---
license: mit
task_categories:
- tabular-regression
- tabular-classification
tags:
- nigeria
- oil-and-gas
- energy
- petroleum
- synthetic
language:
- en
size_categories:
- n<1K
data_type: synthetic
---

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

# Nigerian Oilgas Gas Production

## Dataset Description

This dataset is part of the **Nigerian Oil & Gas Sector** collection, containing comprehensive data on Nigeria's petroleum industry from 1999-2025.

- **Rows**: 324
- **Columns**: 13
- **Period**: 1999-2025 (where applicable)
- **License**: MIT

## Data Quality

- **1999-2014**: ⭐⭐⭐⭐⭐ Based on official NEITI data
- **2015-2025**: ⭐⭐⭐⭐ Validated synthetic (OPEC/NNPC sources)

## Schema

| Column | Type | Sample |
|--------|------|--------|
| `year` | int64 | 1999 |
| `month` | int64 | 1 |
| `year_month` | object | 1999-01 |
| `production_bpd` | float64 | 2088532.868972648 |
| `production_bbl` | float64 | 64744518.93815208 |
| `days_in_month` | int64 | 31 |
| `data_source` | object | NEITI Official Data |
| `data_quality` | object | official |
| `gas_production_mmscfd` | float64 | 313279.9303458972 |
| `gas_flared_mmscfd` | float64 | 78319.98258647429 |
| ... | ... | ... |
| *13 total columns* | | |

## Usage

```python
from datasets import load_dataset

dataset = load_dataset("electricsheepafrica/nigerian_oilgas_gas_production")
df = dataset['train'].to_pandas()
```

## Citation

```bibtex
@dataset{nigerian_oilgas_2025,
  title = {Nigerian Oil & Gas Sector Datasets},
  author = {Electric Sheep Africa},
  year = {2025},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/electricsheepafrica/nigerian_oilgas_gas_production}
}
```

## Collection

Part of: [Nigeria Oil & Gas Sector](https://huggingface.co/collections/electricsheepafrica/nigeria-oil-gas-sector)