Upload dataset folder

README.md

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+---
+license: cc-by-4.0
+language:
+- en
+task_categories:
+- tabular-classification
+- tabular-regression
+multilinguality: monolingual
+size_categories:
+- 1K<n<10K
+tags:
+- tabular
+- xlsx
+- africa
+- libya
+- official-statistics
+- open-data
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-00000-of-00001.parquet
+pretty_name: "Libya Migration Data - [Migrants] - Baseline Assessment [IOM DTM] | Africa (Libya official open data)"
+---
+
+# Libya Migration Data - [Migrants] - Baseline Assessment [IOM DTM] | Africa (Libya official open data)
+
+4,610 rows - 1 Africa country - 2022-2023 - Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)
+
+![rows](https://img.shields.io/badge/rows-4610-blue)
+![countries](https://img.shields.io/badge/countries-1-green)
+![years](https://img.shields.io/badge/years-2022-2023-orange)
+![indicators](https://img.shields.io/badge/indicators-0-purple)
+![license](https://img.shields.io/badge/license-cc-by-4.0-lightgrey)
+
+## 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 46](https://data.humdata.org/dataset/cacf12d4-22b1-438f-bcb4-78aa9078ab94/resource/290a8091-b017-4637-9209-70c2a80402ec/download/dtm-libya-r46-public-migrants-dataset.xlsx)
+- **Format:** `XLSX`
+- **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
+- **Packaging mode:** `tabular_resource`
+
+## Geographic coverage
+
+1 Africa country:
+
+| Country | Rows | First year | Last year | Name |
+|---------|-----:|-----------:|----------:|------|
+| `LBY` | 4,610 | 2022 | 2023 | `Libya` |
+
+## 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. | `290a8091-b017-4637-9209-70c2a80402ec:summary:0` |
+| `country_iso3` | `category` | ISO3 country code. | `LBY` |
+| `country_name` | `category` | Country name. | `Libya` |
+| `source_sheet` | `string` | Workbook sheet name, when the source is a spreadsheet. | `Summary` |
+| `east` | `string` | Source column. | `West` |
+| `al_jabal_al_akhdar` | `string` | Source column. | `Al Jabal Al Gharbi` |
+| `d_17850` | `float64` | Source column. | `25430.0` |
+| `d_0_025281065968710964` | `float64` | Source column. | `0.0360166670915585` |
+| `column_5` | `float64` | Source column. | `` |
+| `column_6` | `float64` | Source column. | `` |
+| `niger` | `string` | Source column. | `Egypt` |
+| `d_171614` | `float64` | Source column. | `160699.0` |
+| `d_0_2430579750786758` | `float64` | Source column. | `0.2275989927230186` |
+| `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. | `2023` |
+| `source_period_label` | `category` | Human-readable period inferred from source resource metadata. | `2022-2023` |
+| `source_provider` | `category` | Publishing organization. | `International Organization for Migration (IOM)` |
+| `source_dataset` | `category` | Source package title. | `Libya Migration Data - [Migrants] - Baseline Assessment [IOM DTM]` |
+| `source_resource` | `category` | Source resource title. | `DTM Libya Migrants Baseline Assessment Round 46` |
+| `source_package_id` | `category` | CKAN package UUID. | `cacf12d4-22b1-438f-bcb4-78aa9078ab94` |
+| `source_resource_id` | `category` | CKAN resource UUID. | `290a8091-b017-4637-9209-70c2a80402ec` |
+| `source_url` | `category` | Original source resource URL. | `https://data.humdata.org/dataset/cacf12d4-22b1-438f-bcb4-78aa9078ab94/re` |
+| `license_id` | `category` | Source license identifier. | `cc-by` |
+| `retrieved_at` | `category` | UTC retrieval timestamp. | `2026-08-17T13:13:43Z` |
+| `adm_1_geodivision_en` | `string` | Source column. | `` |
+| `adm_1_geodivision_ar` | `string` | Source column. | `` |
+| `adm_2_mantika_region_en` | `string` | Source column. | `` |
+| `adm_2_mantika_region_ar` | `string` | Source column. | `` |
