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electricsheepafrica/africa-sudan-sudan-flood-affected-people-from-2013-to-2020-802bfca1

Sudan - Flood Affected People from 2013 to 2020 | Africa (Sudan official open data) 134 rows - 1 Africa country - 2013-2020 - Repackaged by Electric Sheep Africa TL;DR This dataset packages one official XLSX resource from Sudan 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: Sudan - Flood Affected People from 2013 to… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-sudan-sudan-flood-affected-people-from-2013-to-2020-802bfca1.

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Dataset Card

Sudan - Flood Affected People from 2013 to 2020 | Africa (Sudan official open data)

134 rows - 1 Africa country - 2013-2020 - Repackaged by Electric Sheep Africa

rows countries years indicators license

TL;DR

This dataset packages one official XLSX resource from Sudan 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
SDN13420132020Sudan

Indicators or Resource Contents

  • —sudan-flood-affected-people-from-2013-to-2020-802bfca1 - Sudan - Flood Affected People from 2013 to 2020

Schema

ColumnTypeDescriptionExample
indicator_idstringStable indicator identifier.sudan-flood-affected-people-from-2013-to-2020-802bfca1
indicator_namestringHuman-readable indicator name.Sudan - Flood Affected People from 2013 to 2020
country_iso3stringISO3 country code.SDN
source_sheetstringWorkbook sheet name, when the source is a spreadsheet.Afffected ppl per state & year
country_namestringCountry name.Sudan
yearInt64Observation year.2013
valuefloat64Numeric observation value.184410.0
unitstringMeasurement unit, when available.source_units_unspecified
dimension_statestringSource dimension.Khartoum
dimension_averagestringSource dimension.47672.857142857145
source_period_start_yearInt64First year inferred from source resource metadata.2013
source_period_end_yearInt64Last year inferred from source resource metadata.2020
source_period_labelcategoryHuman-readable period inferred from source resource metadata.2013-2020
source_providercategoryPublishing organization.OCHA Sudan
source_datasetcategorySource package title.Sudan - Flood Affected People from 2013 to 2020
source_resourcecategorySource resource title.Floods-Affected-People_Sudan_2013-to-2020.xlsx
source_package_idcategoryCKAN package UUID.d80d6da2-a634-4d2a-9dc8-6f73804dbf3e
source_resource_idcategoryCKAN resource UUID.ab735cf3-4633-477c-a17a-b470e6c4bd8b
source_urlcategoryOriginal source resource URL.https://data.humdata.org/dataset/d80d6da2-a634-4d2a-9dc8-6f73804dbf3e/re
license_idcategorySource license identifier.cc-by
retrieved_atcategoryUTC retrieval timestamp.2026-08-19T06:27:19Z

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-sudan-sudan-flood-affected-people-from-2013-to-2020-802bfca1")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

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

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_sudan_sudan_flood_affected_people_from_2013_to_2020_802bfca1_2020,
  title        = {Sudan - Flood Affected People from 2013 to 2020 | Africa (Sudan official open data)},
  author       = {OCHA Sudan},
  year         = {2020},
  url          = {https://data.humdata.org/dataset/sudan-flood-affected-people-from-2013-to-2020},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-sudan-sudan-flood-affected-people-from-2013-to-2020-802bfca1}}
}

License

Released under CC BY 4.0.

Original data (c) OCHA Sudan. 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 2026-08-19 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/d80d6da2-a634-4d2a-9dc8-6f73804dbf3e/resource/ab735cf3-4633-477c-a17a-b470e6c4bd8b/download/floods-affected-peoplesudan2013-to-2020.xlsx