electricsheepasia/asia-displacement-iraq-affected-persons-locations-0-0-0-0

Iraq - Affected Persons Locations (DTM) 7 August 2014

Publisher: OCHA Iraq (inactive) · Source: HDX · License: hdx-other · Updated: 2023-05-02

Abstract

IOM IRAQ Displacement Tracking Matrix (DTM) 7 August 2014. Between January 2014 and 7 August, IOM has identified and confirmed the location of 1,056,900 IDP's displaced by conflict and insecurity across Iraq. IOM continues to monitor and track the situation in order to verify the numbers of the displaced population.

Each row in this dataset represents tabular records. Data was last updated on HDX on 2023-05-02. Geographic scope: IRQ.

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

Dataset Characteristics

Variables

Geographic — idps_summary (IDPs 2014, IDPs Post June 2014, IDPs Pre June 2014 (Mainly Anbar Crisis)).

Identifier / Metadata — unnamed_1 (range 187.0–176150.0), unnamed_2 (range 1122.0–1056900.0), unnamed_3 (range 22.0–1056900.0), unnamed_4 (range 157.0–94597.0), unnamed_5 (range 942.0–567582.0) and 6 others.

Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/asia-displacement-iraq-affected-persons-locations-0-0-0-0")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

Schema

Numeric Summary

Curation

Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (N/A, null, none, -, unknown, no data, #N/A) were unified to NaN. 9 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). 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 OCHA Iraq (inactive) and has not been independently validated by ESA.
• —Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
• —The following columns have >20% missing values and should be treated with caution in modelling: unnamed_4, unnamed_5, unnamed_6, unnamed_7, unnamed_8, unnamed_9.
• —Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

Citation

@dataset{hdx_asia_displacement_iraq_affected_persons_locations_0_0_0_0,
  title     = {Iraq - Affected Persons Locations (DTM)  7 August 2014},
  author    = {OCHA Iraq (inactive)},
  year      = {2023},
  url       = {https://data.humdata.org/dataset/iraq-affected-persons-locations-0-0-0-0},
  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.