Datasetpublic

electricsheepafrica/africa-angola-unicef-esaro-regional-db-31-march-2018-3a22c7f2

UNICEF ESARO Regional db 31 March 2018 | Africa (Angola official open data) 121 rows - 1 Africa country - 2017 - Repackaged by Electric Sheep Africa TL;DR This dataset packages one official XLSX resource from Angola 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: UNICEF ESARO Regional db 31 March 2018 Publisher:… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-angola-unicef-esaro-regional-db-31-march-2018-3a22c7f2.

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Dataset Card

UNICEF ESARO Regional db 31 March 2018 | Africa (Angola official open data)

121 rows - 1 Africa country - 2017 - Repackaged by Electric Sheep Africa

TL;DR

This dataset packages one official XLSX resource from Angola 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: UNICEF ESARO Regional db 31 March 2018
—Publisher: UNICEF Eastern and Southern Africa Regional Office (ESARO) (inactive)
—Resource: UNICEF ESARO Regional refugee db 30 September 2017.xlsx
—Format: XLSX
—License: CC BY 4.0
—Packaging mode: tabular_resource

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
`AGO`	121	2017	2017	`Angola`

Indicators or Resource Contents

—This source file is packaged as a normalized tabular resource.

Schema

Column	Type	Description	Example
`source_record_id`	`string`	Stable row identifier for tabular resources.	`7acc4932-835a-4ad7-ac4d-6ae15e399505:situation-and-funding-summary:0`
`country_iso3`	`category`	ISO3 country code.	`AGO`
`country_name`	`category`	Country name.	`Angola`
`source_sheet`	`string`	Workbook sheet name, when the source is a spreadsheet.	`Situation and Funding summary`
`year`	`Int64`	Observation year.	`2017`
`ethiopia`	`string`	Source column.	`Kenya`
`d_135901523`	`string`	Source column.	`41000000`
`d_312332`	`string`	Source column.	`72979`
`d_267132`	`string`	Source column.	`57471`
`d_19100000`	`string`	Source column.	`2454499`
`d_10580904`	`string`	Source column.	`1733000`
`d_8519096`	`string`	Source column.	`721499`
`d_0_44602596858638743`	`string`	Source column.	`0.2939496003053984`
`kenya`	`string`	Source column.	`Uganda`
`d_110377`	`string`	Source column.	`1034106`
`d_72848_82`	`string`	Source column.	`630804.66`
`d_0_66`	`float64`	Source column.	`0.61`
`source_period_start_year`	`Int64`	First year inferred from source resource metadata.	`2017`
`source_period_end_year`	`Int64`	Last year inferred from source resource metadata.	`2017`
`source_period_label`	`category`	Human-readable period inferred from source resource metadata.	`2017`
`source_provider`	`category`	Publishing organization.	`UNICEF Eastern and Southern Africa Regional Office (ESARO) (inactive)`
`source_dataset`	`category`	Source package title.	`UNICEF ESARO Regional db 31 March 2018`
`source_resource`	`category`	Source resource title.	`UNICEF ESARO Regional refugee db 30 September 2017.xlsx`
`source_package_id`	`category`	CKAN package UUID.	`e514b983-cf97-4af6-9fc9-ec2b62f1283b`
`source_resource_id`	`category`	CKAN resource UUID.	`7acc4932-835a-4ad7-ac4d-6ae15e399505`
`source_url`	`category`	Original source resource URL.	`https://data.humdata.org/dataset/e514b983-cf97-4af6-9fc9-ec2b62f1283b/re`
`license_id`	`category`	Source license identifier.	`cc-by`
`retrieved_at`	`category`	UTC retrieval timestamp.	`2026-08-17T20:52:25Z`
`sector`	`string`	Source column.	``
`indicator`	`string`	Source column.	``
`country`	`string`	Source column.	``
`2017`	`string`	Source column.	``
`2017_2`	`string`	Source column.	``
`gap`	`float64`	Source column.	``
`achieved`	`float64`	Source column.	``

Usage

python

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-angola-unicef-esaro-regional-db-31-march-2018-3a22c7f2")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

python

sample_country = df[df["country_iso3"] == "AGO"]

Work with indicators

python

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

bibtex

@misc{electric_sheep_africa_africa_angola_unicef_esaro_regional_db_31_march_2018_3a22c7f2_2017,
  title        = {UNICEF ESARO Regional db 31 March 2018 | Africa (Angola official open data)},
  author       = {UNICEF Eastern and Southern Africa Regional Office (ESARO) (inactive)},
  year         = {2017},
  url          = {https://data.humdata.org/dataset/unicef-esaro-regional-db-31-october-2017},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-angola-unicef-esaro-regional-db-31-march-2018-3a22c7f2}}
}

License

Released under CC BY 4.0.

Original data (c) UNICEF Eastern and Southern Africa Regional Office (ESARO) (inactive). 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 2026-08-17 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/e514b983-cf97-4af6-9fc9-ec2b62f1283b/resource/7acc4932-835a-4ad7-ac4d-6ae15e399505/download/unicef-esaro-regional-refugee-db-30-september-2017.xlsx