Add README.md

README.md

@@ -1,56 +1,157 @@
 ---
+annotations_creators:
+- no-annotation
+language_creators:
+- found
+language:
+- en
+license: other
+multilinguality:
+- monolingual
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+task_categories:
+- tabular-classification
+- tabular-regression
+task_ids: []
+tags:
+- africa
+- humanitarian
+- hdx
+- electric-sheep-africa
+- hxl
+- operational-presence
+- who-is-doing-what-and-where-3w-4w-5w
+- nga
+pretty_name: "Nigeria: Northeast Nigeria 3Ws (April-June 2022)"
 dataset_info:
-  features:
-  - name: organization
-    dtype: string
-  - name: org_acronym
-    dtype: string
-  - name: type_of_organization
-    dtype: string
-  - name: operation_type
-    dtype: string
-  - name: project_sector
-    dtype: string
-  - name: activities
-    dtype: string
-  - name: status
-    dtype: string
-  - name: states
-    dtype: string
-  - name: state_pcode
-    dtype: string
-  - name: lga
-    dtype: string
-  - name: lga_pcode
-    dtype: string
-  - name: ishrp
-    dtype: string
-  - name: response_type
-    dtype: string
-  - name: isrp
-    dtype: string
-  - name: month
-    dtype: string
-  - name: year
-    dtype: float64
-  - name: esa_source
-    dtype: string
-  - name: esa_processed
-    dtype: string
   splits:
-  - name: train
-    num_bytes: 1732272
-    num_examples: 7124
-  - name: test
-    num_bytes: 433612
-    num_examples: 1781
-  download_size: 176075
-  dataset_size: 2165884
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
+    - name: train
+      num_examples: 7124
+    - name: test
+      num_examples: 1781
 ---
+
+# Nigeria: Northeast Nigeria 3Ws (April-June 2022)
+
+**Publisher:** OCHA Nigeria · **Source:** [HDX](https://data.humdata.org/dataset/nigeria-northeast-nigeria-3ws-april-june-2022) · **License:** `other-pd-nr` · **Updated:** 2025-04-15
+
+---
+
+## Abstract
+
+Nigeria: Northeast Nigeria 3Ws (April-June 2022)
+
+Each row in this dataset represents subnational administrative unit observations. Data was last updated on HDX on 2025-04-15. Geographic scope: **NGA**.
+
+*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*
+
+---
+
+## Dataset Characteristics
+
+| | |
+|---|---|
+| **Domain** | Humanitarian and development data |
+| **Unit of observation** | Subnational administrative unit observations |
+| **Rows (total)** | 8,905 |
+| **Columns** | 18 (1 numeric, 17 categorical, 0 datetime) |
+| **Train split** | 7,124 rows |
+| **Test split** | 1,781 rows |
+| **Geographic scope** | NGA |
+| **Publisher** | OCHA Nigeria |
+| **HDX last updated** | 2025-04-15 |
+
+---
+
+## Variables
+
+**Geographic** — `org_acronym` (International Organization For Migration, United Nations High Commissioner For Refugees, United Nations Children'S Emergency Fund), `type_of_organization` (INGO, UN Agency, NNGO), `operation_type` (Reporting, Implementing, #operation+type), `states` (Borno, Adamawa, Yobe), `state_pcode` (NGA008, NGA002, NGA036) and 4 others.
+
+**Temporal** — `month`.
+
+**Identifier / Metadata** — `esa_source`, `esa_processed`.
+
+**Other** — `organization` (IOM, UNHCR, UNICEF), `project_sector` (Protection, Nutrition, Water, Sanitation & Hygiene), `activities` (Nutrition, Health, Other (specify in remarks column)), `status` (Ongoing, Completed, completed), `ishrp` and 1 others.
+
+---
+
+## Quick Start
+
+```python
+from datasets import load_dataset
+
+ds    = load_dataset("electricsheepafrica/africa-nigeria-northeast-nigeria-3ws-april-june-2022")
+train = ds["train"].to_pandas()
+test  = ds["test"].to_pandas()
+
+print(train.shape)
+train.head()
+```
+
+---
+
+## Schema
+
+| Column | Type | Null % | Range / Sample Values |
+|---|---|---|---|
+| `organization` | object | 0.0% | IOM, UNHCR, UNICEF |
+| `org_acronym` | object | 0.0% | International Organization For Migration, United Nations High Commissioner For Refugees, United Nations Children'S Emergency Fund |
+| `type_of_organization` | object | 0.0% | INGO, UN Agency, NNGO |
+| `operation_type` | object | 0.0% | Reporting, Implementing, #operation+type |
+| `project_sector` | object | 0.0% | Protection, Nutrition, Water, Sanitation & Hygiene |
+| `activities` | object | 0.0% | Nutrition, Health, Other (specify in remarks column) |
+| `status` | object | 0.0% | Ongoing, Completed, completed |
+| `states` | object | 0.0% | Borno, Adamawa, Yobe |
+| `state_pcode` | object | 0.0% | NGA008, NGA002, NGA036 |
+| `lga` | object | 0.0% | Jere, Maiduguri, Bama |
+| `lga_pcode` | object | 0.0% |  |
+| `ishrp` | object | 0.0% |  |
+| `response_type` | object | 0.0% |  |
+| `isrp` | object | 0.0% |  |
+| `month` | object | 0.0% |  |
+| `year` | float64 | 0.0% | 2022.0 – 2022.0 (mean 2022.0) |
+| `esa_source` | object | 0.0% |  |
+| `esa_processed` | object | 0.0% |  |
+
+---
+
+## Numeric Summary
+
+| Column | Min | Max | Mean | Median |
+|---|---|---|---|---|
+| `year` | 2022.0 | 2022.0 | 2022.0 | 2022.0 |
+
+---
+
+## 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`. 1 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). 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 OCHA Nigeria and has not been independently validated by ESA.
+- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
+- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/nigeria-northeast-nigeria-3ws-april-june-2022) for the publisher's own methodology notes and caveats.
+
+---
+
+## Citation
+
+```bibtex
+@dataset{hdx_africa_nigeria_northeast_nigeria_3ws_april_june_2022,
+  title     = {Nigeria: Northeast Nigeria 3Ws (April-June 2022)},
+  author    = {OCHA Nigeria},
+  year      = {2025},
+  url       = {https://data.humdata.org/dataset/nigeria-northeast-nigeria-3ws-april-june-2022},
+  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
+}
+```
+
+---
+
+*[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*