electricsheepafrica/africa-cod-ps-gmb

---
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:
- other
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- baseline-population
- gazetteer
- gender-and-age-disaggregated-data-gadd
- hxl
- gmb
pretty_name: "Gambia - Subnational Population Statistics"
dataset_info:
splits:
- name: train
num_examples: 6
- name: test
num_examples: 1
---

# Gambia - Subnational Population Statistics

**Publisher:** OCHA West and Central Africa (ROWCA) · **Source:** [HDX](https://data.humdata.org/dataset/cod-ps-gmb) · **License:** `cc-by-igo` · **Updated:** 2025-07-22

---

## Abstract

Gambia administrative level 0 (country), 1 (local government area) 2021 population statistics

REFERENCE YEAR: 2021

These tables are suitable for database or GIS linkage to the [Gambia - Subnational Administrative Boundaries](https://data.humdata.org/dataset/cod-ab-gmb) layers using the ADM0 and ADM1_PCODE items.

Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2025-07-22. Geographic scope: **GMB**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Demographics and population |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 8 |
| **Columns** | 3 (0 numeric, 3 categorical, 0 datetime) |
| **Train split** | 6 rows |
| **Test split** | 1 rows |
| **Geographic scope** | GMB |
| **Publisher** | OCHA West and Central Africa (ROWCA) |
| **HDX last updated** | 2025-07-22 |

---

## Variables

**Geographic** — `iso3_adm0_name_adm0_pcode_adm1_name_adm1_pcode_f_tl_m_tl_t_tl_f_00_04_f_05_09_f_10_14_f_15_19_f_20_24_f_25_29_f_30_34_f_35_39_f_40_44_f_45_49_f_50_54_f_55_59_f_60_64_f_65_69_f_70_74_f_75_79_f_80plus_m_00_04_m_05_09_m_10_14_m_15_19_m_20_24_m_25_29_m_30_34_m_35_39_m_40_44_m_45_49_m_50_54_m_55_59_m_60_64_m_65_69_m_70_74_m_75_79_m_80plus_t_00_04_t_05_09_t_10_14_t_15_19_t_20_24_t_25_29_t_30_34_t_35_39_t_40_44_t_45_49_t_50_54_t_55_59_t_60_64_t_65_69_t_70_74_t_75_79_t_80plus` (GMB;GAMBIA;GM;Banjul;GM01;16745;17532;34277;2326;1887;1773;1753;1816;1461;1317;1012;791;758;563;504;263;201;167;95;57;2047;1548;1583;1621;1793;1827;1837;1437;1083;925;637;484;285;185;139;70;31;4373;3434;3356;3374;3610;3288;3154;2449;1874;1683;1200;988;548;386;306;165;89, GMB;GAMBIA;GM;Basse;GM02;142475;129680;272155;27228;22633;18585;14305;11399;10592;8521;7032;5595;4500;3564;2739;2131;1326;1247;664;414;26557;23345;19456;14381;9671;7973;6330;5008;3611;3364;2674;2158;1807;1220;1082;623;420;53785;45978;38040;28686;21070;18565;14851;12040;9206;7865;6239;4897;3937;2546;2329;1287;834, GMB;GAMBIA;GM;Brikama;GM03;420113;395803;815916;75433;63226;54163;46034;39305;32231;27808;22534;15253;13041;9421;7404;5372;3645;2778;1528;938;68568;56186;49071;43684;38237;31112;26318;21804;15956;14003;10060;7573;5256;3295;2486;1372;824;144001;119411;103234;89718;77542;63344;54126;44337;31209;27044;19480;14977;10628;6940;5264;2900;1761).

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

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-cod-ps-gmb")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `iso3_adm0_name_adm0_pcode_adm1_name_adm1_pcode_f_tl_m_tl_t_tl_f_00_04_f_05_09_f_10_14_f_15_19_f_20_24_f_25_29_f_30_34_f_35_39_f_40_44_f_45_49_f_50_54_f_55_59_f_60_64_f_65_69_f_70_74_f_75_79_f_80plus_m_00_04_m_05_09_m_10_14_m_15_19_m_20_24_m_25_29_m_30_34_m_35_39_m_40_44_m_45_49_m_50_54_m_55_59_m_60_64_m_65_69_m_70_74_m_75_79_m_80plus_t_00_04_t_05_09_t_10_14_t_15_19_t_20_24_t_25_29_t_30_34_t_35_39_t_40_44_t_45_49_t_50_54_t_55_59_t_60_64_t_65_69_t_70_74_t_75_79_t_80plus` | object | 0.0% | GMB;GAMBIA;GM;Banjul;GM01;16745;17532;34277;2326;1887;1773;1753;1816;1461;1317;1012;791;758;563;504;263;201;167;95;57;2047;1548;1583;1621;1793;1827;1837;1437;1083;925;637;484;285;185;139;70;31;4373;3434;3356;3374;3610;3288;3154;2449;1874;1683;1200;988;548;386;306;165;89, GMB;GAMBIA;GM;Basse;GM02;142475;129680;272155;27228;22633;18585;14305;11399;10592;8521;7032;5595;4500;3564;2739;2131;1326;1247;664;414;26557;23345;19456;14381;9671;7973;6330;5008;3611;3364;2674;2158;1807;1220;1082;623;420;53785;45978;38040;28686;21070;18565;14851;12040;9206;7865;6239;4897;3937;2546;2329;1287;834, GMB;GAMBIA;GM;Brikama;GM03;420113;395803;815916;75433;63226;54163;46034;39305;32231;27808;22534;15253;13041;9421;7404;5372;3645;2778;1528;938;68568;56186;49071;43684;38237;31112;26318;21804;15956;14003;10060;7573;5256;3295;2486;1372;824;144001;119411;103234;89718;77542;63344;54126;44337;31209;27044;19480;14977;10628;6940;5264;2900;1761 |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-06 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
_No numeric columns._

---

## 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 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.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/cod-ps-gmb) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_cod_ps_gmb,
title = {Gambia - Subnational Population Statistics},
author = {OCHA West and Central Africa (ROWCA)},
year = {2025},
url = {https://data.humdata.org/dataset/cod-ps-gmb},
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.*