electricsheepasia/asia-displacement-syria-iom-dtm-from-api

Syrian Arab Republic IOM Displacement Tracking Matrix (DTM) from API

Publisher: International Organization for Migration (IOM) · Source: HDX · License: hdx-other · Updated: 2026-05-04

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Abstract

This dataset comes from the International Organization for Migration (IOM)'s displacement tracking matrix (DTM) publicly accessible API. This API allows the humanitarian community, academia, media, government, and non-governmental organizations to utilize the data collected by DTM. The DTM API only provides non-sensitive IDP figures, aggregated at the country, Admin 1 (states, provinces, or equivalent), and Admin 2 (smaller subnational administrative areas) levels. For more detailed information, please see the country-specific DTM datasets on HDX.

Each row in this dataset represents subnational administrative unit observations. Temporal coverage is indicated by the reportingdate column(s). Geographic scope: SYR.

Curated into ML-ready Parquet format by Electric Sheep Africa.

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Dataset Characteristics

Domain	Conflict and security
Unit of observation	Subnational administrative unit observations
Rows (total)	1,667
Columns	23 (8 numeric, 14 categorical, 1 datetime)
Train split	1,333 rows
Test split	333 rows
Geographic scope	SYR
Publisher	International Organization for Migration (IOM)
HDX last updated	2026-05-04

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Variables

Geographic — admin0name (Syrian Arab Republic), admin0pcode (SYR), admin1name (Rural Damascus, Aleppo, Tartous), admin1pcode (SY03, SY02, SY10), admin2name (Jablah, Damascus, Jebel Saman) and 7 others.

Temporal — reportingdate, monthreportingdate (range 2.0–12.0).

Demographic — numbermales (range 20.0–3414290.0), numberfemales (range 14.0–3261183.0).

Outcome / Measurement — roundnumber (range 1.0–14.0).

Identifier / Metadata — id (range 105.0–139125.0), numpresentidpind (range 4.0–6731534.0), esa_source, esa_processed.

Other — operation (Syrian Arab Republic Displacement, As-Sweida Conflict), operationstatus.

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/asia-displacement-syria-iom-dtm-from-api")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

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Schema

Column	Type	Null %	Range / Sample Values
id	float64	4.0%	105.0 – 139125.0 (mean 52869.37)
operation	object	0.0%	Syrian Arab Republic Displacement, As-Sweida Conflict
admin0name	object	0.0%	Syrian Arab Republic
admin0pcode	object	0.0%	SYR
admin1name	object	4.0%	Rural Damascus, Aleppo, Tartous
admin1pcode	object	4.0%	SY03, SY02, SY10
admin2name	object	28.8%	Jablah, Damascus, Jebel Saman
admin2pcode	object	28.8%	SY0602, SY0100, SY0200
adminlevel	int64	0.0%	0.0 – 2.0 (mean 1.6719)
numpresentidpind	int64	0.0%	4.0 – 6731534.0 (mean 115401.0864)
reportingdate	datetime64[ns]	0.0%
yearreportingdate	int64	0.0%	2025.0 – 2025.0 (mean 2025.0)
monthreportingdate	int64	0.0%	2.0 – 12.0 (mean 4.5945)
roundnumber	int64	0.0%	1.0 – 14.0 (mean 3.8752)
displacementreason	object	0.0%	Conflict, Other reason, Economic reasons
numbermales	float64	57.0%	20.0 – 3414290.0 (mean 103812.5816)
numberfemales	float64	57.0%	14.0 – 3261183.0 (mean 107059.205)
idporiginadmin1name	object	0.0%	Not available, Rural Damascus, Homs
idporiginadmin1pcode	object	0.0%	Not available, SY03, SY04
assessmenttype	object	0.0%
operationstatus	object	0.0%
esa_source	object	0.0%
esa_processed	object	0.0%

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Numeric Summary

Column	Min	Max	Mean	Median
id	105.0	139125.0	52869.37	45941.0
adminlevel	0.0	2.0	1.6719	2.0
numpresentidpind	4.0	6731534.0	115401.0864	5088.0
yearreportingdate	2025.0	2025.0	2025.0	2025.0
monthreportingdate	2.0	12.0	4.5945	2.0
roundnumber	1.0	14.0	3.8752	1.0
numbermales	20.0	3414290.0	103812.5816	11842.0
numberfemales	14.0	3261183.0	107059.205	12209.0

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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. 1 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.

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Limitations

• Data originates from International Organization for Migration (IOM) 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: admin2name, admin2pcode, numbermales, numberfemales.
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{hdx_asia_displacement_syria_iom_dtm_from_api,
  title     = {Syrian Arab Republic IOM Displacement Tracking Matrix (DTM) from API},
  author    = {International Organization for Migration (IOM)},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/syr-iom-dtm-from-api},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

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Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.