electricsheepafrica/africa-world-bank-combined-indicators-for-congo-rep

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- tabular-classification
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- agriculture-livestock
- aid-effectiveness
- climate-weather
- development
- economics
- education
- energy
- environment
- cog
pretty_name: "Congo, Rep. - Economic, Social, Environmental, Health, Education, Development and Energy"
dataset_info:
splits:
- name: train
num_examples: 46425
- name: test
num_examples: 11606
---

# Congo, Rep. - Economic, Social, Environmental, Health, Education, Development and Energy

**Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-combined-indicators-for-congo-rep) · **License:** `cc-by` · **Updated:** 2026-03-27

---

## Abstract

Contains data from the World Bank's [data portal](http://data.worldbank.org/) covering the following topics which also exist as individual datasets on HDX: [Agriculture and Rural Development](https://data.humdata.org/dataset/world-bank-agriculture-and-rural-development-indicators-for-congo-rep), [Aid Effectiveness](https://data.humdata.org/dataset/world-bank-aid-effectiveness-indicators-for-congo-rep), [Economy and Growth](https://data.humdata.org/dataset/world-bank-economy-and-growth-indicators-for-congo-rep), [Education](https://data.humdata.org/dataset/world-bank-education-indicators-for-congo-rep), [Energy and Mining](https://data.humdata.org/dataset/world-bank-energy-and-mining-indicators-for-congo-rep), [Environment](https://data.humdata.org/dataset/world-bank-environment-indicators-for-congo-rep), [Financial Sector](https://data.humdata.org/dataset/world-bank-financial-sector-indicators-for-congo-rep), [Health](https://data.humdata.org/dataset/world-bank-health-indicators-for-congo-rep), [Infrastructure](https://data.humdata.org/dataset/world-bank-infrastructure-indicators-for-congo-rep), [Social Protection and Labor](https://data.humdata.org/dataset/world-bank-social-protection-and-labor-indicators-for-congo-rep), [Poverty](https://data.humdata.org/dataset/world-bank-poverty-indicators-for-congo-rep), [Private Sector](https://data.humdata.org/dataset/world-bank-private-sector-indicators-for-congo-rep), [Public Sector](https://data.humdata.org/dataset/world-bank-public-sector-indicators-for-congo-rep), [Science and Technology](https://data.humdata.org/dataset/world-bank-science-and-technology-indicators-for-congo-rep), [Social Development](https://data.humdata.org/dataset/world-bank-social-development-indicators-for-congo-rep), [Urban Development](https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-congo-rep), [Gender](https://data.humdata.org/dataset/world-bank-gender-indicators-for-congo-rep), [Millenium development goals](https://data.humdata.org/dataset/world-bank-millenium-development-goals-indicators-for-congo-rep), [Climate Change](https://data.humdata.org/dataset/world-bank-climate-change-indicators-for-congo-rep), [External Debt](https://data.humdata.org/dataset/world-bank-external-debt-indicators-for-congo-rep), [Trade](https://data.humdata.org/dataset/world-bank-trade-indicators-for-congo-rep).

Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-03-27. Geographic scope: **COG**.

*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Public health |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 58,032 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 46,425 rows |
| **Test split** | 11,606 rows |
| **Geographic scope** | COG |
| **Publisher** | World Bank Group |
| **HDX last updated** | 2026-03-27 |

---

## Variables

**Geographic** — `country_name` (Congo, Rep.), `country_iso3` (COG), `year` (range 1960.0–2025.0).

**Outcome / Measurement** — `value` (range -2617655000000.0–9969251000000.0).

**Identifier / Metadata** — `indicator_name` (Domestic credit to private sector (% of GDP), Population in urban agglomerations of more than 1 million, Population in urban agglomerations of more than 1 million (% of total population)), `indicator_code` (EN.URB.MCTY, EN.URB.LCTY, SM.POP.NETM), `esa_source` (HDX), `esa_processed` (2026-04-15).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-combined-indicators-for-congo-rep")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

print(train.shape)
train.head()
```

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `country_name` | object | 0.0% | Congo, Rep. |
| `country_iso3` | object | 0.0% | COG |
| `year` | int64 | 0.0% | 1960.0 – 2025.0 (mean 1997.4892) |
| `indicator_name` | object | 0.0% | Domestic credit to private sector (% of GDP), Population in urban agglomerations of more than 1 million, Population in urban agglomerations of more than 1 million (% of total population) |
| `indicator_code` | object | 0.0% | EN.URB.MCTY, EN.URB.LCTY, SM.POP.NETM |
| `value` | float64 | 0.0% | -2617655000000.0 – 9969251000000.0 (mean 59097228752.0625) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-15 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1960.0 | 2025.0 | 1997.4892 | 2000.0 |
| `value` | -2617655000000.0 | 9969251000000.0 | 59097228752.0625 | 52.1598 |

---

## Curation

Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (`N/A`, `null`, `none`, `-`, `unknown`, `no data`, `#N/A`) were unified to `NaN`. 17,372 exact duplicate rows were removed. The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.

---

## Limitations

- Data originates from World Bank Group and has not been independently validated by ESA.
- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/world-bank-combined-indicators-for-congo-rep) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_world_bank_combined_indicators_for_congo_rep,
title = {Congo, Rep. - Economic, Social, Environmental, Health, Education, Development and Energy},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-combined-indicators-for-congo-rep},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}
```

---

*[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*