---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- indicators
- poverty
- caf
pretty_name: "Central African Republic - Poverty"
dataset_info:
  splits:
    - name: train
      num_examples: 48
    - name: test
      num_examples: 12
---

# Central African Republic - Poverty

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

---

## Abstract

Contains data from the World Bank's [data portal](http://data.worldbank.org/). There is also a [consolidated country dataset](https://data.humdata.org/dataset/world-bank-combined-indicators-for-central-african-republic) on HDX.

For countries with an active poverty monitoring program, the World Bank—in collaboration with national institutions, other development agencies, and civil society—regularly conducts analytical work to assess the extent and causes of poverty and inequality, examine the impact of growth and public policy, and review household survey data and measurement methods.  Data here includes poverty and inequality measures generated from analytical reports, from national poverty monitoring programs, and from the World Bank’s Development Research Group which has been producing internationally comparable and global poverty estimates and lines since 1990.

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

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Poverty and economic vulnerability |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 60 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 48 rows |
| **Test split** | 12 rows |
| **Geographic scope** | CAF |
| **Publisher** | World Bank Group |
| **HDX last updated** | 2026-03-27 |

---

## Variables

**Geographic** — `country_name` (Central African Republic), `country_iso3` (CAF), `year` (range 1992.0–2022.0).

**Outcome / Measurement** — `value` (range 1.2–96.7).

**Identifier / Metadata** — `indicator_name` (Population living in slums (% of urban population), Poverty headcount ratio at $3.00 a day (2021 PPP) (% of population), Poverty headcount ratio at $8.30 a day (2021 PPP) (% of population)), `indicator_code` (EN.POP.SLUM.UR.ZS, SI.POV.DDAY, SI.POV.UMIC), `esa_source` (HDX), `esa_processed` (2026-04-16).

---

## Quick Start

```python
from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-world-bank-poverty-indicators-for-central-african-republic")
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% | Central African Republic |
| `country_iso3` | object | 0.0% | CAF |
| `year` | int64 | 0.0% | 1992.0 – 2022.0 (mean 2007.8) |
| `indicator_name` | object | 0.0% | Population living in slums (% of urban population), Poverty headcount ratio at $3.00 a day (2021 PPP) (% of population), Poverty headcount ratio at $8.30 a day (2021 PPP) (% of population) |
| `indicator_code` | object | 0.0% | EN.POP.SLUM.UR.ZS, SI.POV.DDAY, SI.POV.UMIC |
| `value` | float64 | 0.0% | 1.2 – 96.7 (mean 50.0107) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-16 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1992.0 | 2022.0 | 2007.8 | 2008.0 |
| `value` | 1.2 | 96.7 | 50.0107 | 60.25 |

---

## 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`. 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-poverty-indicators-for-central-african-republic) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_world_bank_poverty_indicators_for_central_african_republic,
  title     = {Central African Republic - Poverty},
  author    = {World Bank Group},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/world-bank-poverty-indicators-for-central-african-republic},
  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.*