license: cc-by-4.0
language:
- en
task_categories:
- tabular-regression
- time-series-forecasting
multilinguality: monolingual
size_categories:
- n<1K
tags:
- tabular
- csv
- africa
- djibouti
- official-statistics
- open-data
configs:
- config_name: default
data_files:
- split: train
path: data/train-00000-of-00001.parquet
pretty_name: Djibouti - Urban Development | Africa (Djibouti official open data)
Djibouti - Urban Development | Africa (Djibouti official open data)
511 rows - 1 Africa country - 1960-2025 - Repackaged by Electric Sheep Africa
TL;DR
This dataset packages one official CSV resource from Djibouti as
ML-ready Parquet. The source file is the provenance boundary; all usable
indicators or tabular columns from the resource stay together in this repo.
About the source
- Source: Djibouti - Urban Development
- Publisher: World Bank Group
- Resource: Urban Development Indicators for Djibouti
- Format:
CSV - License: CC BY 4.0
- Packaging mode:
indicator_long
Geographic coverage
1 Africa country:
| Country | Rows | First year | Last year | Name |
|---|---|---|---|---|
DJI |
511 | 1960 | 2025 | Djibouti |
Indicators or Resource Contents
djibouti-urban-development-76ee3dc6- Djibouti - Urban Development
Schema
| Column | Type | Description | Example |
|---|---|---|---|
indicator_id |
string |
Stable indicator identifier. | djibouti-urban-development-76ee3dc6 |
indicator_name |
string |
Human-readable indicator name. | Djibouti - Urban Development |
country_iso3 |
string |
ISO3 country code. | DJI |
country_name |
string |
Country name. | Djibouti |
year |
Int64 |
Observation year. | 2015 |
value |
float64 |
Numeric observation value. | 8.39170619892 |
unit |
string |
Measurement unit, when available. | source_units_unspecified |
dimension_country_name |
string |
Source dimension. | Djibouti |
dimension_country_iso3 |
string |
Source dimension. | DJI |
dimension_indicator_name |
string |
Source dimension. | Urban land area where elevation is below 5 meters (sq. km) |
dimension_indicator_code |
string |
Source dimension. | AG.LND.EL5M.UR.K2 |
source_period_start_year |
Int64 |
First year inferred from source resource metadata. | `` |
source_period_end_year |
Int64 |
Last year inferred from source resource metadata. | `` |
source_period_label |
string |
Human-readable period inferred from source resource metadata. | `` |
source_provider |
category |
Publishing organization. | World Bank Group |
source_dataset |
category |
Source package title. | Djibouti - Urban Development |
source_resource |
category |
Source resource title. | Urban Development Indicators for Djibouti |
source_package_id |
category |
CKAN package UUID. | 3003be3c-5a25-4155-869a-6affb8bf7258 |
source_resource_id |
category |
CKAN resource UUID. | 0d62baac-8947-4553-9be7-72b33e03c62d |
source_url |
category |
Original source resource URL. | https://data.humdata.org/dataset/3003be3c-5a25-4155-869a-6affb8bf7258/re |
license_id |
category |
Source license identifier. | cc-by |
retrieved_at |
category |
UTC retrieval timestamp. | 2026-08-16T10:32:57Z |
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-djibouti-djibouti-urban-development-73d9baaa")
df = ds["train"].to_pandas()
print(df.head())
Filter to one country
sample_country = df[df["country_iso3"] == "DJI"]
Work with indicators
if "indicator_id" in df.columns:
print(df["indicator_id"].value_counts().head())
sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])
Citation
@misc{electric_sheep_africa_africa_djibouti_djibouti_urban_development_73d9baaa_2025,
title = {Djibouti - Urban Development | Africa (Djibouti official open data)},
author = {World Bank Group},
year = {2025},
url = {https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-djibouti},
publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-djibouti-djibouti-urban-development-73d9baaa}}
}
License
Released under CC BY 4.0.
Original data (c) World Bank Group. When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.
About Electric Sheep
Electric Sheep Africa is part of the Electric Sheep mission: a unified,
ML-ready data layer for Africa on Hugging Face. We pull data from authoritative
open sources, normalize the schemas, package as Parquet, and publish with
consistent dataset cards so researchers and developers can use load_dataset()
to start working in seconds.
Browse the full collection: huggingface.co/electricsheepafrica
Provenance: ingested 2026-08-16 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/3003be3c-5a25-4155-869a-6affb8bf7258/resource/0d62baac-8947-4553-9be7-72b33e03c62d/download/urban-development_dji.csv