electricsheepafrica/africa-central-african-republic-republique-centrafricaine-situation-des-inondations-e1e8aca0

République Centrafricaine : Situation des Inondations | Africa (Central African Republic official open data)

715 rows - 1 Africa country - 2022 - Repackaged by Electric Sheep Africa

TL;DR

This dataset packages one official XLSX resource from Central African Republic 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: République Centrafricaine : Situation des Inondations
• Publisher: OCHA Central African Republic
• Resource: OCHA CAR_DONNEES-INONDATIONS_DATA_COMPPIL_6122022
• Format: XLSX
• License: CC BY 4.0
• Packaging mode: tabular_resource

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
CAF	715	2022	2022	Central African Republic

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.	dff21492-ea0b-442d-9b79-3fd7c7ffb367:personnes-affectees-impacts:0
country_iso3	category	ISO3 country code.	CAF
country_name	category	Country name.	Central African Republic
source_sheet	string	Workbook sheet name, when the source is a spreadsheet.	Personnes affectées-Impacts
year	Int64	Observation year.	2022
prefecture	string	Source column.	#adm1+name
sous_prefecture	string	Source column.	adm2+name
commune	string	Source column.	#adm3+name
type_localite	string	Source column.	``
localite_s	string	Source column.	``
menage_affecte	float64	Source column.	``
individus_affecte	float64	Source column.	``
column1	float64	Source column.	``
date_alerte	string	Source column.	#date
alerte_rrm	string	Source column.	``
source_s	string	Source column.	``
commentaires	string	Source column.	``
infrastructures_privees_ecroulees_maisons_boutiques	float64	Source column.	``
infrastructures_privees_a_toitures_emportees_maisons_bou	float64	Source column.	``
infrastructures_privees_maisons_boutiques_affectees	float64	Source column.	``
infrastructures_publiques_administratives	float64	Source column.	``
infrastructures_publiques_educatives	float64	Source column.	``
infrastructures_publiques_sanitaires	float64	Source column.	``
infrastructures_publiques_religieuses	float64	Source column.	``
blessures	string	Source column.	``
perte_en_vie_humaine	string	Source column.	``
autre	string	Source column.	``
superficie_cultivable_affectee_ha	float64	Source column.	``
mouvement_de_population	string	Source column.	``
si_mvt_de_pop_preciser_ampleur_nb_men	float64	Source column.	``
si_mvt_de_pop_preciser_ou_choisir_la_liste	string	Source column.	``
si_mvt_de_pop_preciser_le_lieu_exact	string	Source column.	``
si_mvt_de_pop_preciser_si_en_fa_ou_site	string	Source column.	``
commentaire	string	Source column.	``
source_period_start_year	Int64	First year inferred from source resource metadata.	2022
source_period_end_year	Int64	Last year inferred from source resource metadata.	2022
source_period_label	category	Human-readable period inferred from source resource metadata.	2022
source_provider	category	Publishing organization.	OCHA Central African Republic
source_dataset	category	Source package title.	République Centrafricaine : Situation des Inondations
source_resource	category	Source resource title.	OCHA CAR_DONNEES-INONDATIONS_DATA_COMPPIL_6122022
source_package_id	category	CKAN package UUID.	3e230b3f-e0d7-4c7d-a788-0d4c82d8f814
source_resource_id	category	CKAN resource UUID.	dff21492-ea0b-442d-9b79-3fd7c7ffb367
source_url	category	Original source resource URL.	https://data.humdata.org/dataset/3e230b3f-e0d7-4c7d-a788-0d4c82d8f814/re
license_id	category	Source license identifier.	cc-by
retrieved_at	category	UTC retrieval timestamp.	2026-08-14T23:28:30Z
localite	string	Source column.	``
acteurs	string	Source column.	``
count	float64	Source column.	``
type_acteur	string	Source column.	``
menages_assistes	float64	Source column.	``
individus_assistes	float64	Source column.	``
type_reponse	string	Source column.	``
id	string	Source column.	``
check_assistance	float64	Source column.	``
check	float64	Source column.	``
kits_abris	float64	Source column.	``
kit_nfi	float64	Source column.	``
abri_finalise	float64	Source column.	``
nb_comite_hygiene	float64	Source column.	``
kit_eha	float64	Source column.	``
latrines_construites	float64	Source column.	``
douches_construites	float64	Source column.	``
latrines_rehabilitees	float64	Source column.	``
