electricsheepafrica/africa-synth-retail-and-ecommerce-stock-and-inventory-levels-nigeria

⚠️ Synthetic dataset — Parameterized from published SSA literature, not real observations. Not suitable for empirical analysis or policy inference.

Stock And Inventory Levels

Dataset Description

Comprehensive stock and inventory levels for Nigerian retail and e-commerce analysis

Dataset Information

• Category: Product and Inventory
• Industry: Retail & E-Commerce
• Country: Nigeria
• Format: CSV, Parquet
• Rows: 500,000
• Columns: 10
• Date Generated: 2025-10-06
• Location: data/stock_and_inventory_levels/
• License: GPL

Schema

Column	Type	Sample Values
inventory_id	String	INV0000000
product_id	String	PRD45195
warehouse_location	String	Lagos
current_stock	Integer	275
reorder_point	Integer	14
reorder_quantity	Integer	352
stock_status	String	in_stock
last_restock_date	String	2024-08-13
shelf_location	String	Aisle-6-Shelf-3
expiry_date	String	2026-11-14

Sample Data

inventory_id product_id warehouse_location  current_stock  reorder_point  reorder_quantity stock_status last_restock_date   shelf_location expiry_date
  INV0000000   PRD45195              Lagos            275             14               352     in_stock        2024-08-13  Aisle-6-Shelf-3        None
  INV0000001   PRD48058         Benin City            606             56               386     in_stock        2024-07-02  Aisle-9-Shelf-6        None
  INV0000002   PRD72766              Lagos            293             45               444     in_stock        2024-09-25 Aisle-15-Shelf-6  2026-11-14

Use Cases

• Data analysis and insights
• Machine learning model training
• Business intelligence
• Research and education
• Predictive analytics

Nigerian Context

This dataset incorporates authentic Nigerian retail and e-commerce characteristics:

E-Commerce Platforms

• Jumia (35% market share) - Leading marketplace
• Konga (25% market share) - Major competitor
• Jiji (20% market share) - Classifieds platform
• PayPorte, Slot, and other platforms

Physical Retail

• Shoprite, Spar, Game - Major supermarket chains
• Slot, Pointek - Electronics retailers
• Mr Price - Fashion retail
• Traditional markets: Balogun Market, Computer Village

Payment Methods

• Cash on Delivery (45%) - Most popular
• Bank Transfer (25%)
• Debit Card (15%)
• USSD (8%)
• Mobile Money (5%)
• Credit Card (2%)

Logistics & Delivery

• GIG Logistics - Nationwide coverage
• Kwik Delivery - Fast urban delivery
• DHL, FedEx - International and express
• Red Star Express - Nationwide courier
• Local dispatch riders

Geographic Coverage

Major Nigerian cities including:

• Lagos - Commercial capital, highest retail density
• Abuja - Federal capital, high e-commerce penetration
• Kano - Northern commercial hub
• Port Harcourt - Oil city, strong purchasing power
• Ibadan - Large urban market
• Plus 10+ other major cities

Products & Categories

• Electronics: Tecno, Infinix, Samsung phones; laptops, TVs
• Fashion: Ankara fabric, Agbada, Kaftan, sneakers
• Groceries: Rice (50kg bags), Garri, Palm Oil, Indomie
• Beauty: Shea butter, Black soap, hair extensions
• Home: Generators, inverters, solar panels

Currency & Pricing

• Currency: Nigerian Naira (NGN, ₦)
• Exchange Rate: ~₦1,500/USD
• Price Ranges: Realistic Nigerian market prices
• Time Zone: West Africa Time (WAT, UTC+1)

File Formats

CSV

data/stock_and_inventory_levels/nigerian_retail_and_ecommerce_stock_and_inventory_levels.csv

Parquet (Recommended)

data/stock_and_inventory_levels/nigerian_retail_and_ecommerce_stock_and_inventory_levels.parquet

Nigerian Retail and E-Commerce - Loading the Dataset

Hugging Face Datasets

from datasets import load_dataset

# Load dataset
dataset = load_dataset("electricsheepafrica/nigerian_retail_and_ecommerce_stock_and_inventory_levels")

# Convert to pandas
df = dataset['train'].to_pandas()

print(f"Loaded {len(df):,} rows")

Pandas (Direct)

import pandas as pd

# Load CSV
df = pd.read_csv('data/stock_and_inventory_levels/nigerian_retail_and_ecommerce_stock_and_inventory_levels.csv')

# Load Parquet (recommended for large datasets)
df = pd.read_parquet('data/stock_and_inventory_levels/nigerian_retail_and_ecommerce_stock_and_inventory_levels.parquet')

PyArrow

import pyarrow.parquet as pq

# Load Parquet
table = pq.read_table('data/stock_and_inventory_levels/nigerian_retail_and_ecommerce_stock_and_inventory_levels.parquet')
df = table.to_pandas()

Data Quality

• ✅ Realistic Distributions: Based on Nigerian retail patterns
• ✅ No Missing Critical Fields: Complete core data
• ✅ Proper Data Types: Appropriate types for each column
• ✅ Consistent Naming: Clear, descriptive column names
• ✅ Nigerian Context: Authentic local characteristics
• ✅ Production Scale: Suitable for real-world applications

Ethical Considerations

• This is synthetic data generated for research and development
• No real customer data or personally identifiable information
• Designed to reflect realistic patterns without privacy concerns
• Safe for public use, testing, and education

License

GPL License - General Public License

This dataset is free to use for:

• Research and academic purposes
• Commercial applications
• Educational projects
• Open source development

Citation

@dataset{nigerian_retail_stock_and_inventory_levels_2025,
  title={Stock And Inventory Levels},
  author={Electric Sheep Africa},
  year={2025},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/datasets/electricsheepafrica/nigerian-retail-stock-and-inventory-levels}}
}

Related Datasets

This dataset is part of the Nigerian Retail & E-Commerce Datasets collection, which includes 42 datasets covering:

• Customer & Shopper Data
• Sales & Transactions
• Product & Inventory
• Marketing & Engagement
• Operations & Workforce
• Pricing & Revenue
• Customer Support
• Emerging & Advanced Technologies

Browse all datasets: https://huggingface.co/electricsheepafrica

Updates & Maintenance

• Version: 1.0
• Last Updated: 2025-10-06
• Maintenance: Active
• Issues: Report via Hugging Face discussions

Contact

For questions, feedback, or collaboration:

• Hugging Face: electricsheepafrica
• Issues: Open a discussion on the dataset page
• General Inquiries: Via Hugging Face profile

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Part of the Nigerian Industry Datasets Initiative
Building comprehensive, authentic datasets for African markets.