---
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
- baseline-population
- migration
- caf
pretty_name: "CENTRAL AFRICAN REPUBLIC - Population and migration indicators, UNECA"
dataset_info:
  splits:
    - name: train
      num_examples: 33
    - name: test
      num_examples: 8
---

# CENTRAL AFRICAN REPUBLIC - Population and migration indicators, UNECA

**Publisher:** United Nations Economic Commission for Africa · **Source:** [HDX](https://data.humdata.org/dataset/central-african-republic-uneca-population-and-migration) · **License:** `cc-by-igo` · **Updated:** 2024-09-13

---

## Abstract

This dataset contains many indicators related to population and migration such as Average annual population growth rate, Population 15-19 , Annual rate of change of the migrant stock, International migrant stock at mid-year, etc. The whole list and their description can be find in this link https://bit.ly/2ODhFQh

Each row in this dataset represents tabular records. Data was last updated on HDX on 2024-09-13. Geographic scope: **CAF**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Demographics and population |
| **Unit of observation** | Tabular records |
| **Rows (total)** | 42 |
| **Columns** | 51 (15 numeric, 36 categorical, 0 datetime) |
| **Train split** | 33 rows |
| **Test split** | 8 rows |
| **Geographic scope** | CAF |
| **Publisher** | United Nations Economic Commission for Africa |
| **HDX last updated** | 2024-09-13 |

---

## Variables

**Identifier / Metadata** — `esa_source`, `esa_processed`.

**Other** — `indicator` (Average annual population growth rate - Total (%), Net reproduction rate (per woman), Life expectancy at birth - Total (years)), `1970` (range 1.8–930.1), `1971` (range 1.9–948.5), `1972` (range 1.9–966.8), `1973` (range 1.9–985.6) and 44 others.

---

## Quick Start

```python
from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-central-african-republic-uneca-population-and-migration")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `indicator` | object | 0.0% | Average annual population growth rate - Total (%), Net reproduction rate (per woman), Life expectancy at birth - Total (years) |
| `1970` | float64 | 50.0% | 1.8 – 930.1 (mean 226.7286) |
| `1971` | float64 | 50.0% | 1.9 – 948.5 (mean 231.3762) |
| `1972` | float64 | 50.0% | 1.9 – 966.8 (mean 235.9476) |
| `1973` | float64 | 50.0% | 1.9 – 985.6 (mean 240.5333) |
| `1974` | float64 | 52.4% | 2.0 – 970.7 (mean 207.32) |
| `1975` | float64 | 52.4% | 2.0 – 991.0 (mean 211.51) |
| `1976` | float64 | 54.8% | 2.1 – 863.9 (mean 174.2368) |
| `1977` | float64 | 54.8% | 2.1 – 886.5 (mean 178.1105) |
| `1978` | float64 | 54.8% | 2.2 – 909.6 (mean 182.2) |
| `1979` | float64 | 54.8% | 2.2 – 934.1 (mean 186.5789) |
| `1980` | float64 | 54.8% | 2.3 – 960.7 (mean 191.3158) |
| `1981` | float64 | 54.8% | 2.3 – 990.7 (mean 196.5684) |
| `1982` | object | 47.6% | 3.0, 3.8, 99.0 |
| `1983` | object | 47.6% | 3.0, 3.8, 101.4 |
| `1984` | object | 47.6% | 2.8, 3.8, 103.6 |
| `1985` | object | 47.6% | 2.5, 2.8, 105.7 |
| `1986` | object | 47.6% | 2.3, 2.8, 108.5 |
| `1987` | object | 47.6% | 49.7, 2.8, 2.2 |
| `1988` | object | 47.6% | 2.8, 2.1, 606.7 |
| `1989` | object | 47.6% | 2.2, 2.8, 115.5 |
| `1990` | float64 | 14.3% | 1.3 – 793.1 (mean 100.3389) |
| `1991` | object | 47.6% | 2.5, 2.6, 120.9 |
| `1992` | object | 47.6% |  |
| `1993` | object | 47.6% |  |
| `1994` | object | 47.6% |  |
| `1995` | float64 | 14.3% | 2.0 – 911.0 (mean 114.4417) |
| `1996` | object | 47.6% |  |
| `1997` | object | 47.6% |  |
| `1998` | object | 47.6% |  |
| `1999` | object | 47.6% |  |
| `2000` | float64 | 16.7% | 1.9 – 984.5 (mean 101.9486) |
| `2001` | object | 45.2% |  |
| `2002` | object | 45.2% |  |
| `2003` | object | 45.2% |  |
| `2004` | object | 45.2% |  |
| `2005` | object | 0.0% |  |
| `2006` | object | 45.2% |  |
| `2007` | object | 45.2% |  |
| `2008` | object | 45.2% |  |
| `2009` | object | 45.2% |  |
| `2010` | object | 0.0% |  |
| `2011` | object | 45.2% |  |
| `2012` | object | 45.2% |  |
| `2013` | object | 47.6% |  |
| `2014` | object | 47.6% |  |
| `2015` | object | 4.8% |  |
| `2016` | object | 50.0% |  |
| `2017` | object | 31.0% |  |
| `esa_source` | object | 0.0% |  |
| `esa_processed` | object | 0.0% |  |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `1970` | 1.8 | 930.1 | 226.7286 | 43.1 |
| `1971` | 1.9 | 948.5 | 231.3762 | 43.0 |
| `1972` | 1.9 | 966.8 | 235.9476 | 43.6 |
| `1973` | 1.9 | 985.6 | 240.5333 | 44.6 |
| `1974` | 2.0 | 970.7 | 207.32 | 45.25 |
| `1975` | 2.0 | 991.0 | 211.51 | 46.1 |
| `1976` | 2.1 | 863.9 | 174.2368 | 46.6 |
| `1977` | 2.1 | 886.5 | 178.1105 | 47.3 |
| `1978` | 2.2 | 909.6 | 182.2 | 47.9 |
| `1979` | 2.2 | 934.1 | 186.5789 | 48.4 |
| `1980` | 2.3 | 960.7 | 191.3158 | 48.9 |
| `1981` | 2.3 | 990.7 | 196.5684 | 49.3 |
| `1990` | 1.3 | 793.1 | 100.3389 | 7.8 |
| `1995` | 2.0 | 911.0 | 114.4417 | 12.05 |
| `2000` | 1.9 | 984.5 | 101.9486 | 12.5 |

---

## 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`. 15 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). 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 United Nations Economic Commission for Africa and has not been independently validated by ESA.
- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
- The following columns have >20% missing values and should be treated with caution in modelling: `1970`, `1971`, `1972`, `1973`, `1974`, `1975`, `1976`, `1977`....
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/central-african-republic-uneca-population-and-migration) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_central_african_republic_uneca_population_and_migration,
  title     = {CENTRAL AFRICAN REPUBLIC - Population and migration indicators, UNECA},
  author    = {United Nations Economic Commission for Africa},
  year      = {2024},
  url       = {https://data.humdata.org/dataset/central-african-republic-uneca-population-and-migration},
  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.*