electricsheepafrica/african-critical-minerals-reserves

---
license: cc-by-4.0
language:
- en
tags:
- extractives
- critical-minerals
- ev-battery
- lithium
- cobalt
- graphite
- nickel
- manganese
- platinum-group-metals
- rare-earths
- vanadium
- chromium
- copper
- africa
- supply-chain
- esg
- mining
- synthetic
pretty_name: African Critical Minerals Reserves
size_categories:
- 100K<n<1M
task_categories:
- tabular-regression
- time-series-forecasting
- scenario-analysis
dataset_info:
features:
- name: record_id
dtype: int64
- name: country
dtype: string
- name: country_code
dtype: string
- name: region
dtype: string
- name: mineral
dtype: string
- name: scenario
dtype: string
- name: year
dtype: int64
- name: mine_type
dtype: string
- name: project_status
dtype: string
- name: reserve_estimate_tonnes
dtype: int64
- name: production_volume_tonnes
dtype: int64
- name: grade_percent
dtype: float64
- name: extraction_cost_usd_per_tonne
dtype: float64
- name: market_price_usd_per_tonne
dtype: float64
- name: processing_capacity_tonnes
dtype: int64
- name: domestic_processing_rate_percent
dtype: float64
- name: export_volume_tonnes
dtype: int64
- name: investment_flows_usd_millions
dtype: float64
- name: chinese_investment_share_percent
dtype: float64
- name: esg_compliance_score
dtype: float64
- name: artisanal_production_percent
dtype: float64
- name: geopolitical_risk_index
dtype: float64
- name: infrastructure_quality_index
dtype: float64
- name: corruption_perception_index
dtype: float64
- name: political_stability_index
dtype: float64
- name: battery_chemistry_use
dtype: string
- name: ev_demand_share_percent
dtype: float64
- name: recycling_rate_percent
dtype: float64
- name: substitution_risk_index
dtype: float64
- name: supply_concentration_hhi
dtype: float64
- name: data_source
dtype: string
splits:
- name: baseline_demand
num_records: ~9000
- name: ev_acceleration
num_records: ~9000
- name: supply_chain_disruption
num_records: ~9000
- name: all
num_records: ~27000
configs:
- config_name: baseline_demand
description: "Current EV adoption trajectory with ~30% CAGR in battery mineral demand through 2030. Assumes gradual policy support and steady supply chain development."
data_files:
- split: baseline_demand
path: data/african_critical_minerals_baseline_demand.csv
production_growth_multiplier: 1.0
investment_multiplier: 1.0
price_multiplier: 1.0
esg_improvement_rate: 0.02
processing_capacity_growth: 0.06
geopolitical_risk_trend: 0.0
export_volume_growth: 0.05
artisanal_decline_rate: 0.01
supply_disruption_probability: 0.05
demand_shock: 0.0
- config_name: ev_acceleration
description: "Aggressive EV policies globally (EU ICE ban 2035, US IRA expansion, China NEV mandate). 50%+ CAGR in battery mineral demand. Massive investment inflows but supply constraints drive price spikes."
data_files:
- split: ev_acceleration
path: data/african_critical_minerals_ev_acceleration.csv
production_growth_multiplier: 1.5
investment_multiplier: 2.2
price_multiplier: 1.6
esg_improvement_rate: 0.035
processing_capacity_growth: 0.12
geopolitical_risk_trend: 0.02
export_volume_growth: 0.10
artisanal_decline_rate: 0.02
supply_disruption_probability: 0.08
demand_shock: 0.15
- config_name: supply_chain_disruption
description: "Major trade restrictions, export bans (DRC raw cobalt ban expansion, Zimbabwe lithium export ban enforcement), geopolitical shocks. Supply chain fragmentation, price volatility, forced domestic processing."
data_files:
- split: supply_chain_disruption
path: data/african_critical_minerals_supply_chain_disruption.csv
production_growth_multiplier: 0.6
investment_multiplier: 0.7
price_multiplier: 1.8
esg_improvement_rate: 0.005
processing_capacity_growth: 0.03
geopolitical_risk_trend: 0.05
export_volume_growth: -0.02
artisanal_decline_rate: -0.005
supply_disruption_probability: 0.25
demand_shock: -0.10
---

# African Critical Minerals Reserves

Comprehensive synthetic dataset modeling critical mineral reserves, production, trade flows, governance indicators, and supply chain dynamics across **20 African countries**, **10 critical minerals**, and **3 demand/supply scenarios** spanning **2020-2030**.

