README.md

---
license: cc-by-4.0
language:
- en
task_categories:
- tabular-regression
- time-series-forecasting
multilinguality: multilingual
size_categories:
- 1K<n<10K
tags:
- "tabular"
- "africa"
- "open-data"
- "official-statistics"
- "south-sudan"
- "international-organization-for-migration-iom"
- "education"
- "ssd"
- "education-facilities-schools"
- "facilities-infrastructure"
- "geodata"
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-00000-of-00001.parquet
pretty_name: "South Sudan Village Assessment Education Facilities Iom Dt | Africa (International Organization for Migration (IOM))"
---

# South Sudan Village Assessment Education Facilities Iom Dt | Africa (International Organization for Migration (IOM))

**5,772 rows** - **1 Africa country/area** - **2019-2020** - **12 indicators** - *Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*

![rows](https://img.shields.io/badge/rows-5772-blue)
![countries](https://img.shields.io/badge/countries-1-green)
![period](https://img.shields.io/badge/period-2019--2020-orange)
![indicators](https://img.shields.io/badge/indicators-12-purple)
![license](https://img.shields.io/badge/license-cc--by--4.0-lightgrey)

## TL;DR

This dataset contains **5,772 rows** from **International Organization for Migration (IOM)**, covering **South Sudan Village Assessment Education Facilities Iom Dt**. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

## What This Dataset Measures

Education datasets help analysts study access, participation, learning systems, infrastructure, and outcomes across places and periods.

Source-provided context: The dataset has education facilities' names, locations and the services available there, last reviewed in April 2023.

## How To Read This Dataset

- **One row means:** one indicator observation for one geography, time period, and optional source dimensions.
- **Primary geography column:** `country_iso3`.
- **Best time column:** `year`.
- **Time coverage basis:** year.
- **Recommended join keys:** `country_iso3`, `year`, `indicator_id`.

## Coverage

| Dimension | Value |
|---|---:|
| Rows | 5,772 |
| Countries/areas | 1 |
| First period | 2019 |
| Last period | 2020 |
| Indicators | 12 |
| Columns | 64 |
| Source format | XLSX |

## Geographic Coverage

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

| Area | Rows | First year | Last year | Name |
|------|-----:|-----------:|----------:|------|
| `SSD` | 5,772 | 2019 | 2020 | `South Sudan` |

## Indicators, Variables, Or Resource Contents

- `south-sudan-village-assessment-education-facilities-iom-dtm-boma-pcode-63c49521` - South Sudan - Village Assessment - Education Facilities - [IOM-DTM] - boma pcode(source_units_unspecified)
- `south-sudan-village-assessment-education-facilities-iom-dtm-latitude-ref-df76ccc4` - South Sudan - Village Assessment - Education Facilities - [IOM-DTM] - latitude ref(source_units_unspecified)
- `south-sudan-village-assessment-education-facilities-iom-dtm-longitude-re-53450eb4` - South Sudan - Village Assessment - Education Facilities - [IOM-DTM] - longitude ref(source_units_unspecified)
- `south-sudan-village-assessment-education-facilities-iom-dtm-d-9-male-ann-e775162f` - South Sudan - Village Assessment - Education Facilities - [IOM-DTM] - d 9 male annual student enrolment(source_units_unspecified)
- `south-sudan-village-assessment-education-facilities-iom-dtm-d-9-female-a-de921290` - South Sudan - Village Assessment - Education Facilities - [IOM-DTM] - d 9 female annual student enrolment(source_units_unspecified)
- `south-sudan-village-assessment-education-facilities-iom-dtm-s2-total-enr-aea14a9e` - South Sudan - Village Assessment - Education Facilities - [IOM-DTM] - s2 total enrollment(source_units_unspecified)
- `south-sudan-village-assessment-education-facilities-iom-dtm-d-9-male-ann-29a828a4` - South Sudan - Village Assessment - Education Facilities - [IOM-DTM] - d 9 male annual student dropouts(source_units_unspecified)
- `south-sudan-village-assessment-education-facilities-iom-dtm-d-9-female-a-dbfc679a` - South Sudan - Village Assessment - Education Facilities - [IOM-DTM] - d 9 female annual student dropouts(source_units_unspecified)
- `south-sudan-village-assessment-education-facilities-iom-dtm-s2-total-dro-5d81dec7` - South Sudan - Village Assessment - Education Facilities - [IOM-DTM] - s2 total dropouts(source_units_unspecified)
- `south-sudan-village-assessment-education-facilities-iom-dtm-d-9-male-ann-e5557ffc` - South Sudan - Village Assessment - Education Facilities - [IOM-DTM] - d 9 male annual number of teachers(source_units_unspecified)
- `south-sudan-village-assessment-education-facilities-iom-dtm-d-9-female-a-9033243b` - South Sudan - Village Assessment - Education Facilities - [IOM-DTM] - d 9 female annual number of teachers(source_units_unspecified)
- `south-sudan-village-assessment-education-facilities-iom-dtm-s2-total-tea-f88d71ee` - South Sudan - Village Assessment - Education Facilities - [IOM-DTM] - s2 total teachers(source_units_unspecified)

