electricsheepafrica/africa-lake-chad-basin-baseline-population

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: other
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- tabular-classification
- other
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- baseline-population
- complex-emergency-conflict-security
- hxl
- cmr
- tcd
- ner
- nga
pretty_name: "Lake Chad Basin Baseline Population"
dataset_info:
splits:
- name: train
num_examples: 63
- name: test
num_examples: 15
---

# Lake Chad Basin Baseline Population

**Publisher:** OCHA West and Central Africa (ROWCA) · **Source:** [HDX](https://data.humdata.org/dataset/lake-chad-basin-baseline-population) · **License:** `other-pd-nr` · **Updated:** 2024-05-24

---

## Abstract

The data contains the latest estimated population of each administrative level 1 unit in the Lake Chad Basin. Estimation is based on input from UNFPA and the most recently available census for each country. Data is encoded as utf-8. The second row of the CSV contains [HXL](http://hxlstandard.org) tags.

Each row in this dataset represents country-level aggregates. Temporal coverage is indicated by the `asofdate` column(s). Geographic scope: **CMR, TCD, NER, NGA**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Conflict and security |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 79 |
| **Columns** | 6 (1 numeric, 4 categorical, 1 datetime) |
| **Train split** | 63 rows |
| **Test split** | 15 rows |
| **Geographic scope** | CMR, TCD, NER, NGA |
| **Publisher** | OCHA West and Central Africa (ROWCA) |
| **HDX last updated** | 2024-05-24 |

---

## Variables

**Geographic** — `country` (Nigeria, Chad, Cameroon), `reportedlocation` (#adm1+name, Cross River, Gombe).

**Temporal** — `asofdate`.

**Outcome / Measurement** — `totaltotal` (range 38913.0–12452097.0).

**Identifier / Metadata** — `esa_source` (HDX), `esa_processed` (2026-04-06).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-lake-chad-basin-baseline-population")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `country` | object | 0.0% | Nigeria, Chad, Cameroon |
| `reportedlocation` | object | 0.0% | #adm1+name, Cross River, Gombe |
| `totaltotal` | float64 | 1.3% | 38913.0 – 12452097.0 (mean 3016332.9359) |
| `asofdate` | datetime64[ns] | 1.3% | |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-06 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `totaltotal` | 38913.0 | 12452097.0 | 3016332.9359 | 2875695.5 |

---

## 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`. 2 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 OCHA West and Central Africa (ROWCA) and has not been independently validated by ESA.
- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
- This dataset spans 4 countries; geographic and methodological inconsistencies across national boundaries may affect cross-country comparability.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/lake-chad-basin-baseline-population) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_lake_chad_basin_baseline_population,
title = {Lake Chad Basin Baseline Population},
author = {OCHA West and Central Africa (ROWCA)},
year = {2024},
url = {https://data.humdata.org/dataset/lake-chad-basin-baseline-population},
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.*