Sammylayo/nigerian_retail_and_ecommerce_revenue_and_profit_data

---
license: gpl
task_categories:
- tabular-regression
- time-series-forecasting
language:
- en
tags:
- retail
- ecommerce
- nigeria
- synthetic-data
- pricing
- revenue
size_categories:
- 100K<n<1M
pretty_name: Revenue And Profit Data
---

# Revenue And Profit Data

## Dataset Description

Comprehensive revenue and profit data for Nigerian retail and e-commerce analysis

## Dataset Information

- **Category**: Pricing and Revenue
- **Industry**: Retail & E-Commerce
- **Country**: Nigeria
- **Format**: CSV, Parquet
- **Rows**: 200,000
- **Columns**: 10
- **Date Generated**: 2025-10-06
- **Location**: `data/revenue_and_profit_data/`
- **License**: GPL

## Schema

| Column | Type | Sample Values |
|--------|------|---------------|
| `record_id` | String | REV0000000 |
| `product_id` | String | PRD22956 |
| `category` | String | Groceries |
| `city` | String | Calabar |
| `date` | String | 2024-04-12 |
| `revenue_ngn` | Float | 8935847.11 |
| `cost_ngn` | Float | 6473962.33 |
| `profit_ngn` | Float | 2461884.7799999993 |
| `profit_margin` | Float | 0.2755 |
| `units_sold` | Integer | 944 |

## Sample Data

```
record_id product_id category city date revenue_ngn cost_ngn profit_ngn profit_margin units_sold
REV0000000 PRD22956 Groceries Calabar 2024-04-12 8935847.11 6473962.33 2461884.78 0.2755 944
REV0000001 PRD54925 Fashion Enugu 2024-03-25 5369186.80 4362043.61 1007143.19 0.1876 894
REV0000002 PRD98221 Groceries Enugu 2024-05-01 3443662.89 2910830.34 532832.55 0.1547 368
```

## 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/revenue_and_profit_data/nigerian_retail_and_ecommerce_revenue_and_profit_data.csv
```

### Parquet (Recommended)
```
data/revenue_and_profit_data/nigerian_retail_and_ecommerce_revenue_and_profit_data.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_revenue_and_profit_data")

# 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/revenue_and_profit_data/nigerian_retail_and_ecommerce_revenue_and_profit_data.csv')

# Load Parquet (recommended for large datasets)
df = pd.read_parquet('data/revenue_and_profit_data/nigerian_retail_and_ecommerce_revenue_and_profit_data.parquet')
```

### PyArrow

```python
import pyarrow.parquet as pq

# Load Parquet
table = pq.read_table('data/revenue_and_profit_data/nigerian_retail_and_ecommerce_revenue_and_profit_data.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_revenue_and_profit_data_2025,
title={Revenue And Profit Data},
author={Electric Sheep Africa},
year={2025},
publisher={Hugging Face},
howpublished={\url{https://huggingface.co/datasets/electricsheepafrica/nigerian-retail-revenue-and-profit-data}}
}
```

## 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.