Add README.md

README.md

@@ -1,44 +1,159 @@
 ---
+annotations_creators:
+- no-annotation
+language_creators:
+- found
+language:
+- en
+license: cc-by-sa-4.0
+multilinguality:
+- monolingual
+size_categories:
+- n<1K
+source_datasets:
+- original
+task_categories:
+- tabular-classification
+- tabular-regression
+task_ids: []
+tags:
+- africa
+- humanitarian
+- hdx
+- electric-sheep-africa
+- conflict-violence
+- fatalities
+- forecasting
+- hxl
+- eri
+pretty_name: "Eritrea - VIEWS conflict forecasts"
 dataset_info:
-  features:
-  - name: country_id
-    dtype: int64
-  - name: month_id
-    dtype: int64
-  - name: name
-    dtype: string
-  - name: gwcode
-    dtype: int64
-  - name: isoab
-    dtype: string
-  - name: year
-    dtype: int64
-  - name: month
-    dtype: int64
-  - name: main_mean_ln
-    dtype: float64
-  - name: main_mean
-    dtype: float64
-  - name: main_dich
-    dtype: float64
-  - name: esa_source
-    dtype: string
-  - name: esa_processed
-    dtype: string
   splits:
-  - name: train
-    num_bytes: 2884
-    num_examples: 28
-  - name: test
-    num_bytes: 824
-    num_examples: 8
-  download_size: 11143
-  dataset_size: 3708
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
+    - name: train
+      num_examples: 28
+    - name: test
+      num_examples: 7
 ---
+
+# Eritrea - VIEWS conflict forecasts
+
+**Publisher:** Violence & Impacts Early-Warning System · **Source:** [HDX](https://data.humdata.org/dataset/eri-views-conflict-forecasts) · **License:** `cc-by-sa` · **Updated:** 2026-04-01
+
+---
+
+## Abstract
+
+The Violence & Impacts Early-Warning System (VIEWS) is an award-winning conflict prediction system that generates monthly forecasts for violent conflicts across the world up to three years in advance. It is supported by the iterative research and development activities undertaken by the VIEWS consortium.
+
+Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-04-01. Geographic scope: **ERI**.
+
+*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*
+
+---
+
+## Dataset Characteristics
+
+| | |
+|---|---|
+| **Domain** | Conflict and security |
+| **Unit of observation** | Country-level aggregates |
+| **Rows (total)** | 36 |
+| **Columns** | 12 (8 numeric, 4 categorical, 0 datetime) |
+| **Train split** | 28 rows |
+| **Test split** | 7 rows |
+| **Geographic scope** | ERI |
+| **Publisher** | Violence & Impacts Early-Warning System |
+| **HDX last updated** | 2026-04-01 |
+
+---
+
+## Variables
+
+**Geographic** — `country_id` (range 56.0–56.0), `isoab` (ERI), `year` (range 2026.0–2029.0).
+
+**Temporal** — `month_id` (range 555.0–590.0), `month` (range 1.0–12.0).
+
+**Identifier / Metadata** — `name` (Eritrea), `gwcode` (range 531.0–531.0), `esa_source` (HDX), `esa_processed` (2026-04-06).
+
+**Other** — `main_mean_ln` (range 0.0266–0.1345), `main_mean` (range 0.027–0.1439), `main_dich` (range 0.0–0.0).
+
+---
+
+## Quick Start
+
+```python
+from datasets import load_dataset
+
+ds    = load_dataset("electricsheepafrica/africa-eri-views-conflict-forecasts")
+train = ds["train"].to_pandas()
+test  = ds["test"].to_pandas()
+
+print(train.shape)
+train.head()
+```
+
+---
+
+## Schema
+
+| Column | Type | Null % | Range / Sample Values |
+|---|---|---|---|
+| `country_id` | int64 | 0.0% | 56.0 – 56.0 (mean 56.0) |
+| `month_id` | int64 | 0.0% | 555.0 – 590.0 (mean 572.5) |
+| `name` | object | 0.0% | Eritrea |
+| `gwcode` | int64 | 0.0% | 531.0 – 531.0 (mean 531.0) |
+| `isoab` | object | 0.0% | ERI |
+| `year` | int64 | 0.0% | 2026.0 – 2029.0 (mean 2027.1667) |
+| `month` | int64 | 0.0% | 1.0 – 12.0 (mean 6.5) |
+| `main_mean_ln` | float64 | 0.0% | 0.0266 – 0.1345 (mean 0.0679) |
+| `main_mean` | float64 | 0.0% | 0.027 – 0.1439 (mean 0.0704) |
+| `main_dich` | float64 | 0.0% | 0.0 – 0.0 (mean 0.0) |
+| `esa_source` | object | 0.0% | HDX |
+| `esa_processed` | object | 0.0% | 2026-04-06 |
+
+---
+
+## Numeric Summary
+
+| Column | Min | Max | Mean | Median |
+|---|---|---|---|---|
+| `country_id` | 56.0 | 56.0 | 56.0 | 56.0 |
+| `month_id` | 555.0 | 590.0 | 572.5 | 572.5 |
+| `gwcode` | 531.0 | 531.0 | 531.0 | 531.0 |
+| `year` | 2026.0 | 2029.0 | 2027.1667 | 2027.0 |
+| `month` | 1.0 | 12.0 | 6.5 | 6.5 |
+| `main_mean_ln` | 0.0266 | 0.1345 | 0.0679 | 0.0633 |
+| `main_mean` | 0.027 | 0.1439 | 0.0704 | 0.0654 |
+| `main_dich` | 0.0 | 0.0 | 0.0 | 0.0 |
+
+---
+
+## 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`. 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 Violence & Impacts Early-Warning System 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/eri-views-conflict-forecasts) for the publisher's own methodology notes and caveats.
+
+---
+
+## Citation
+
+```bibtex
+@dataset{hdx_africa_eri_views_conflict_forecasts,
+  title     = {Eritrea - VIEWS conflict forecasts},
+  author    = {Violence & Impacts Early-Warning System},
+  year      = {2026},
+  url       = {https://data.humdata.org/dataset/eri-views-conflict-forecasts},
+  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.*