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electricsheepafrica/africa-libya-libya-migration-data-migrants-baseline-assessment-iom-dtm-881c3afb

Libya Migration Data - [Migrants] - Baseline Assessment [IOM DTM] | Africa (Libya official open data) 4,726 rows - 1 Africa country - 2023 - Repackaged by Electric Sheep Africa TL;DR This dataset packages one official XLSX resource from Libya 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: Libya Migration Data -… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-libya-libya-migration-data-migrants-baseline-assessment-iom-dtm-881c3afb.

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Libya Migration Data - [Migrants] - Baseline Assessment [IOM DTM] | Africa (Libya official open data)

4,726 rows - 1 Africa country - 2023 - Repackaged by Electric Sheep Africa

rows countries years indicators license

TL;DR

This dataset packages one official XLSX resource from Libya 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: [Libya Migration Data - [Migrants] - Baseline Assessment [IOM DTM]](https://data.humdata.org/dataset/libya-migration-data-migrants-baseline-assessment-iom-dtm)
  • —Publisher: International Organization for Migration (IOM)
  • —Resource: DTM Libya Migrants Baseline Assessment Round 56
  • —Format: XLSX
  • —License: CC BY 4.0
  • —Packaging mode: tabular_resource

Geographic coverage

1 Africa country:

CountryRowsFirst yearLast yearName
LBY4,72620232023Libya

Indicators or Resource Contents

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

Schema

ColumnTypeDescriptionExample
source_record_idstringStable row identifier for tabular resources.a8a91e15-7570-44dc-bade-9604b3ad6eb2:summary:0
country_iso3categoryISO3 country code.LBY
country_namecategoryCountry name.Libya
source_sheetstringWorkbook sheet name, when the source is a spreadsheet.Summary
yearInt64Observation year.2023
weststringSource column.West
tripolistringSource column.Misrata
d_127301float64Source column.87274.0
d_0_14826509077525843float64Source column.0.101646393447969
column_5float64Source column.``
column_6float64Source column.``
sudanstringSource column.Niger
d_262036float64Source column.189546.0
d_0_30518842213639813stringSource column.0.22076067663323254
source_period_start_yearInt64First year inferred from source resource metadata.2023
source_period_end_yearInt64Last year inferred from source resource metadata.2023
source_period_labelcategoryHuman-readable period inferred from source resource metadata.2023
source_providercategoryPublishing organization.International Organization for Migration (IOM)
source_datasetcategorySource package title.Libya Migration Data - [Migrants] - Baseline Assessment [IOM DTM]
source_resourcecategorySource resource title.DTM Libya Migrants Baseline Assessment Round 56
source_package_idcategoryCKAN package UUID.cacf12d4-22b1-438f-bcb4-78aa9078ab94
source_resource_idcategoryCKAN resource UUID.a8a91e15-7570-44dc-bade-9604b3ad6eb2
source_urlcategoryOriginal source resource URL.https://data.humdata.org/dataset/cacf12d4-22b1-438f-bcb4-78aa9078ab94/re
license_idcategorySource license identifier.cc-by
retrieved_atcategoryUTC retrieval timestamp.2026-08-17T13:13:43Z
adm1_region_enstringSource column.``
adm2_mantika_enstringSource column.``
adm3_baladiya_enstringSource column.``
adm4_muhalla_enstringSource column.``
adm4_muhalla_arstringSource column.``
muhalla_pcodestringSource column.``
muhalla_typestringSource column.``
latitudefloat64Source column.``
longitudefloat64Source column.``
assessmentroundfloat64Source column.``
migrants_in_muhallastringSource column.``
migrant_indfloat64Source column.``
rented_accomodation_self_paid_indfloat64Source column.``
rented_accomodation_paind_by_others_indfloat64Source column.``
rented_accomodation_paind_by_employer_indfloat64Source column.``
squatting_on_other_people_s_properties_indfloat64Source column.``
abondoned_buildings_indfloat64Source column.``
sheltered_in_their_workplace_indfloat64Source column.``
schools_or_other_public_buildings_indfloat64Source column.``
in_informal_camp_setting_indfloat64Source column.``
no_accomodation_indfloat64Source column.``
other_shelterfloat64Source column.``
migrants_arrived_last_monthfloat64Source column.``
migrants_arrived_between_1_to_6_months_agofloat64Source column.``
migrants_arrived_between_6_to_12_months_agofloat64Source column.``
migrants_arrived_over_12_months_agofloat64Source column.``
migrants_arrival_time_unknownfloat64Source column.``
migrants_with_residency_permitfloat64Source column.``
migrants_with_work_permitfloat64Source column.``
migrants_with_no_permitfloat64Source column.``
migrants_permit_status_unknownfloat64Source column.``
migrants_adult_menfloat64Source column.``
migrants_adult_womenfloat64Source column.``
migrants_childrenfloat64Source column.``
priority_need_1stringSource column.``
priority_need_1_problemstringSource column.``
priority_need_2stringSource column.``
priority_need_2_problemstringSource column.``
priority_need_3stringSource column.``
priority_need_3_problemstringSource column.``
adm_1_geodivision_enstringSource column.``
adm_1_geodivision_arstringSource column.``
adm_2_mantika_region_enstringSource column.``
adm_2_mantika_region_arstringSource column.``
adm_3_baladiya_area_enstringSource column.``
adm_3_baladiya_area_arstringSource column.``
baladiya_pcodestringSource column.``
latfloat64Source column.``
longfloat64Source column.``
migrants_indfloat64Source column.``
adm_4_muhalla_enstringSource column.``
adm_4_muhalla_arstringSource column.``
muhalla_p_codestringSource column.``
region1stringSource column.``
region_2stringSource column.``
migrant_nationalitystringSource column.``
migrant_individualsfloat64Source column.``

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-libya-libya-migration-data-migrants-baseline-assessment-iom-dtm-881c3afb")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

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

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_libya_libya_migration_data_migrants_baseline_assessment_iom_dtm_881c3afb_2023,
  title        = {Libya Migration Data - [Migrants] - Baseline Assessment [IOM DTM] | Africa (Libya official open data)},
  author       = {International Organization for Migration (IOM)},
  year         = {2023},
  url          = {https://data.humdata.org/dataset/libya-migration-data-migrants-baseline-assessment-iom-dtm},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-libya-libya-migration-data-migrants-baseline-assessment-iom-dtm-881c3afb}}
}

License

Released under CC BY 4.0.

Original data (c) International Organization for Migration (IOM). 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/cacf12d4-22b1-438f-bcb4-78aa9078ab94/resource/a8a91e15-7570-44dc-bade-9604b3ad6eb2/download/dtmlibyar56migrantsdataset_public-hdx.xlsx