+| `adm_3_baladiya_area_en` | `string` | Source column. | `` |
+| `adm_3_baladiya_area_ar` | `string` | Source column. | `` |
+| `baladiya_pcode` | `string` | Source column. | `` |
+| `lat` | `float64` | Source column. | `` |
+| `long` | `float64` | Source column. | `` |
+| `assessmentround` | `float64` | Source column. | `` |
+| `migrants_ind` | `float64` | Source column. | `` |
+| `adm1_region_en` | `string` | Source column. | `` |
+| `adm2_mantika_en` | `string` | Source column. | `` |
+| `adm3_baladiya_en` | `string` | Source column. | `` |
+| `adm4_muhalla_en` | `string` | Source column. | `` |
+| `adm4_muhalla_ar` | `string` | Source column. | `` |
+| `muhalla_pcode` | `string` | Source column. | `` |
+| `muhalla_type` | `string` | Source column. | `` |
+| `migrants_in_muhalla` | `string` | Source column. | `` |
+| `migrant_ind` | `float64` | Source column. | `` |
+| `rented_accomodation_self_paid_ind` | `float64` | Source column. | `` |
+| `rented_accomodation_paind_by_others_ind` | `float64` | Source column. | `` |
+| `rented_accomodation_paind_by_employer_ind` | `float64` | Source column. | `` |
+| `squatting_on_other_people_s_properties_ind` | `float64` | Source column. | `` |
+| `abondoned_buildings_ind` | `float64` | Source column. | `` |
+| `sheltered_in_their_workplace_ind` | `float64` | Source column. | `` |
+| `schools_or_other_public_buildings_ind` | `float64` | Source column. | `` |
+| `in_informal_camp_setting_ind` | `float64` | Source column. | `` |
+| `no_accomodation_ind` | `float64` | Source column. | `` |
+| `other_shelter` | `float64` | Source column. | `` |
+| `migrants_arrived_last_month` | `float64` | Source column. | `` |
+| `migrants_arrived_between_1_to_6_months_ago` | `float64` | Source column. | `` |
+| `migrants_arrived_between_6_to_12_months_ago` | `float64` | Source column. | `` |
+| `migrants_arrived_over_12_months_ago` | `float64` | Source column. | `` |
+| `migrants_arrival_time_unknown` | `float64` | Source column. | `` |
+| `migrants_with_residency_permit` | `float64` | Source column. | `` |
+| `migrants_with_work_permit` | `float64` | Source column. | `` |
+| `migrants_with_no_permit` | `float64` | Source column. | `` |
+| `migrants_permit_status_unknown` | `float64` | Source column. | `` |
+| `migrants_adult_men` | `float64` | Source column. | `` |
+| `migrants_adult_women` | `float64` | Source column. | `` |
+| `migrants_children` | `float64` | Source column. | `` |
+| `priority_need_1` | `string` | Source column. | `` |
+| `priority_need_1_problem` | `string` | Source column. | `` |
+| `priority_need_2` | `string` | Source column. | `` |
+| `priority_need_2_problem` | `string` | Source column. | `` |
+| `priority_need_3` | `string` | Source column. | `` |
+| `priority_need_3_problem` | `string` | Source column. | `` |
+| `adm_4_muhalla_en` | `string` | Source column. | `` |
+| `adm_4_muhalla_ar` | `string` | Source column. | `` |
+| `muhalla_p_code` | `string` | Source column. | `` |
+| `region1` | `string` | Source column. | `` |
+| `region_2` | `string` | Source column. | `` |
+| `migrant_nationality` | `string` | Source column. | `` |
+| `migrant_individuals` | `float64` | Source column. | `` |
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("electricsheepafrica/africa-libya-libya-migration-data-migrants-baseline-assessment-iom-dtm-adb1f6ca")
+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_adb1f6ca_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-adb1f6ca}}
+}
+```
+
+## License
+
+Released under [CC BY 4.0](https://creativecommons.org/licenses/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](https://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/290a8091-b017-4637-9209-70c2a80402ec/download/dtm-libya-r46-public-migrants-dataset.xlsx

