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electricsheepafrica/africa-burundi-unicef-esaro-regional-db-31-march-2018-0c412acd

UNICEF ESARO Regional db 31 March 2018 | Africa (Burundi official open data) 341 rows - 1 Africa country - 2018 - Repackaged by Electric Sheep Africa TL;DR This dataset packages one official XLSX resource from Burundi 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-burundi-unicef-esaro-regional-db-31-march-2018-0c412acd.

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Dataset Card

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

341 rows - 1 Africa country - 2018 - Repackaged by Electric Sheep Africa

rows countries years indicators license

TL;DR

This dataset packages one official XLSX resource from Burundi 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

Geographic coverage

1 Africa country:

CountryRowsFirst yearLast yearName
BDI34120182018Burundi

Indicators or Resource Contents

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

Schema

ColumnTypeDescriptionExample
source_record_idstringStable row identifier for tabular resources.adb88e5f-85e0-4f2a-b69c-018ebd3e6ffe:guidance-dates-of-update:0
country_iso3categoryISO3 country code.BDI
country_namecategoryCountry name.Burundi
source_sheetstringWorkbook sheet name, when the source is a spreadsheet.Guidance & Dates of update
yearInt64Observation year.2018
countrystringSource column.Ethiopia
date_of_updatestringSource column.2018-04-05 00:00:00
source_period_start_yearInt64First year inferred from source resource metadata.2018
source_period_end_yearInt64Last year inferred from source resource metadata.2018
source_period_labelcategoryHuman-readable period inferred from source resource metadata.2018
source_providercategoryPublishing organization.UNICEF Eastern and Southern Africa Regional Office (ESARO) (inactive)
source_datasetcategorySource package title.UNICEF ESARO Regional db 31 March 2018
source_resourcecategorySource resource title.UNICEF ESARO Regional db 2018.xlsx
source_package_idcategoryCKAN package UUID.e514b983-cf97-4af6-9fc9-ec2b62f1283b
source_resource_idcategoryCKAN resource UUID.adb88e5f-85e0-4f2a-b69c-018ebd3e6ffe
source_urlcategoryOriginal source resource URL.https://data.humdata.org/dataset/e514b983-cf97-4af6-9fc9-ec2b62f1283b/re
license_idcategorySource license identifier.cc-by
retrieved_atcategoryUTC retrieval timestamp.2026-08-15T08:23:53Z
sourcestringSource column.``
hrpstringSource column.``
hrp_hrd_flash_appealfloat64Source column.``
hacfloat64Source column.``
hac_unicef_sitrepfloat64Source column.``
hac_unicef_sitrep_2float64Source column.``
fewsnet_flash_appeal_riasco_plan_2016_2017stringSource column.``
hrp_hrd_flash_appeal_2stringSource column.``
hrp_hrd_flash_appeal_3stringSource column.``
hrd_hacstringSource column.``
unesco_uisstringSource column.``
hac_unicefstringSource column.``
hac_unicef_2stringSource column.``
sectorstringSource column.``
indicatorstringSource column.``
2018float64Source column.``
latest_resultsfloat64Source column.``
gapfloat64Source column.``
achievedfloat64Source column.``
resultsfloat64Source column.``
sector_2stringSource column.``
indicator_2stringSource column.``
country_2stringSource column.``
2018_2float64Source column.``
results_2float64Source column.``
gap_2float64Source column.``
achieved_2float64Source column.``
eritreastringSource column.``
d_14000000stringSource column.``
d_5260275stringSource column.``
d_8739725stringSource column.``
d_0_6242660714285714stringSource column.``
burundistringSource column.``
d_26000000stringSource column.``
d_1782684stringSource column.``
d_24217316stringSource column.``
d_0_9314352307692307stringSource column.``
angolastringSource column.``
d_14660000stringSource column.``
d_951636stringSource column.``
d_13708364stringSource column.``
d_0_9350862210095497stringSource column.``
hac_requirement_usstringSource column.``
d_111810939float64Source column.``
d_34235000float64Source column.``
d_154932574float64Source column.``
d_300978513float64Source column.``
d_183309871float64Source column.``