robinet_rehabilites	float64	Source column.	``
pers_snsibilisees_sur_eha	float64	Source column.	``
forage_rehabilite	float64	Source column.	``
aquatabs	float64	Source column.	``
volume_d_eau_offert_l	float64	Source column.	``
forage	float64	Source column.	``
robinet	float64	Source column.	``
water_tracking_blader	float64	Source column.	``
puits_rehabilites	float64	Source column.	``
depistage	float64	Source column.	``
mam	float64	Source column.	``
mas	float64	Source column.	``
soutien_psycho_parents	float64	Source column.	``
suivi_mas	float64	Source column.	``
nb_consultations	float64	Source column.	``
prise_en_charge	float64	Source column.	``
moustiquaire	float64	Source column.	``
antipaludeen	float64	Source column.	``
poste_fixe	float64	Source column.	``
clinique_mobile	float64	Source column.	``
pec_vbg	float64	Source column.	``
kit_sr	float64	Source column.	``
pers_couvertes_kit_sr	float64	Source column.	``
de_biscuit	float64	Source column.	``
volume_vivres	float64	Source column.	``
beneficiaire_pers	float64	Source column.	``
beneficiaire_menag	float64	Source column.	``
montant_in_kind	float64	Source column.	``
bangui	string	Source column.	``
d_34580	float64	Source column.	``
d_individus	float64	Source column.	``
kabo	string	Source column.	``
d_3320	float64	Source column.	``
d_3417	float64	Source column.	``
d_77000	string	Source column.	``
d_0_6441358541074117	string	Source column.	``
column_4	float64	Source column.	``
bria	string	Source column.	``
d_1493	float64	Source column.	``
column_9	float64	Source column.	``
ngaoundaye	string	Source column.	``
d_630	float64	Source column.	``
ngaoundaye_2	string	Source column.	``
crca	string	Source column.	``
d_1	float64	Source column.	``
mcr	string	Source column.	``
d_1_2	float64	Source column.	``
d_0_06666666666666667	float64	Source column.	``
d_1394	float64	Source column.	``
column_3	string	Source column.	``
d_885	float64	Source column.	``
column_6	float64	Source column.	``
pagne_de_6_yards_1	string	Source column.	``
gov	string	Source column.	``
d_2	float64	Source column.	``
d_0_11764705882352941	float64	Source column.	``
org	string	Source column.	``
type	string	Source column.	``
pcode1	string	Source column.	``
pcode2	string	Source column.	``
secteur	string	Source column.	``
acteur	string	Source column.	``
description_acteur	string	Source column.	``
spref_code	string	Source column.	``
longitude	float64	Source column.	``
latitude	float64	Source column.	``
region	string	Source column.	``
zone	string	Source column.	``
sous_prefecture_2	string	Source column.	``
pcode2_2	string	Source column.	``
lib3	string	Source column.	``
prefecture_2	string	Source column.	``
sigle	string	Source column.	``
type_org	string	Source column.	``
sigle_eng	string	Source column.	``
description_eng	string	Source column.	``
org_type	string	Source column.	``
lt	string	Source column.	``
type_org_2	string	Source column.	``
type_org_eng	string	Source column.	``
cluster	string	Source column.	``
cluster_eng	string	Source column.	``

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-central-african-republic-republique-centrafricaine-situation-des-inondations-e1e8aca0")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

sample_country = df[df["country_iso3"] == "CAF"]

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_central_african_republic_republique_centrafricaine_situation_des_inondati_2022,
  title        = {République Centrafricaine : Situation des Inondations | Africa (Central African Republic official open data)},
  author       = {OCHA Central African Republic},
  year         = {2022},
  url          = {https://data.humdata.org/dataset/republique-centrafricaine-situation-des-inondations},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-central-african-republic-republique-centrafricaine-situation-des-inondations-e1e8aca0}}
}

License

Released under CC BY 4.0.

Original data (c) OCHA Central African Republic. 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

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Provenance: ingested 2026-08-15 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/3e230b3f-e0d7-4c7d-a788-0d4c82d8f814/resource/dff21492-ea0b-442d-9b79-3fd7c7ffb367/download/ocha-car_donnees-inondations_data_comppil_6122022.xlsx