data/train-00000-of-00001.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f3a73b6c855782a546fe107065f0553c645c0c226f0ef7500bb73999ae2c0877
+size 140992

metadata/source_snapshot.json

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+{
+  "columns": [
+    "source_record_id",
+    "country_iso3",
+    "country_name",
+    "source_sheet",
+    "east",
+    "al_jabal_al_akhdar",
+    "d_17850",
+    "d_0_025281065968710964",
+    "column_5",
+    "column_6",
+    "niger",
+    "d_171614",
+    "d_0_2430579750786758",
+    "source_period_start_year",
+    "source_period_end_year",
+    "source_period_label",
+    "source_provider",
+    "source_dataset",
+    "source_resource",
+    "source_package_id",
+    "source_resource_id",
+    "source_url",
+    "license_id",
+    "retrieved_at",
+    "adm_1_geodivision_en",
+    "adm_1_geodivision_ar",
+    "adm_2_mantika_region_en",
+    "adm_2_mantika_region_ar",
+    "adm_3_baladiya_area_en",
+    "adm_3_baladiya_area_ar",
+    "baladiya_pcode",
+    "lat",
+    "long",
+    "assessmentround",
+    "migrants_ind",
+    "adm1_region_en",
+    "adm2_mantika_en",
+    "adm3_baladiya_en",
+    "adm4_muhalla_en",
+    "adm4_muhalla_ar",
+    "muhalla_pcode",
+    "muhalla_type",
+    "migrants_in_muhalla",
+    "migrant_ind",
+    "rented_accomodation_self_paid_ind",
+    "rented_accomodation_paind_by_others_ind",
+    "rented_accomodation_paind_by_employer_ind",
+    "squatting_on_other_people_s_properties_ind",
+    "abondoned_buildings_ind",
+    "sheltered_in_their_workplace_ind",
+    "schools_or_other_public_buildings_ind",
+    "in_informal_camp_setting_ind",
+    "no_accomodation_ind",
+    "other_shelter",
+    "migrants_arrived_last_month",
+    "migrants_arrived_between_1_to_6_months_ago",
+    "migrants_arrived_between_6_to_12_months_ago",
+    "migrants_arrived_over_12_months_ago",
+    "migrants_arrival_time_unknown",
+    "migrants_with_residency_permit",
+    "migrants_with_work_permit",
+    "migrants_with_no_permit",
+    "migrants_permit_status_unknown",
+    "migrants_adult_men",
+    "migrants_adult_women",
+    "migrants_children",
+    "priority_need_1",
+    "priority_need_1_problem",
+    "priority_need_2",
+    "priority_need_2_problem",
+    "priority_need_3",
+    "priority_need_3_problem",
+    "adm_4_muhalla_en",
+    "adm_4_muhalla_ar",
+    "muhalla_p_code",
+    "region1",
+    "region_2",
+    "migrant_nationality",
+    "migrant_individuals"
+  ],
+  "generated_at": "2026-08-17T13:33:35Z",
+  "indicator_count": 0,
+  "mode": "tabular_resource",
+  "repo_id": "electricsheepafrica/africa-libya-libya-migration-data-migrants-baseline-assessment-iom-dtm-adb1f6ca",
+  "rows": 4610,
+  "source": {
+    "api_base_url": "https://data.humdata.org/api/3/action",
+    "country_iso3": "LBY",
+    "country_name": "Libya",
+    "group_names": "lby",
+    "license_id": "cc-by",
+    "license_title": "Creative Commons Attribution International (CC BY)",
+    "license_url": "http://www.opendefinition.org/licenses/cc-by",
+    "organization_name": "international-organization-for-migration",
+    "organization_title": "International Organization for Migration (IOM)",
+    "package_id": "cacf12d4-22b1-438f-bcb4-78aa9078ab94",
+    "package_name": "libya-migration-data-migrants-baseline-assessment-iom-dtm",
+    "package_notes": "The dataset contains number of migrants in Libya at sub national level. The dataset also contains nationality of the migrants and their needs.",
+    "package_page_url": "https://data.humdata.org/dataset/libya-migration-data-migrants-baseline-assessment-iom-dtm",
+    "package_title": "Libya Migration Data - [Migrants] - Baseline Assessment [IOM DTM]",
+    "portal_url": "https://data.humdata.org",
+    "resource_description": "IOM Libya’s Displacement Tracking Matrix (DTM) programme identified a total of 706,062 migrants from over 44 nationalities in the 100 Libyan municipalities during round 46 of data collection (January - February 2023). The number of migrants in Libya has continued to increase slightly compared to the previous round of data collection (694,398 migrants, Round 45, November – December 2022).",
+    "resource_format": "XLSX",
+    "resource_id": "290a8091-b017-4637-9209-70c2a80402ec",
+    "resource_last_modified": "2023-05-25T11:28:52.370443",
+    "resource_name": "DTM Libya Migrants Baseline Assessment Round 46",
+    "resource_position": "14",
+    "resource_url": "https://data.humdata.org/dataset/cacf12d4-22b1-438f-bcb4-78aa9078ab94/resource/290a8091-b017-4637-9209-70c2a80402ec/download/dtm-libya-r46-public-migrants-dataset.xlsx",
+    "tag_names": "demographics,displacement,hxl,migration"
+  },
+  "year_max": 2023,
+  "year_min": 2022
+}