d_66119117float64Source column.``
d_92119117float64Source column.``
d_23750000float64Source column.``
d_38410000float64Source column.``
d_614817501float64Source column.``
washstringSource column.``
of_people_reached_with_key_messages_of_hygiene_practicesstringSource column.``
d_60000float64Source column.``
d_55000float64Source column.``
d_0_08333333333333333float64Source column.``
child_protectionstringSource column.``
d_850000float64Source column.``
d_162281float64Source column.``
d_687719float64Source column.``
d_0_8090811764705882float64Source column.``
healthstringSource column.``
of_children_vaccinated_against_measlesstringSource column.``
d_56000float64Source column.``
d_6411float64Source column.``
d_49589float64Source column.``
d_0_11448214285714285float64Source column.``
nutritionstringSource column.``
d_41610000float64Source column.``
d_6215627float64Source column.``
d_35394373float64Source column.``
d_0_850621797644797float64Source column.``
cpstringSource column.``
of_uasc_receiving_protection_servicesstringSource column.``
d_30000float64Source column.``
d_3553float64Source column.``
d_26447float64Source column.``
d_0_11843333333333333float64Source column.``
d_1000000float64Source column.``
d_874991float64Source column.``
d_125009float64Source column.``
d_0_125009float64Source column.``
of_people_with_access_to_safe_waterstringSource column.``
d_702000float64Source column.``
d_53092float64Source column.``
d_648908float64Source column.``
d_0_07562962962962963float64Source column.``
of_people_with_sustained_access_to_safe_water_through_nestringSource column.``
d_34279200float64Source column.``
d_4917244float64Source column.``
d_29361956float64Source column.``
d_0_8565531284277346float64Source column.``
of_children_receiving_psychosocial_support_servicesstringSource column.``
d_250000float64Source column.``
d_57172float64Source column.``
d_192828float64Source column.``
d_0_228688float64Source column.``
d_26669780float64Source column.``
d_7705215float64Source column.``
d_18964565float64Source column.``
d_0_7110881679563911float64Source column.``
d_200000float64Source column.``
d_3000float64Source column.``
d_197000float64Source column.``
d_0_015float64Source column.``
wash_2stringSource column.``
d_6000000float64Source column.``
d_29416float64Source column.``
d_5970584float64Source column.``
d_0_9950973333333333float64Source column.``
educationstringSource column.``
of_children_accessing_quality_educationstringSource column.``
d_123361float64Source column.``
d_30836float64Source column.``
d_92525float64Source column.``
d_0_24996554826890183float64Source column.``
of_people_reached_with_key_messages_on_hygiene_practicesstringSource column.``
d_470000float64Source column.``
d_340000float64Source column.``
d_0_2765957446808511float64Source column.``
d_7200000float64Source column.``
d_809442float64Source column.``
d_6390558float64Source column.``
d_0_8875775float64Source column.``
of_children_in_humanitarian_situations_accessing_approprstringSource column.``
d_5000float64Source column.``
d_5000_2float64Source column.``
d_0float64Source column.``
d_0_2float64Source column.``
d_1000000_2float64Source column.``
d_1float64Source column.``

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-burundi-unicef-esaro-regional-db-31-march-2018-0c412acd")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

python
sample_country = df[df["country_iso3"] == "BDI"]

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_burundi_unicef_esaro_regional_db_31_march_2018_0c412acd_2018,
  title        = {UNICEF ESARO Regional db 31 March 2018 | Africa (Burundi official open data)},
  author       = {UNICEF Eastern and Southern Africa Regional Office (ESARO) (inactive)},
  year         = {2018},
  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-burundi-unicef-esaro-regional-db-31-march-2018-0c412acd}}
}

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 2026-08-15 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/e514b983-cf97-4af6-9fc9-ec2b62f1283b/resource/adb88e5f-85e0-4f2a-b69c-018ebd3e6ffe/download/unicef-esaro-regional-db-2018.xlsx