electricsheepafrica/africa-south-sudan-south-sudan-flow-monitoring-registry-january-august-2025-81f4036b

South Sudan Flow Monitoring Registry January August 2025 | Africa (International Organization for Migration (IOM))

83,403 rows - 1 Africa country/area - 2025 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 83,403 rows from International Organization for Migration (IOM), covering South Sudan Flow Monitoring Registry January August 2025. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Demographic datasets help analysts understand population structure, household conditions, migration, gender, age, and settlement patterns.

Source-provided context: Flow monitoring aims to derive quantitative estimates of the flow of individuals through specific locations (usually border points) and to collect information about the demographic information and reasons for migration of the people moving. This helps to quantify highly mobile populations by providing a picture of complex mobility dynamics. Flow monitoring data is collected on a monthly basis and this file covers the data collection from Jan to Aug 2025.

How To Read This Dataset

• One row means: one source record from the original tabular resource, with Electric Sheep Africa provenance columns added where available.
• Primary geography column: country_iso3.
• Best time column: year.
• Time coverage basis: year.
• Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

Dimension	Value
Rows	83,403
Countries/areas	1
First period	2025
Last period	2025
Indicators	0
Columns	68
Source format	XLSX

Geographic Coverage

Top areas shown below, sorted by row count when available:

Area	Rows	First year	Last year	Name
SSD	83,403	2025	2025	South Sudan

Indicators, Variables, Or Resource Contents

• This repo preserves one source tabular resource with its usable columns kept together.

Schema

Column	Type	Description	Example
source_record_id	string	Stable row identifier assigned during Electric Sheep Africa engineering.	bab6036f-3e98-4e12-b270-47427b1a9787:fmr-summary-jan-aug-2025-public:0
country_iso3	dictionary<values=string, indices=int8, ordered=0>	ISO3 country or area code.	SSD
country_name	dictionary<values=string, indices=int8, ordered=0>	Country or area name.	South Sudan
source_sheet	string	Source column from the original resource.	FMR_summary_Jan-Aug_2025_public
year	int64	Observation year.	2025
interview_month	string	Source column from the original resource.	2025-01-01 00:00:00
fmp_name	string	Source column from the original resource.	Abaya
fmp_latitude	double	Source column from the original resource.	3.403891
fmp_longitude	double	Source column from the original resource.	31.365706
direction	string	Source column from the original resource.	Outgoing
dep_country	string	Source column from the original resource.	SSD
dep_adm1	string	Source column from the original resource.	Central Equatoria
dep_adm1_pcode	string	Source column from the original resource.	SS01
dep_adm2	string	Source column from the original resource.	Kajo-keji
dep_adm2_pcode	string	Source column from the original resource.	SS0102
dep_iscamp	string	Source column from the original resource.	No
dep_camp	string	Source column from the original resource.	``
dest_country	string	Source column from the original resource.	UGA
dest_adm1	string	Source column from the original resource.	Moyo
dest_adm1_pcode	string	Source column from the original resource.	UG309
dest_adm2	string	Source column from the original resource.	Obongi
dest_adm2_pcode	string	Source column from the original resource.	UG3091
dest_iscamp	string	Source column from the original resource.	Yes
dest_camp	string	Source column from the original resource.	Chinyi
dest_habres	string	Source column from the original resource.	No
lmt_migration	string	Source column from the original resource.	No
time_atdep	string	Source column from the original resource.	<1 Day
time_atdest	string	Source column from the original resource.	2-7 Days
registered_refugees	string	Source column from the original resource.	Yes
return_relocation	string	Source column from the original resource.	No
forced_displacement	string	Source column from the original resource.	No
reason	string	Source column from the original resource.	Travel To Collect Aid
reason_subtype	string	Source column from the original resource.	``
transport	string	Source column from the original resource.	Motorbike
groups	double	Source column from the original resource.	1.0
total_ind	double	Source column from the original resource.	2.0
female_04	double	Source column from the original resource.	0.0
female_517	double	Source column from the original resource.	0.0
female_1859	double	Source column from the original resource.	0.0
female_60	double	Source column from the original resource.	0.0
male_04	double	Source column from the original resource.	0.0
male_517	double	Source column from the original resource.	0.0
male_1859	double	Source column from the original resource.	2.0
male_60	double	Source column from the original resource.	0.0
nationality_first	string	Source column from the original resource.	SSD
nationality_second	string	Source column from the original resource.	``
nationality_third	string	Source column from the original resource.	``
nationality_first_ind	double	Source column from the original resource.	2.0
nationality_second_ind	double	Source column from the original resource.	0.0
nationality_third_ind	double	Source column from the original resource.	0.0
uuid	string	Source column from the original resource.	003f0142-2c7c-4c2d-a267-406bd4428050
nationality_ssd_ind	double	Source column from the original resource.	2.0
source_period_start_year	int64	Start year inferred from source metadata.	2025
source_period_end_year	int64	End year inferred from source metadata.	2025
source_period_label	dictionary<values=string, indices=int8, ordered=0>	Source column from the original resource.	2025
source_provider	dictionary<values=string, indices=int8, ordered=0>	Publishing organization.	International Organization for Migration (IOM)
source_dataset	dictionary<values=string, indices=int8, ordered=0>	Source dataset or package title.	South Sudan - Flow Monitoring Registry - January - August 2025
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	DTM_SSD_FMR_summary_Jan-Aug_2025_public.xlsx
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	db03cda7-cd1f-4379-b8d7-74f906aebc9c
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	bab6036f-3e98-4e12-b270-47427b1a9787
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.humdata.org/dataset/db03cda7-cd1f-4379-b8d7-74f906aebc9c...
license_id	dictionary<values=string, indices=int8, ordered=0>	Source license identifier.	cc-by
retrieved_at	dictionary<values=string, indices=int8, ordered=0>	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-08-10T18:18:23Z
index	double	Source column from the original resource.	``
variable_name	string	Source column from the original resource.	``
description	string	Source column from the original resource.	``
subject	string	Source column from the original resource.	``
note	string	Source column from the original resource.	``

