electricsheepafrica/africa-drc-drc-displacement-countrywide-monitoring-baseline-assessmen-71a37c11
DRC Displacement - Countrywide Monitoring - Baseline Assessment [IOM DTM] | Africa (DRC official open data) 543 rows - 1 Africa country - 2025 - Repackaged by Electric Sheep Africa TL;DR This dataset packages one official XLSX resource from DRC as ML-ready Parquet. The source file is the provenance boundary; all usable indicators or tabular columns from the resource stay together in this repo. About the source Source: DRC Displacement -… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-drc-drc-displacement-countrywide-monitoring-baseline-assessmen-71a37c11.
DRC Displacement - Countrywide Monitoring - Baseline Assessment [IOM DTM] | Africa (DRC official open data)
543 rows - 1 Africa country - 2025 - Repackaged by Electric Sheep Africa
TL;DR
This dataset packages one official XLSX resource from DRC as ML-ready Parquet. The source file is the provenance boundary; all usable indicators or tabular columns from the resource stay together in this repo.
About the source
- Source: [DRC Displacement - Countrywide Monitoring - Baseline Assessment [IOM DTM]](https://data.humdata.org/dataset/drc-displacement-countrywide-monitoring-baseline-assessment-iom-dtm)
- Publisher: International Organization for Migration (IOM)
- Resource: Baseline Assessment - Countrywide Displacement Overview 2025 - Round 3
- Format:
XLSX - License: CC BY 4.0
- Packaging mode:
tabular_resource
Geographic coverage
1 Africa country:
Indicators or Resource Contents
- This source file is packaged as a normalized tabular resource.
Schema
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-drc-drc-displacement-countrywide-monitoring-baseline-assessmen-71a37c11")
df = ds["train"].to_pandas()
print(df.head())Filter to one country
sample_country = df[df["country_iso3"] == "COD"]Work with indicators
if "indicator_id" in df.columns:
print(df["indicator_id"].value_counts().head())
sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])Citation
@misc{electric_sheep_africa_africa_drc_drc_displacement_countrywide_monitoring_baseline_assessmen_71a37c11_2025,
title = {DRC Displacement - Countrywide Monitoring - Baseline Assessment [IOM DTM] | Africa (DRC official open data)},
author = {International Organization for Migration (IOM)},
year = {2025},
url = {https://data.humdata.org/dataset/drc-displacement-countrywide-monitoring-baseline-assessment-iom-dtm},
publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-drc-drc-displacement-countrywide-monitoring-baseline-assessmen-71a37c11}}
}License
Released under CC BY 4.0.
Original data (c) International Organization for Migration (IOM). When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.
About Electric Sheep
Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa on Hugging Face. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use load_dataset() to start working in seconds.
Browse the full collection: huggingface.co/electricsheepafrica
Provenance: ingested 2026-08-20 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/e29a8f6f-94b5-4182-a028-f5b09c21668f/resource/904bd740-dd10-4a88-850e-d1f95b450257/download/drcnationaloverview2025finalv2hdx.xlsx
