data
• GPC_Usage_2023.csv - 2023 billing data
• GPC_Usage_2024_2025.csv - 2024-2025 billing data
• NORMAL_DLY_sample_csv.csv - Weather data (sample)

Features

• Data Processing: Combines multiple years of billing data and calculates daily cost averages
• Dual-Axis Visualization: Shows both cost and temperature trends on the same graph
• Event Markers: Highlights important dates:
• Moving to a house (June 2024)
• Installing new windows (October 2024)
• Comparative Analysis: Separates apartment vs. house energy usage patterns

Requirements

numpy
pandas
matplotlib

Data Format

The script expects CSV files with the following columns: - Billing Period - Date range or single date for the billing period - Cost - Total electricity cost for the period - High Temp - Highest temperature during the period - Low Temp - Lowest temperature during the period

Output

The script generates a dual-axis line chart showing: - Green lines: Electricity costs (separated for apartment vs. house periods) - Blue line: Average temperature (continuous across all periods) - Red dashed line: House move date - Orange dotted line: New windows installation date

This visualization helps identify seasonal patterns, the impact of housing changes, and energy efficiency improvements over time.