license: cc-by-4.0
language:
- en
task_categories:
- tabular-classification
- tabular-regression
multilinguality: monolingual
size_categories:
- n<1K
tags:
- tabular
- xlsx
- africa
- mali
- official-statistics
- open-data
- population
configs:
- config_name: default
data_files:
- split: train
path: data/train-00000-of-00001.parquet
pretty_name: >-
Mali Displacement - [IDPs, Returnees] - Baseline Assessment [IOM DTM] | Africa
(Mali official open data)
Mali Displacement - [IDPs, Returnees] - Baseline Assessment [IOM DTM] | Africa (Mali official open data)
98 rows - 1 Africa country - 2012-2021 - Repackaged by Electric Sheep Africa
TL;DR
This dataset packages one official XLSX resource from Mali 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: Mali Displacement - [IDPs, Returnees] - Baseline Assessment [IOM DTM]
- Publisher: International Organization for Migration (IOM)
- Resource: DTM Mali Baseline Assessment Round 73
- Format:
XLSX - License: CC BY 4.0
- Packaging mode:
tabular_resource
Geographic coverage
1 Africa country:
| Country | Rows | First year | Last year | Name |
|---|---|---|---|---|
MLI |
98 | 2012 | 2021 | Mali |
Indicators or Resource Contents
- This source file is packaged as a normalized tabular resource.
Schema
| Column | Type | Description | Example |
|---|---|---|---|
source_record_id |
string |
Stable row identifier for tabular resources. | ff07cfc3-95da-48bf-b77f-b80a14741b3b:baseline:0 |
country_iso3 |
category |
ISO3 country code. | MLI |
country_name |
category |
Country name. | Mali |
source_sheet |
string |
Workbook sheet name, when the source is a spreadsheet. | Baseline |
snapshot_date |
string |
Source column. | #date+reported |
admin_0 |
string |
Source column. | #country+name |
admin_0_pcode |
string |
Source column. | #country+code |
admin_1 |
string |
Source column. | #adm1+name |
admin_1_pcode |
string |
Source column. | #adm1+code |
admin_2 |
string |
Source column. | #adm2+name |
admin_2_pcode |
string |
Source column. | #adm2+code |
admin_3 |
string |
Source column. | #adm3+name |
admin_3_pcode |
string |
Source column. | #adm3+code |
lowest_admin_level |
string |
Source column. | `` |
total_no_of_idps_hh |
float64 |
Source column. | `` |
total_no_of_idps_ind |
float64 |
Source column. | `` |
num_ret_from_abroad_ind |
float64 |
Source column. | `` |
num_ret_from_abroad_hh |
float64 |
Source column. | `` |
num_ret_idp_hh |
float64 |
Source column. | `` |
num_ret_idp_ind |
float64 |
Source column. | `` |
total_no_of_returnees_hh |
float64 |
Source column. | `` |
total_no_of_returnees_ind |
float64 |
Source column. | `` |
country_of_origin_of_idp |
string |
Source column. | `` |
admin_0_origin_majority_ret_from_abroad |
string |
Source column. | `` |
admin_1_area_of_origin_of_idp |
string |
Source column. | `` |
confidentiality |
string |
Source column. | `` |
type_of_displacement |
string |
Source column. | `` |
conflict |
float64 |
Source column. | `` |
insecurity |
float64 |
Source column. | `` |
natural_disaster |
float64 |
Source column. | `` |
political_reasons |
float64 |
Source column. | `` |
economic_reasons |
float64 |
Source column. | `` |
main_displacement_start_date |
float64 |
Source column. | `` |
updateddate |
string |
Source column. | `` |
roundno |
float64 |
Source column. | `` |
returns |
float64 |
Source column. | `` |
migration_flows |
float64 |
Source column. | `` |
other_reason |
float64 |
Source column. | `` |
methodology |
string |
Source column. | `` |
admin_0_pcode_origin_majority_ret_from_abroad |
string |
Source column. | `` |
admin_1_pcode_origin_majority_present_idp |
string |
Source column. | `` |
source_period_start_year |
Int64 |
First year inferred from source resource metadata. | 2012 |
source_period_end_year |
Int64 |
Last year inferred from source resource metadata. | 2021 |
source_period_label |
category |
Human-readable period inferred from source resource metadata. | 2012-2021 |
source_provider |
category |
Publishing organization. | International Organization for Migration (IOM) |
source_dataset |
category |
Source package title. | Mali Displacement - [IDPs, Returnees] - Baseline Assessment [IOM DTM] |
source_resource |
category |
Source resource title. | DTM Mali Baseline Assessment Round 73 |
source_package_id |
category |
CKAN package UUID. | ea41f7c7-2ebe-456b-b5eb-e3e0ac8d708b |
source_resource_id |
category |
CKAN resource UUID. | ff07cfc3-95da-48bf-b77f-b80a14741b3b |
source_url |
category |
Original source resource URL. | https://data.humdata.org/dataset/ea41f7c7-2ebe-456b-b5eb-e3e0ac8d708b/re |
license_id |
category |
Source license identifier. | cc-by |
retrieved_at |
category |
UTC retrieval timestamp. | 2026-08-12T23:12:09Z |
column_name |
string |
Source column. | `` |
description |
string |
Source column. | `` |
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-mali-mali-displacement-idps-returnees-baseline-assessment-iom-d-f49d0bb1")
df = ds["train"].to_pandas()
print(df.head())
Filter to one country
sample_country = df[df["country_iso3"] == "MLI"]
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_mali_mali_displacement_idps_returnees_baseline_assessment_iom_d_f49d0bb1_2021,
title = {Mali Displacement - [IDPs, Returnees] - Baseline Assessment [IOM DTM] | Africa (Mali official open data)},
author = {International Organization for Migration (IOM)},
year = {2021},
url = {https://data.humdata.org/dataset/mali-baseline-assessment-data-iom-dtm},
publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mali-mali-displacement-idps-returnees-baseline-assessment-iom-d-f49d0bb1}}
}
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 2026-08-13 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/ea41f7c7-2ebe-456b-b5eb-e3e0ac8d708b/resource/ff07cfc3-95da-48bf-b77f-b80a14741b3b/download/hdx-dtm_dataset_mali_r73.xlsx