--- license: gpl task_categories: - tabular-classification - text-classification language: - en tags: - retail - ecommerce - nigeria - synthetic-data - inventory - supply-chain - synthetic size_categories: - 100K ⚠️ **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 ```python 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) ```python 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 ```python 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 ```bibtex @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 --- **Part of the Nigerian Industry Datasets Initiative** Building comprehensive, authentic datasets for African markets.