electricsheepafrica/africa-mauritania-the-regional-inform-sahel-model-bf031eeb

The regional INFORM Sahel model | Africa (Mauritania official open data)

745 rows - 1 Africa country - 2021 - Repackaged by Electric Sheep Africa

TL;DR

This dataset packages one official XLSX resource from Mauritania 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: The regional INFORM Sahel model
• Publisher: INFORM
• Resource: inform_risk_sahel_2021.xlsx
• Format: XLSX
• License: CC BY 4.0
• Packaging mode: tabular_resource

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
MRT	745	2021	2021	Mauritania

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.	ec460c6a-fe35-4164-9e1c-55d4a1cf509b:home:0
country_iso3	category	ISO3 country code.	MRT
country_name	category	Country name.	Mauritania
source_sheet	string	Workbook sheet name, when the source is a spreadsheet.	Home
year	Int64	Observation year.	2021
index_for_risk_management_inform_sahel	string	Source column.	(release: 15 Aout 2019 v 1.0.0)
source_period_start_year	Int64	First year inferred from source resource metadata.	2021
source_period_end_year	Int64	Last year inferred from source resource metadata.	2021
source_period_label	category	Human-readable period inferred from source resource metadata.	2021
source_provider	category	Publishing organization.	INFORM
source_dataset	category	Source package title.	The regional INFORM Sahel model
source_resource	category	Source resource title.	inform_risk_sahel_2021.xlsx
source_package_id	category	CKAN package UUID.	05823a5a-a1e2-4ea0-96ea-3cf439f4ad37
source_resource_id	category	CKAN resource UUID.	ec460c6a-fe35-4164-9e1c-55d4a1cf509b
source_url	category	Original source resource URL.	https://data.humdata.org/dataset/05823a5a-a1e2-4ea0-96ea-3cf439f4ad37/re
license_id	category	Source license identifier.	cc-by
retrieved_at	category	UTC retrieval timestamp.	2026-08-18T00:06:00Z
table_of_contents	string	Source column.	``
sheets	string	Source column.	``
country	string	Source column.	``
admin1	string	Source column.	``
iso3	string	Source column.	``
iso_admin1	string	Source column.	``
food_insecurity_probability	string	Source column.	``
physical_exposure_to_flood	float64	Source column.	``
land_degradation	float64	Source column.	``
droughts_probability_and_historical_impact	float64	Source column.	``
natural	float64	Source column.	``
political_violence	float64	Source column.	``
conflict_probability	float64	Source column.	``
human	float64	Source column.	``
hazard	float64	Source column.	``
development_deprivation	float64	Source column.	``
inequality	float64	Source column.	``
aid_dependency	float64	Source column.	``
socio_economic_vulnerability	float64	Source column.	``
uprooted_people	float64	Source column.	``
health_conditions	float64	Source column.	``
children_u5	float64	Source column.	``
malnutrition	float64	Source column.	``
recent_shocks	float64	Source column.	``
food_security	string	Source column.	``
other_vulnerable_groups	float64	Source column.	``
vulnerable_groups	float64	Source column.	``
vulnerability	float64	Source column.	``
drr	float64	Source column.	``
governance	float64	Source column.	``
institutional	float64	Source column.	``
communication	float64	Source column.	``
physical_infrastructure	float64	Source column.	``
access_to_health_care	float64	Source column.	``
infrastructure	float64	Source column.	``
lack_of_coping_capacity	float64	Source column.	``
risk	float64	Source column.	``
centre	string	Source column.	``
cmr	string	Source column.	``
cm_ce	string	Source column.	``
d_4_8	float64	Source column.	``
d_2_1	float64	Source column.	``
d_3_6	float64	Source column.	``
d_7_5	float64	Source column.	``
d_5_4	float64	Source column.	``
d_6_5	float64	Source column.	``
d_1481597218_0000002	float64	Source column.	``
d_55_812732936475534	float64	Source column.	``
d_1_1	float64	Source column.	``
d_2_3	float64	Source column.	``
d_12_795552632982673	float64	Source column.	``
d_1_3	float64	Source column.	``
d_1_6	float64	Source column.	``
d_3_8	float64	Source column.	``
d_67266	float64	Source column.	``
d_6_1	float64	Source column.	``