Designed for **EV/battery companies**, **mining investors**, **policy analysts**, and **supply chain risk modelers** evaluating Africa's role in the global energy transition.

## Dataset Summary

| Dimension | Value |
|---|---|
| Total records | ~27,000+ (9,000+ per scenario) |
| Countries | 20 (DRC, Zambia, Zimbabwe, South Africa, Namibia, Mozambique, Madagascar, Tanzania, Ghana, Mali, Guinea, Botswana, Morocco, Egypt, Kenya, Uganda, Rwanda, Burundi, Angola, Niger) |
| Minerals | 10 (lithium, cobalt, manganese, graphite, nickel, copper, rare earths, platinum group metals, vanadium, chromium) |
| Scenarios | 3 (baseline_demand, ev_acceleration, supply_chain_disruption) |
| Year range | 2020-2030 |
| Columns | 31 |
| Regions | Central, Southern, Eastern, West, North Africa |

## Research Sources & Calibration

Parameters are calibrated to peer-reviewed and industry sources:

- **USGS Mineral Commodity Summaries 2024-2025** - Reserve estimates, production volumes, grade ranges, global market shares for cobalt, lithium, nickel, copper, manganese, graphite, PGMs, chromium, vanadium, rare earths
- **IEA Global Critical Minerals Outlook 2024** - EV demand trajectories, battery chemistry demand shares, recycling rates, substitution risk assessments
- **African Mining Vision (AMV) 2024** - Critical minerals policy frameworks, domestic value addition baselines, artisanal mining prevalence
- **Benchmark Mineral Intelligence 2024** - Battery-grade mineral pricing, processing capacity constraints, supply chain concentration metrics (HHI)
- **S&P Global Market Intelligence 2024** - Mine-level production data, extraction cost curves, investment flow estimates
- **National critical minerals strategies** - DRC mining code 2018, Zimbabwe lithium export ban 2023, Zambia debt restructuring impacts, Namibia critical minerals policy 2023, South Africa Critical Minerals and Metals Strategy 2025

### Key Domain Facts Embedded

| Fact | Source |
|---|---|
| DRC produces ~74% of global cobalt (170kt of 230kt in 2023) | USGS MCS 2025 |
| South Africa holds ~90% of global PGM reserves (63kt of 70kt) | USGS MCS 2025, WPIC |
| Zimbabwe lithium reserves ~2.7Mt with 55kt production in 2023 | USGS MCS 2025, APRI |
| Mozambique graphite reserves ~25Mt, world's 2nd largest | Benchmark Minerals 2024 |
| South Africa manganese production ~6.5Mt (31% of global) | USGS MCS 2025 |
| DRC copper production ~2.6Mt (Copperbelt) | USGS MCS 2025 |
| Chinese investment dominates DRC (65%), Zimbabwe (55%), Guinea (50%) | S&P Global 2024 |
| Zimbabwe banned raw lithium exports (Feb 2023) | National policy |

## Scenarios

### baseline_demand
Current EV adoption trajectory with ~12-18% CAGR in battery mineral demand through 2030. Assumes gradual policy support, steady supply chain development, and moderate price appreciation. Production grows at historical rates, ESG scores improve slowly (~2%/yr), and geopolitical risk remains stable.

### ev_acceleration
Aggressive global EV policies: EU ICE ban by 2035, US IRA expansion, China NEV mandate strengthening. Battery mineral demand CAGR jumps to 22-28%. Massive investment inflows (2.2x baseline), but supply constraints drive 60% price premiums. Processing capacity expands rapidly (12%/yr), ESG improves faster (3.5%/yr), but geopolitical risk rises as competition intensifies.

### supply_chain_disruption
Major trade restrictions and geopolitical shocks: DRC raw cobalt export ban expansion, Zimbabwe lithium export ban enforcement, supply chain fragmentation. Production growth drops to 60% of baseline, investment falls to 70%, but prices spike 80%. Export volumes decline (-2%/yr), artisanal mining increases, and geopolitical risk rises sharply (5%/yr trend).