## Schema

| Column | Type | Description | Example |
|--------|------|-------------|---------|
| `indicator_id` | `string` | Stable source or Electric Sheep Africa indicator identifier. | `south-sudan-village-assessment-education-facilities-iom-dtm-boma-pcod...` |
| `indicator_name` | `string` | Human-readable indicator name. | `South Sudan - Village Assessment - Education Facilities - [IOM-DTM] -...` |
| `country_iso3` | `string` | ISO3 country or area code. | `SSD` |
| `source_sheet` | `string` | Source column from the original resource. | `SSudan_Village_EDU_Aug19_Mar20` |
| `country_name` | `string` | Country or area name. | `South Sudan` |
| `year` | `int64` | Observation year. | `2019` |
| `value` | `double` | Numeric observation value. | `103298.0` |
| `unit` | `string` | Measurement unit, when supplied by the source. | `source_units_unspecified` |
| `dimension_state` | `string` | Source dimension retained during long-form normalization. | `Western Bahr el Ghazal` |
| `dimension_state_pcode` | `string` | Source dimension retained during long-form normalization. | `SS09` |
| `dimension_county` | `string` | Source dimension retained during long-form normalization. | `Wau` |
| `dimension_county_pcode` | `string` | Source dimension retained during long-form normalization. | `SS0903` |
| `dimension_payam` | `string` | Source dimension retained during long-form normalization. | `Wau_South` |
| `dimension_payam_pcode` | `string` | Source dimension retained during long-form normalization. | `SS090307` |
| `dimension_boma` | `string` | Source dimension retained during long-form normalization. | `Jebel A` |
| `dimension_is_current_boma_name_the_same` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_if_different_specify_new_boma_name` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_village` | `string` | Source dimension retained during long-form normalization. | `Jebel A` |
| `dimension_village_name_other` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_1_type_of_education_facility` | `string` | Source dimension retained during long-form normalization. | `Primary` |
| `dimension_name_of_education_facility` | `string` | Source dimension retained during long-form normalization. | `Kiir foundation primary school` |
| `dimension_d_2_a_current_status_of_education_facility` | `string` | Source dimension retained during long-form normalization. | `Operational` |
| `dimension_d_2_b_if_non_operational_please_select_a_reaso` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_2_b_other_specify` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_2_c_since_when_has_the_school_been_non_opera` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_3_a_what_standard_of_primary_education_is_of` | `string` | Source dimension retained during long-form normalization. | `Standard 1-8` |
| `dimension_d_3_b_if_the_primary_school_does_not_cover_up` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_4_if_this_is_a_secondary_school_what_standar` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_5_what_is_the_main_language_used_to_teach_in` | `string` | Source dimension retained during long-form normalization. | `English` |
| `dimension_d_5_local_language` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_6_what_school_curriculum_does_this_school_te` | `string` | Source dimension retained during long-form normalization. | `New South Sudan Curriculum` |
| `dimension_d_6_if_other_school_curriculum_specify` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_7_is_the_school_able_to_accommodate_all_scho` | `string` | Source dimension retained during long-form normalization. | `Yes` |
| `dimension_d_8_are_there_children_from_other_bomas_attend` | `string` | Source dimension retained during long-form normalization. | `Yes` |
| `dimension_d_11_whats_is_the_main_reason_for_pupils_dropp` | `string` | Source dimension retained during long-form normalization. | `High school fees` |
| `dimension_d_11_specify_other_dropping_out_reason` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_12_a_are_there_disabled_children_enrolled_in` | `string` | Source dimension retained during long-form normalization. | `Yes` |
| `dimension_d_12_b_if_yes_what_are_the_disabilities_they_n` | `string` | Source dimension retained during long-form normalization. | `Physical disability` |
| `dimension_d_12_c_if_yes_does_the_school_make_efforts_to` | `string` | Source dimension retained during long-form normalization. | `No` |
| `dimension_d_13_does_the_school_have_an_appropiate_safe_a` | `string` | Source dimension retained during long-form normalization. | `No` |
| `dimension_d_14_describe_the_education_facility_structure` | `string` | Source dimension retained during long-form normalization. | `Semi-permanent building` |
| `dimension_d_15_a_number_of_class_rooms` | `string` | Source dimension retained during long-form normalization. | `Insufficient` |
| `dimension_d_15_b_school_furniture` | `string` | Source dimension retained during long-form normalization. | `Insufficient` |
| `dimension_d_15_c_school_latrines` | `string` | Source dimension retained during long-form normalization. | `Insufficient` |
| `dimension_d_15_d_drinking_water_for_the_school` | `string` | Source dimension retained during long-form normalization. | `Not present` |
| `dimension_d_15_e_non_drinking_water_for_hygiene` | `string` | Source dimension retained during long-form normalization. | `Not present` |
| `dimension_d_17_does_the_school_find_it_difficult_to_get` | `string` | Source dimension retained during long-form normalization. | `Yes` |
| `dimension_d_17_if_yes_what_usually_happens_to_the_respec` | `string` | Source dimension retained during long-form normalization. | `Suspended` |
| `dimension_d_17_specify_other_happening_to_students_when` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_18_who_is_the_main_supporter_of_the_school` | `string` | Source dimension retained during long-form normalization. | `Private sector` |
| `dimension_d_19_do_the_students_go_for_further_education` | `string` | Source dimension retained during long-form normalization. | `Yes` |
| `dimension_d_20_a_do_you_have_accelerated_learning_progra` | `string` | Source dimension retained during long-form normalization. | `No` |
| `dimension_d_20_b_if_yes_who_is_the_main_provider_of_supp` | `string` | Source dimension retained during long-form normalization. | `` |
| `source_period_start_year` | `int64` | Start year inferred from source metadata. | `2019` |
| `source_period_end_year` | `int64` | End year inferred from source metadata. | `2023` |
| `source_period_label` | `dictionary<values=string, indices=int8, ordered=0>` | Source column from the original resource. | `2019-2023` |
| `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 - Village Assessment - Education Facilities - [IOM-DTM]` |
| `source_resource` | `dictionary<values=string, indices=int8, ordered=0>` | Source resource title, table name, or file name. | `DTM South Sudan Village Assessment Education Facilities Aug19 to Mar20` |
| `source_package_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source package identifier. | `de0a7adc-5ef1-410a-a532-31b34ba45b07` |
| `source_resource_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source resource identifier. | `87719cd8-d8f7-4287-b634-4f767259f9b3` |
| `source_url` | `dictionary<values=string, indices=int8, ordered=0>` | Original source URL or download URL. | `https://data.humdata.org/dataset/de0a7adc-5ef1-410a-a532-31b34ba45b07...` |
| `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` |

