Datasets:
iso3 stringclasses 1
value | country_name stringclasses 1
value | year int64 2.02k 2.02k | new_displacement float64 182 1.67k ⌀ | new_displacement_rounded float64 180 1.7k ⌀ | total_displacement int64 0 1.98k | total_displacement_rounded float64 180 2k ⌀ | esa_source stringclasses 1
value | esa_processed stringdate 2026-04-05 00:00:00 2026-04-05 00:00:00 |
|---|---|---|---|---|---|---|---|---|
MDG | Madagascar | 2,018 | 1,668 | 1,700 | 1,982 | 2,000 | HDX | 2026-04-05 |
MDG | Madagascar | 2,019 | null | null | 0 | null | HDX | 2026-04-05 |
MDG | Madagascar | 2,020 | null | null | 0 | null | HDX | 2026-04-05 |
MDG | Madagascar | 2,021 | 1,295 | 1,300 | 1,295 | 1,300 | HDX | 2026-04-05 |
MDG | Madagascar | 2,022 | null | null | 0 | null | HDX | 2026-04-05 |
MDG | Madagascar | 2,023 | null | null | 0 | null | HDX | 2026-04-05 |
MDG | Madagascar | 2,024 | 182 | 180 | 182 | 180 | HDX | 2026-04-05 |
Madagascar - Internal Displacements (New Displacements) – IDPs
Publisher: Internal Displacement Monitoring Centre (IDMC) · Source: HDX · License: cc-by-igo · Updated: 2026-03-18
Abstract
The Global Internal Displacement Database (GIDD), maintained by the Internal Displacement Monitoring Centre (IDMC), provides comprehensive, validated annual estimates of internal displacement worldwide. It defines internally displaced persons (IDPs) in line with 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 GIDD tracks two primary metrics: "People Displaced" or population "Stock" figures, which represent the total number of people living in displacement at year-end, and "New Displacement," which counts new displacement incidents (population Flows) rather than individual people, accounting for potential multiple displacements by the same person. This dataset serves as a crucial resource for understanding long-term trends and validated displacement figures globally. 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/.
"Internally displaced persons - IDPs" refers to the number of people living in displacement as of the end of each year.
"Internal displacements (New Displacements)" refers to the number of new cases or incidents of displacement recorded, rather than the number of people displaced. This is done because people may have been displaced more than once.
Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-03-18. Geographic scope: MDG.
Curated into ML-ready Parquet format by Electric Sheep Africa.
Dataset Characteristics
| Domain | Conflict and security |
| Unit of observation | Country-level aggregates |
| Rows (total) | 7 |
| Columns | 9 (5 numeric, 4 categorical, 0 datetime) |
| Train split | 5 rows |
| Test split | 1 rows |
| Geographic scope | MDG |
| Publisher | Internal Displacement Monitoring Centre (IDMC) |
| HDX last updated | 2026-03-18 |
Variables
Geographic — iso3 (MDG), country_name (Madagascar), year (range 2018.0–2024.0), new_displacement (range 182.0–1668.0), new_displacement_rounded (range 180.0–1700.0) and 2 others.
Identifier / Metadata — esa_source (HDX), esa_processed (2026-04-05).
Quick Start
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-idmc-idp-data-mdg")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()
print(train.shape)
train.head()
Schema
| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
iso3 |
object | 0.0% | MDG |
country_name |
object | 0.0% | Madagascar |
year |
int64 | 0.0% | 2018.0 – 2024.0 (mean 2021.0) |
new_displacement |
float64 | 57.1% | 182.0 – 1668.0 (mean 1048.3333) |
new_displacement_rounded |
float64 | 57.1% | 180.0 – 1700.0 (mean 1060.0) |
total_displacement |
int64 | 0.0% | 0.0 – 1982.0 (mean 494.1429) |
total_displacement_rounded |
float64 | 57.1% | 180.0 – 2000.0 (mean 1160.0) |
esa_source |
object | 0.0% | HDX |
esa_processed |
object | 0.0% | 2026-04-05 |
Numeric Summary
| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
year |
2018.0 | 2024.0 | 2021.0 | 2021.0 |
new_displacement |
182.0 | 1668.0 | 1048.3333 | 1295.0 |
new_displacement_rounded |
180.0 | 1700.0 | 1060.0 | 1300.0 |
total_displacement |
0.0 | 1982.0 | 494.1429 | 0.0 |
total_displacement_rounded |
180.0 | 2000.0 | 1160.0 | 1300.0 |
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. 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.
- The following columns have >20% missing values and should be treated with caution in modelling:
new_displacement,new_displacement_rounded,total_displacement_rounded. - Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.
Citation
@dataset{hdx_africa_idmc_idp_data_mdg,
title = {Madagascar - Internal Displacements (New Displacements) – IDPs},
author = {Internal Displacement Monitoring Centre (IDMC)},
year = {2026},
url = {https://data.humdata.org/dataset/idmc-idp-data-mdg},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}
Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.
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