## Variables

### Identifiers
| Variable | Type | Description |
|---|---|---|
| record_id | int | Unique sequential identifier |
| country | string | Full country name |
| country_code | string | ISO 3166-1 alpha-3 code |
| region | string | African region (Central/Southern/Eastern/West/North) |
| mineral | string | Mineral name |
| scenario | string | Scenario name |
| year | int | Observation year (2020-2030) |

### Mining & Production
| Variable | Type | Description |
|---|---|---|
| mine_type | string | Mining method (open_pit, underground, alluvial_artisanal, laterite, brine, pegmatite) |
| project_status | string | Project lifecycle stage (operating, development, feasibility, exploration, care_maintenance, closed) |
| reserve_estimate_tonnes | int | Estimated mineral reserves in metric tonnes |
| production_volume_tonnes | int | Annual production volume in metric tonnes |
| grade_percent | float | Ore grade/quality metric (varies by mineral: % metal for base metals, % C for graphite, g/t for PGMs) |

### Economics
| Variable | Type | Description |
|---|---|---|
| extraction_cost_usd_per_tonne | float | All-in sustaining cost per tonne (grade-adjusted, infrastructure-adjusted) |
| market_price_usd_per_tonne | float | Simulated market price with scenario and volatility adjustments |
| processing_capacity_tonnes | int | Domestic processing/refining capacity in tonnes |
| domestic_processing_rate_percent | float | Percentage of production processed domestically (0-100) |
| export_volume_tonnes | int | Volume available for export after domestic processing |
| investment_flows_usd_millions | float | Annual mining sector investment inflows in USD millions |

### Governance & Risk
| Variable | Type | Description |
|---|---|---|
| chinese_investment_share_percent | float | Estimated share of investment from Chinese entities (0-100) |
| esg_compliance_score | float | ESG compliance score (0-100, higher = better) |
| artisanal_production_percent | float | Share of production from artisanal/small-scale mining (0-100) |
| geopolitical_risk_index | float | Composite geopolitical risk (0-100, higher = riskier) |
| infrastructure_quality_index | float | Infrastructure quality index (0-100) |
| corruption_perception_index | float | Corruption perception index (0-100, based on Transparency International scale) |
| political_stability_index | float | Political stability index (0-100) |

### Market Dynamics
| Variable | Type | Description |
|---|---|---|
| battery_chemistry_use | string | Primary battery/technology application |
| ev_demand_share_percent | float | Percentage of demand driven by EV/battery sector |
| recycling_rate_percent | float | Current global recycling rate for the mineral |
| substitution_risk_index | float | Risk of substitution by alternative materials (0-100) |
| supply_concentration_hhi | float | Herfindahl-Hirschman Index of global supply concentration (0-100) |
| data_source | string | Primary data source reference |

## Usage

```python
from datasets import load_dataset

# Load specific scenario
ds = load_dataset("electricsheepafrica/african-critical-minerals-reserves", "baseline_demand")

# Load all scenarios
ds = load_dataset("electricsheepafrica/african-critical-minerals-reserves")

# Access as pandas
df = ds["all"].to_pandas()

# Filter for DRC cobalt under EV acceleration
drc_cobalt = df[
(df["country"] == "Democratic Republic of Congo") &
(df["mineral"] == "cobalt") &
(df["scenario"] == "ev_acceleration")
]

# Analyze lithium supply risk by country
lithium_risk = df[df["mineral"] == "lithium"].groupby("country").agg({
"reserve_estimate_tonnes": "sum",
"production_volume_tonnes": "sum",
"geopolitical_risk_index": "mean",
"esg_compliance_score": "mean",
}).sort_values("geopolitical_risk_index", ascending=False)
```

## Reproduce

```bash
pip install -r requirements.txt
python generate_dataset.py
python validate_dataset.py
```

## File Structure

```
african-critical-minerals-reserves/
├── README.md
├── generate_dataset.py # Dataset generation script
├── validate_dataset.py # Validation script
├── requirements.txt # Python dependencies
└── data/
├── african_critical_minerals_baseline_demand.csv
├── african_critical_minerals_ev_acceleration.csv
├── african_critical_minerals_supply_chain_disruption.csv
└── african_critical_minerals_all.csv
```

## Limitations

- This is a **synthetic dataset** calibrated to published sources, not primary survey data
- Reserve estimates include geological uncertainty (lognormal distribution)
- Production projections assume no major new discoveries beyond known deposits
- Investment flows are modeled estimates, not actual committed capital
- ESG and governance scores are composite indices based on publicly available indicators
- Prices include volatility but do not model extreme tail events (e.g., pandemics, wars)
- Artisanal mining data is inherently uncertain; figures represent best estimates

## License

CC-BY-4.0

## Citation

```
@dataset{african_critical_minerals_reserves_2024,
title={African Critical Minerals Reserves Dataset},
author={Electric Sheep Africa},
year={2024},
url={https://huggingface.co/datasets/electricsheepafrica/african-critical-minerals-reserves},
note={Calibrated to USGS MCS 2024-2025, IEA GCMO 2024, Benchmark Minerals, S&P Global}
}
```