## Usage

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-south-sudan-south-sudan-village-assessment-education-facilities-iom-dt-9857ee14")
df = ds["train"].to_pandas()
print(df.head())
```

### Inspect Columns

```python
print(df.info())
print(df.head())
```

### Filter By Geography

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

### Time-Series Pattern

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

### Pivot For Analysis

```python
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)](https://data.humdata.org/dataset/south-sudan-village-assessment-education-facilities-iom-dtm)
- **Publisher:** International Organization for Migration (IOM)
- **Portal:** [https://data.humdata.org](https://data.humdata.org)
- **Resource:** [DTM South Sudan Village Assessment Education Facilities Aug19 to Mar20](https://data.humdata.org/dataset/de0a7adc-5ef1-410a-a532-31b34ba45b07/resource/87719cd8-d8f7-4287-b634-4f767259f9b3/download/dtm-south-sudan-village-assessment-education-facilities-aug19-to-mar20.xlsx)
- **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
- **Retrieved/generated:** `2026-08-10T19:54:00Z`
- **Hugging Face repo:** [electricsheepafrica/africa-south-sudan-south-sudan-village-assessment-education-facilities-iom-dt-9857ee14](https://huggingface.co/datasets/electricsheepafrica/africa-south-sudan-south-sudan-village-assessment-education-facilities-iom-dt-9857ee14)

## 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

- Compare education indicators by geography
- Track participation or completion trends
- Join with population and poverty indicators
- Build time-series views and period-over-period comparisons
- Pivot to geography x period or indicator x period matrices
- Check missingness before modeling
- Use `country_iso3` as the safest geography join key when present

## Citation

```bibtex
@misc{electric_sheep_africa_africa_south_sudan_south_sudan_village_assessment_education_facilities_iom_dt_98_2020,
  title        = {South Sudan Village Assessment Education Facilities Iom Dt | Africa (International Organization for Migration (IOM))},
  author       = {International Organization for Migration (IOM)},
  year         = {2020},
  url          = {https://data.humdata.org/dataset/south-sudan-village-assessment-education-facilities-iom-dtm},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-south-sudan-south-sudan-village-assessment-education-facilities-iom-dt-9857ee14}}
}
```

## License

Released under [CC BY 4.0](https://creativecommons.org/licenses/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.

---

Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://data.humdata.org/dataset/south-sudan-village-assessment-education-facilities-iom-dtm