quincy918/electricity-reliability-outages-africa
Electricity Reliability and Outages - Sub-Saharan Africa Synthetic dataset capturing electricity reliability metrics, outage patterns, system losses, and service quality across Sub-Saharan African utilities, including SAIDI/SAIFI indicators and economic impacts. Key Statistics Total records: 15,000 reliability records across 3 scenarios Countries covered: Kenya, Uganda, Nigeria, Ghana, Tanzania, Ethiopia, Malawi, Zambia, Senegal, Rwanda, Niger, Mali Years:… See the full description on the dataset page: https://huggingface.co/datasets/quincy918/electricity-reliability-outages-africa.
Electricity Reliability and Outages - Sub-Saharan Africa
Synthetic dataset capturing electricity reliability metrics, outage patterns, system losses, and service quality across Sub-Saharan African utilities, including SAIDI/SAIFI indicators and economic impacts.
Key Statistics
- Total records: 15,000 reliability records across 3 scenarios
- Countries covered: Kenya, Uganda, Nigeria, Ghana, Tanzania, Ethiopia, Malawi, Zambia, Senegal, Rwanda, Niger, Mali
- Years: 2018-2025
- Scenarios: lowburden (4,000), moderateburden (5,000), high_burden (6,000)
- Average outage hours monthly: 5-32 hours (varies by country)
- Average system losses: 15-30% (varies by country)
Column Descriptions
Usage
import pandas as pd
# Load dataset
df = pd.read_csv("electricity_reliability_outages_moderate_burden.csv")
# Analyze reliability by country
reliability = df.groupby('country').agg({
'outage_hours_monthly': 'mean',
'system_losses_pct': 'mean',
'reliability_rating': 'mean'
})
print(reliability)
# Filter high-outage locations
high_outage = df[df['outage_hours_monthly'] > 20]Research Sources
Author: Electric Sheep Africa