d_0_01234246514869068	float64	Source column.	``
d_5_9	float64	Source column.	``
d_6	float64	Source column.	``
d_6_6	float64	Source column.	``
d_3_3	float64	Source column.	``
d_7_6	float64	Source column.	``
d_1_1559707792458491	float64	Source column.	``
d_5_6	float64	Source column.	``
d_0_49541604824822105	string	Source column.	``
d_5_6_2	string	Source column.	``
d_5_7	float64	Source column.	``
d_5_8	float64	Source column.	``
x	float64	Source column.	``
d_5_8_2	float64	Source column.	``
x_2	float64	Source column.	``
d_0	float64	Source column.	``
d_0_2	float64	Source column.	``
d_417_8059642756025	float64	Source column.	``
d_7_666214065035422e_05	float64	Source column.	``
d_0_3	float64	Source column.	``
d_0_014171651291278278	string	Source column.	``
d_0_7	string	Source column.	``
d_0_7_2	string	Source column.	``
d_2_9	float64	Source column.	``
d_4_6	float64	Source column.	``
d_2_6	float64	Source column.	``
physical_exposure_to_flood_absolute	float64	Source column.	``
land_degradation_low_status_medium_to_storng_degradation	float64	Source column.	``
land_degradation_high_status_medium_to_storng_degradatio	float64	Source column.	``
land_degradation_score	float64	Source column.	``
people_affected_by_droughts_absolute	float64	Source column.	``
physical_exposure_to_flood_relative	float64	Source column.	``
people_affected_by_droughts_relative	float64	Source column.	``
physical_exposure_to_flood_relative_2	float64	Source column.	``
people_affected_by_droughts_relative_2	float64	Source column.	``
frequency_of_drought_events	float64	Source column.	``
people_affected_by_droughts	float64	Source column.	``
people_affected_by_droughts_and_frequency_of_events	float64	Source column.	``
agriculture_droughts_probability	string	Source column.	``
food_insecurity_probability_2	string	Source column.	``
land_degradation_2	float64	Source column.	``
inform_natural_hazard	float64	Source column.	``
gcri_violent_internal_conflict_probability	float64	Source column.	``
gcri_highly_violent_internal_conflict_probability	float64	Source column.	``
gcri_internal_conflict_score	float64	Source column.	``
conflict_intensity	float64	Source column.	``
acled	float64	Source column.	``
inform_human_hazard	float64	Source column.	``
hfa_scores	string	Source column.	``
total_investments_in_risk_reduction_per_capita_gha	float64	Source column.	``
international_investments_in_risk_reduction	float64	Source column.	``
corruption_perception_index	float64	Source column.	``
government_effectiveness	float64	Source column.	``
inform_institutional	float64	Source column.	``
adult_literacy_rate	float64	Source column.	``
access_to_electricity	float64	Source column.	``
internet_users	float64	Source column.	``
mobile_cellular_subscriptions	float64	Source column.	``
improved_sanitation_facilities	float64	Source column.	``
improved_water_source	float64	Source column.	``
physical_connectivity	float64	Source column.	``
phisycians_density	float64	Source column.	``
prevalence_of_dtp_dtc_vaccination	float64	Source column.	``
measles_immunization_coverage	float64	Source column.	``
per_capita_public_and_private_expenditure_on_health_care	float64	Source column.	``
access_to_health_care_index	float64	Source column.	``
inform_infrastructure	float64	Source column.	``
requirement	string	Source column.	``
cadre_harmonise	string	Source column.	``
agriculture_droughts	string	Source column.	``
total_affected_by_drought	float64	Source column.	``
conflict_barometer	float64	Source column.	``
violent_conflict_probability	float64	Source column.	``
highly_violent_conflict_probability	float64	Source column.	``
human_development_index	float64	Source column.	``
multidimensional_poverty_index	float64	Source column.	``
personal_remittances_received_current_us	float64	Source column.	``
humanitarian_aid_fts	float64	Source column.	``
development_aid_oda	float64	Source column.	``
development_aid_oda_2	float64	Source column.	``
net_oda_received_of_gni	float64	Source column.	``
mortality_rate_under_5	float64	Source column.	``
prevalence_of_underweight_in_children_0_59_months_of_age	float64	Source column.	``
