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africa-idmc-event-data-for-cod

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metadata 
annotations_creators:
  - no-annotation
language_creators:
  - found
language:
  - en
license: cc-by-4.0
multilinguality:
  - monolingual
size_categories:
  - n<1K
source_datasets:
  - original
task_categories:
  - tabular-classification
  - tabular-regression
  - other
task_ids: []
tags:
  - africa
  - humanitarian
  - hdx
  - electric-sheep-africa
  - conflict-violence
  - displacement
  - flooding
  - internally-displaced-persons-idp
  - natural-disasters
  - cod
pretty_name: >-
  Democratic Republic of the Congo - Internal Displacements Updates (IDU) (event
  data)
dataset_info:
  splits:
    - name: train
      num_examples: 86
    - name: test
      num_examples: 21

Democratic Republic of the Congo - Internal Displacements Updates (IDU) (event data)

Publisher: Internal Displacement Monitoring Centre (IDMC) · Source: HDX · License: cc-by-igo · Updated: 2026-04-15

Abstract

Conflict and disaster population movement (flows) data for Democratic Republic of the Congo.

The IDU (Internal Displacement Updates) dataset, provided by the Internal Displacement Monitoring Centre (IDMC), offers timely event data and provisional information on new internal displacements caused by conflicts and disasters. Representing the most recent available information over a 180-day time period, the IDU is updated daily and focuses on "flows" (new displacements).

Internally displaced persons (IDPs) are defined according to the 1998 Guiding Principles as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border. The IDMC's event data, sourced from the IDU, provides initial assessments of these internal displacements, reflecting continually updated provisional information from various sources.

While the IDU offers early insights, the more thoroughly validated and curated "stock" (Total number of people leaving on internal displacement) and "flow" (population movements) estimates are available in the annual Global Internal Displacement Database (GIDD). Both datasets are accessible via API, with specific guidance on data access, structure, and limitations, including important preprocessing considerations for the IDU to ensure accurate analysis and avoid double-counting. For further detailed information and complete API specifications, users are encouraged to consult the official documentation at https://www.internal-displacement.org/database/api-documentation/.

The IDMC's Event data, sourced from the Internal Displacement Updates (IDU), offers initial assessments of internal displacements reported within the last 180 days. This dataset provides provisional information that is continually updated on a daily basis, reflecting the availability of data on new displacements arising from conflicts and disasters. The finalized, carefully curated, and validated estimates are then made accessible through the Global Internal Displacement Database (GIDD). The IDU dataset comprises preliminary estimates aggregated from various publishers or sources.

Each row in this dataset represents discrete events or incidents. Temporal coverage is indicated by the displacement_date, displacement_start_date column(s). Geographic scope: COD.

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

Dataset Characteristics

Domain Conflict and security
Unit of observation Discrete events or incidents
Rows (total) 108
Columns 29 (6 numeric, 17 categorical, 5 datetime)
Train split 86 rows
Test split 21 rows
Geographic scope COD
Publisher Internal Displacement Monitoring Centre (IDMC)
HDX last updated 2026-04-15

Variables

Geographic — country (Dem. Rep. Congo), iso3 (COD), latitude (range -8.8535–2.3003), longitude (range 13.1435–30.9917), displacement_type (Conflict, Disaster) and 10 others.

Temporal — event_start_date, event_end_date.

Identifier / Metadata — id (range 208511.0–242792.0), centroid ([-5.9460209, 29.1967172], [-0.0623332, 28.7540799], [-1.1869031, 29.4461316]), event_id (range 29179.0–40747.0), event_name (Dem. Rep. Congo: Non-International armed conflict (NIAC) - South Kivu (M23) - 2025, Dem. Rep. Congo: Non-International armed conflict (NIAC) - North Kivu (M23) - 2025, Dem. Rep. Congo: Non-International armed conflict (NIAC) - North Kivu (ADF) - 2025), sources (OCHA - DRC, Office for the Coordination of Humanitarian Affairs (OCHA), IOM DTM - DRC) and 2 others.

Other — role (Recommended figure, Triangulation), qualifier (approximately, more than or equal to, total), figure (range 52.0–500000.0), created_at, description.

Quick Start 

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-idmc-event-data-for-cod")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

Schema

Column Type Null % Range / Sample Values
id int64 0.0% 208511.0 – 242792.0 (mean 228663.3981)
country object 0.0% Dem. Rep. Congo
iso3 object 0.0% COD
latitude float64 0.0% -8.8535 – 2.3003 (mean -2.2737)
longitude float64 0.0% 13.1435 – 30.9917 (mean 28.2997)
centroid object 0.0% [-5.9460209, 29.1967172], [-0.0623332, 28.7540799], [-1.1869031, 29.4461316]
role object 0.0% Recommended figure, Triangulation
displacement_type object 0.0% Conflict, Disaster
qualifier object 0.0% approximately, more than or equal to, total
figure int64 0.0% 52.0 – 500000.0 (mean 22702.0093)
displacement_date datetime64[ns] 0.0%
displacement_start_date datetime64[ns] 0.0%
displacement_end_date datetime64[ns] 0.0%
year int64 0.0% 2025.0 – 2026.0 (mean 2025.0463)
event_id int64 0.0% 29179.0 – 40747.0 (mean 33449.8981)
event_name object 0.0% Dem. Rep. Congo: Non-International armed conflict (NIAC) - South Kivu (M23) - 2025, Dem. Rep. Congo: Non-International armed conflict (NIAC) - North Kivu (M23) - 2025, Dem. Rep. Congo: Non-International armed conflict (NIAC) - North Kivu (ADF) - 2025
event_start_date datetime64[ns] 0.0%
event_end_date datetime64[ns] 0.0%
sources object 0.0% OCHA - DRC, Office for the Coordination of Humanitarian Affairs (OCHA), IOM DTM - DRC
locations_name object 0.0% Lubero, North Kivu, Democratic Republic of the Congo, Kalemie, Tanganyika, Democratic Republic of the Congo, Kalehe, South Kivu, Democratic Republic of the Congo
locations_coordinates object 0.0% -5.9460209, 29.1967172, -0.0623332, 28.7540799, -1.1869031, 29.4461316
locations_accuracy object 0.0%
locations_type object 0.0%
displacement_occurred object 4.6%
created_at datetime64[ns, UTC] 0.0%
description object 0.0%
combined_type object 0.0%
esa_source object 0.0%
esa_processed object 0.0%

Numeric Summary

Column Min Max Mean Median
id 208511.0 242792.0 228663.3981 235311.5
latitude -8.8535 2.3003 -2.2737 -2.0519
longitude 13.1435 30.9917 28.2997 28.7699
figure 52.0 500000.0 22702.0093 8092.0
year 2025.0 2026.0 2025.0463 2025.0
event_id 29179.0 40747.0 33449.8981 30538.0

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) with >80% missing values were removed: event_codes, event_code_types, category, subcategory, type, subtype.... 6 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 Internal Displacement Monitoring Centre (IDMC) 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_africa_idmc_event_data_for_cod,
  title     = {Democratic Republic of the Congo - Internal Displacements Updates (IDU) (event data)},
  author    = {Internal Displacement Monitoring Centre (IDMC)},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/idmc-event-data-for-cod},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

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