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-south-sudan-south-sudan-flow-monitoring-registry-january-august-2025-81f4036b")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns

print(df.info())
print(df.head())

Filter By Geography

if "country_iso3" in df.columns:
    sample = df[df["country_iso3"] == "SSD"]

Time-Series Pattern

if "value" in df.columns and "year" in df.columns:
    trend = df.sort_values("year")

Pivot For Analysis

if {"indicator_id", "year", "value"}.issubset(df.columns):
    matrix = df.pivot_table(index="year", columns="indicator_id", values="value")
    print(matrix.tail())

Data Quality Notes

• Canonical time field: year.
• Missing values are preserved rather than silently imputed.
• Column names are standardized for machine use; source meanings are preserved where known.
• Always confirm source methodology, units, and collection definitions before policy, production, or redistribution-sensitive use.

Source And Provenance

• Source: International Organization for Migration (IOM)
• Publisher: International Organization for Migration (IOM)
• Portal: https://data.humdata.org
• Resource: DTM_SSD_FMR_summary_Jan-Aug_2025_public.xlsx
• License: CC BY 4.0
• Retrieved/generated: 2026-08-10T19:35:14Z
• Hugging Face repo: electricsheepafrica/africa-south-sudan-south-sudan-flow-monitoring-registry-january-august-2025-81f4036b

Transformations Applied

• Converted the source table to Parquet for efficient analytics and ML workflows.
• Added or preserved source provenance columns where available.
• Standardized README metadata, dataset loading configuration, schema documentation, and citation format.
• Preserved source-reported values without analytical imputation.

Suggested Analyses

• Build demographic profiles
• Normalize indicators per capita
• Join with service-delivery datasets
• Build time-series views and period-over-period comparisons
• Check missingness before modeling
• Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_south_sudan_south_sudan_flow_monitoring_registry_january_august_2025_81f4_2025,
  title        = {South Sudan Flow Monitoring Registry January August 2025 | Africa (International Organization for Migration (IOM))},
  author       = {International Organization for Migration (IOM)},
  year         = {2025},
  url          = {https://data.humdata.org/dataset/south-sudan-flow-monitoring-registry-jan-aug-2025-iom-dtm},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-south-sudan-south-sudan-flow-monitoring-registry-january-august-2025-81f4036b}}
}

License

Released under CC BY 4.0.

Original data is published by International Organization for Migration (IOM). Electric Sheep Africa engineering standardizes the data for discovery, loading, and analysis on Hugging Face. Cite both the original source and this ML-ready dataset when used.

About Electric Sheep Africa

Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.

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Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://data.humdata.org/dataset/south-sudan-flow-monitoring-registry-jan-aug-2025-iom-dtm