electricsheepasia/asia-migration-idps-informal-sites-profiling-and-moveme

Iraq - IDPs Informal sites profiling and movement intentions

Publisher: REACH Initiative · Source: HDX · License: cc-by · Updated: 2025-04-15

Abstract

REACH Initiative supports the humanitarian response in Iraq by conducting assessments of informal sites in Iraq, in partnership with the Camp Coordination and Camp Management (CCCM) cluster. The assessment aims to identify movement intentions and highlight the multi-sectoral needs of internally displaced persons (IDPs) residing in informal sites across Iraq. The results of this assessment aim to support evidence-based strategic orientation and inform humanitarian programming in Iraq.

Each row in this dataset represents tabular records. Data was last updated on HDX on 2025-04-15. Geographic scope: IRQ.

Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).

Dataset Characteristics

Variables

Geographic — reach_iraq_idp_informal_site_profiling_and_intentions_exercise_december_2021_february_2022_in_partnership_with_the_camp_coordination_and_camp_management_cluster_cccm (Items, Project Background, Primary data collection time period).

Identifier / Metadata — unnamed_1 (Description, REACH Initiative supports the humanitarian response in Iraq by conducting assessments of informal sites in Iraq, in partnership with the Camp Coordination and Camp Management (CCCM) cluster. The assessment aims to identify movement intentions and highlight the multi-sectoral needs of internally displaced persons (IDPs) residing in informal sites across Iraq. The results of this assessment aim to support evidence-based strategic orientation and inform humanitarian programming in Iraq., Household data collection took place between 05 December 2021 and 26 February 2022. In total, 2,327 households were assessed across 157 informal sites and 37 sub-districts in Iraq.), esa_source (HDX), esa_processed (2026-05-05).

Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/asia-migration-idps-informal-sites-profiling-and-moveme")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

Schema

Numeric Summary

No numeric columns.

Curation

Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snakecase. Common missing-value markers (`N/A`, `null`, `none`, `-`, `unknown`, `no data`, `#N/A`) were unified to `NaN`. 1 column(s) with >80% missing values were removed: `unnamed2`. 3 exact duplicate rows were removed. The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.

Limitations

• —Data originates from REACH Initiative and has not been independently validated by ESA.
• —Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
• —Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

Citation

@dataset{hdx_asia_migration_idps_informal_sites_profiling_and_moveme,
  title     = {Iraq - IDPs Informal sites profiling and movement intentions},
  author    = {REACH Initiative},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/idps-informal-sites-profiling-and-movement-intentions},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.