Add README.md

README.md

@@ -1,28 +1,145 @@
 ---
+annotations_creators:
+- no-annotation
+language_creators:
+- found
+language:
+- en
+license: cc-by-4.0
+multilinguality:
+- monolingual
+size_categories:
+- n<1K
+source_datasets:
+- original
+task_categories:
+- tabular-classification
+- other
+task_ids: []
+tags:
+- africa
+- humanitarian
+- hdx
+- electric-sheep-africa
+- affected-population
+- climate-weather
+- damage-assessment
+- flooding
+- hxl
+- migration
+- population
+- mli
+pretty_name: "Mali: Suivi des Inondations"
 dataset_info:
-  features:
-  - name: admin1_name
-    dtype: string
-  - name: personnes_affectées
-    dtype: float64
-  - name: esa_source
-    dtype: string
-  - name: esa_processed
-    dtype: string
   splits:
-  - name: train
-    num_bytes: 628
-    num_examples: 16
-  - name: test
-    num_bytes: 203
-    num_examples: 5
-  download_size: 4275
-  dataset_size: 831
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
+    - name: train
+      num_examples: 16
+    - name: test
+      num_examples: 4
 ---
+
+# Mali: Suivi des Inondations
+
+**Publisher:** OCHA Mali · **Source:** [HDX](https://data.humdata.org/dataset/mali-suivi-des-inondations) · **License:** `cc-by` · **Updated:** 2025-05-05
+
+---
+
+## Abstract
+
+Les données contiennent les impacts causés par les inondations et les fortes pluies au Mali.
+
+Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2025-05-05. Geographic scope: **MLI**.
+
+*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*
+
+---
+
+## Dataset Characteristics
+
+| | |
+|---|---|
+| **Domain** | Climate and environment |
+| **Unit of observation** | First-level administrative unit observations |
+| **Rows (total)** | 21 |
+| **Columns** | 4 (1 numeric, 3 categorical, 0 datetime) |
+| **Train split** | 16 rows |
+| **Test split** | 4 rows |
+| **Geographic scope** | MLI |
+| **Publisher** | OCHA Mali |
+| **HDX last updated** | 2025-05-05 |
+
+---
+
+## Variables
+
+**Geographic** — `admin1_name` (#adm1+name, Kayes, Nara).
+
+**Demographic** — `personnes_affectées` (range 717.0–84458.0).
+
+**Identifier / Metadata** — `esa_source` (HDX), `esa_processed` (2026-04-18).
+
+---
+
+## Quick Start
+
+```python
+from datasets import load_dataset
+
+ds    = load_dataset("electricsheepafrica/africa-mali-suivi-des-inondations")
+train = ds["train"].to_pandas()
+test  = ds["test"].to_pandas()
+
+print(train.shape)
+train.head()
+```
+
+---
+
+## Schema
+
+| Column | Type | Null % | Range / Sample Values |
+|---|---|---|---|
+| `admin1_name` | object | 0.0% | #adm1+name, Kayes, Nara |
+| `personnes_affectées` | float64 | 4.8% | 717.0 – 84458.0 (mean 18472.1) |
+| `esa_source` | object | 0.0% | HDX |
+| `esa_processed` | object | 0.0% | 2026-04-18 |
+
+---
+
+## Numeric Summary
+
+| Column | Min | Max | Mean | Median |
+|---|---|---|---|---|
+| `personnes_affectées` | 717.0 | 84458.0 | 18472.1 | 7373.5 |
+
+---
+
+## 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 Mali 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/mali-suivi-des-inondations) for the publisher's own methodology notes and caveats.
+
+---
+
+## Citation
+
+```bibtex
+@dataset{hdx_africa_mali_suivi_des_inondations,
+  title     = {Mali: Suivi des Inondations},
+  author    = {OCHA Mali},
+  year      = {2025},
+  url       = {https://data.humdata.org/dataset/mali-suivi-des-inondations},
+  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.*