phisicians_density	float64	Source column.	``
immunization_rate_or_1_year_olds_immunized_against_dtc	float64	Source column.	``
one_year_olds_fully_immunized_against_measles	float64	Source column.	``
tuberculosis_prevalence	float64	Source column.	``
estimated_number_of_people_living_with_hiv_adult_15_rate	float64	Source column.	``
cholera_reported_cases	float64	Source column.	``
clinically_confirmed_measles_case	string	Source column.	``
health_expenditure_per_capita	float64	Source column.	``
malaria_death_rate	float64	Source column.	``
gender_inequality_index	float64	Source column.	``
income_gini_coefficient	float64	Source column.	``
people_affected_by_natural_disasters	float64	Source column.	``
people_affected_by_natural_disasters_2	float64	Source column.	``
people_affected_by_natural_disasters_3	float64	Source column.	``
cadre_harmonise_2	string	Source column.	``
internally_displaced_persons_idps	float64	Source column.	``
refugees_by_country_of_asylum	float64	Source column.	``
returned_refugees	float64	Source column.	``
prevalence_of_gam_whz_in_children_6_59_months_of_age	float64	Source column.	``
prevalence_of_low_body_mass_index_bmi_in_women	float64	Source column.	``
hfa_scores_last_recent	string	Source column.	``
adult_liteacy_rate	float64	Source column.	``
improved_sanitation_facilities_of_population_with_access	float64	Source column.	``
improved_water_source_of_population_with_access	float64	Source column.	``
gdp_per_capita_ppp_int_usd	string	Source column.	``
population	float64	Source column.	``
population_population_density_ghsl_pop	float64	Source column.	``
population_national_projection	float64	Source column.	``
bcpr_drr_recovery_recips	float64	Source column.	``
gfdrr_recipients	float64	Source column.	``
disaster_prevention_and_preparedness	float64	Source column.	``
dimension	string	Source column.	``
category	string	Source column.	``
component	string	Source column.	``
sub_component	string	Source column.	``
inform_id	string	Source column.	``
indicator_name	string	Human-readable indicator name.	``
indicator_long_name	string	Source column.	``
resolution	string	Source column.	``
description	string	Source column.	``
relevance	string	Source column.	``
validity_limitation_of_indicator	string	Source column.	``
source	string	Source column.	``
url	string	Source column.	``
physical_exposure_to_earthquake_mmi_vi	float64	Source column.	``
physical_exposure_to_earthquake_mmi_viii	float64	Source column.	``
physical_exposure_to_tsunami	float64	Source column.	``
physical_exposure_to_cyclone_ss1	float64	Source column.	``
physical_exposure_to_cyclone_ss3	float64	Source column.	``
physical_exposure_to_cyclone_surge	float64	Source column.	``
intentional_homicide	string	Source column.	``
political_stability	float64	Source column.	``
u5_under_weight	float64	Source column.	``
average_dietary_energy_supply_adequacy	string	Source column.	``
prevalence_of_undernourishment	string	Source column.	``
domestic_food_price_level_index	string	Source column.	``
domestic_food_price_volatility_index	string	Source column.	``
road_density	string	Source column.	``

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritania-the-regional-inform-sahel-model-bf031eeb")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

sample_country = df[df["country_iso3"] == "MRT"]

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_mauritania_the_regional_inform_sahel_model_bf031eeb_2021,
  title        = {The regional INFORM Sahel model | Africa (Mauritania official open data)},
  author       = {INFORM},
  year         = {2021},
  url          = {https://data.humdata.org/dataset/the-regional-inform-sahel-model},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritania-the-regional-inform-sahel-model-bf031eeb}}
}

License

Released under CC BY 4.0.

Original data (c) INFORM. 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 2026-08-18 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/05823a5a-a1e2-4ea0-96ea-3cf439f4ad37/resource/ec460c6a-fe35-4164-9e1c-55d4a1cf509b/download/inform_risk_sahel_2021.xlsx