Add README.md

README.md

@@ -1,64 +1,164 @@
 ---
+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
+- other
+task_ids: []
+tags:
+- africa
+- humanitarian
+- hdx
+- electric-sheep-africa
+- health
+- health-facilities
+- water-sanitation-and-hygiene-wash
+- gin
+pretty_name: "Guinea: Health Centers Data Base"
 dataset_info:
-  features:
-  - name: code_provisoire
-    dtype: string
-  - name: x
-    dtype: float64
-  - name: y
-    dtype: float64
-  - name: sourcecoord
-    dtype: string
-  - name: nom_localite
-    dtype: string
-  - name: name_structure_sanitaire
-    dtype: string
-  - name: nom_hop
-    dtype: string
-  - name: georef
-    dtype: string
-  - name: type_cxxxgroupes
-    dtype: string
-  - name: typo_ministere
-    dtype: string
-  - name: liste_officielle
-    dtype: string
-  - name: reg
-    dtype: string
-  - name: pref
-    dtype: string
-  - name: admin2_code
-    dtype: string
-  - name: spref
-    dtype: string
-  - name: admin3_code
-    dtype: string
-  - name: prefecture_prioritaire
-    dtype: string
-  - name: acteur
-    dtype: string
-  - name: kit
-    dtype: string
-  - name: remarque
-    dtype: string
-  - name: esa_source
-    dtype: string
-  - name: esa_processed
-    dtype: string
   splits:
-  - name: train
-    num_bytes: 312267
-    num_examples: 1397
-  - name: test
-    num_bytes: 77998
-    num_examples: 350
-  download_size: 136175
-  dataset_size: 390265
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
+    - name: train
+      num_examples: 1397
+    - name: test
+      num_examples: 349
 ---
+
+# Guinea: Health Centers Data Base
+
+**Publisher:** WASH Cluster Guinea (inactive) · **Source:** [HDX](https://data.humdata.org/dataset/health-centers-data-base) · **License:** `other-pd-nr` · **Updated:** 2023-03-03
+
+---
+
+## Abstract
+
+This "Health Center Database" is a compilation about a work of the WASH cluster Guinea in collaboration with all his partners.
+This data base has been built from the initial data base from the Health Ministry of Guinea.
+If you get any suggestions or updates to this "Health center database", please send an email to: washclusterguinea@gmail.com
+The compilation of the update will be send to this HDX regularly.
+
+Each row in this dataset represents subnational administrative unit observations. Data was last updated on HDX on 2023-03-03. Geographic scope: **GIN**.
+
+*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*
+
+---
+
+## Dataset Characteristics
+
+| | |
+|---|---|
+| **Domain** | Public health |
+| **Unit of observation** | Subnational administrative unit observations |
+| **Rows (total)** | 1,747 |
+| **Columns** | 22 (2 numeric, 20 categorical, 0 datetime) |
+| **Train split** | 1,397 rows |
+| **Test split** | 349 rows |
+| **Geographic scope** | GIN |
+| **Publisher** | WASH Cluster Guinea (inactive) |
+| **HDX last updated** | 2023-03-03 |
+
+---
+
+## Variables
+
+**Geographic** — `code_provisoire` (1, GIN00700109 CSMitt, GIN00700110PSKene), `x` (range -15.0219–12.5832), `y` (range 7.2563–14.4817), `sourcecoord` (geonode, Ministere Plan, CRS), `type_cxxxgroupes` (PS, CS, HP) and 3 others.
+
+**Identifier / Metadata** — `name_structure_sanitaire` (Balandougou, Hamdallaye, Hafia), `georef` (OK, Coord absent), `pref`, `spref`, `prefecture_prioritaire` and 2 others.
+
+**Other** — `nom_localite` (Labé, Hafia, Kankan), `nom_hop` (Sanoyah, Hérico, Balandougou), `liste_officielle` (ok, Non), `reg` (Nzerekore, Kankan, Kindia), `acteur` and 2 others.
+
+---
+
+## Quick Start
+
+```python
+from datasets import load_dataset
+
+ds    = load_dataset("electricsheepafrica/africa-health-centers-data-base")
+train = ds["train"].to_pandas()
+test  = ds["test"].to_pandas()
+
+print(train.shape)
+train.head()
+```
+
+---
+
+## Schema
+
+| Column | Type | Null % | Range / Sample Values |
+|---|---|---|---|
+| `code_provisoire` | object | 0.0% | 1, GIN00700109 CSMitt, GIN00700110PSKene |
+| `x` | float64 | 33.0% | -15.0219 – 12.5832 (mean -10.7227) |
+| `y` | float64 | 33.0% | 7.2563 – 14.4817 (mean 10.0786) |
+| `sourcecoord` | object | 29.4% | geonode, Ministere Plan, CRS |
+| `nom_localite` | object | 38.6% | Labé, Hafia, Kankan |
+| `name_structure_sanitaire` | object | 0.0% | Balandougou, Hamdallaye, Hafia |
+| `nom_hop` | object | 33.7% | Sanoyah, Hérico, Balandougou |
+| `georef` | object | 0.1% | OK, Coord absent |
+| `type_cxxxgroupes` | object | 0.0% | PS, CS, HP |
+| `typo_ministere` | object | 1.4% | PS,  CS, CS |
+| `liste_officielle` | object | 0.1% | ok, Non |
+| `reg` | object | 0.0% | Nzerekore, Kankan, Kindia |
+| `pref` | object | 0.0% |  |
+| `admin2_code` | object | 1.7% |  |
+| `spref` | object | 0.0% |  |
+| `admin3_code` | object | 0.0% |  |
+| `prefecture_prioritaire` | object | 45.6% |  |
+| `acteur` | object | 71.7% |  |
+| `kit` | object | 76.8% |  |
+| `remarque` | object | 80.0% |  |
+| `esa_source` | object | 0.0% |  |
+| `esa_processed` | object | 0.0% |  |
+
+---
+
+## Numeric Summary
+
+| Column | Min | Max | Mean | Median |
+|---|---|---|---|---|
+| `x` | -15.0219 | 12.5832 | -10.7227 | -10.7212 |
+| `y` | 7.2563 | 14.4817 | 10.0786 | 10.2138 |
+
+---
+
+## 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`. 7 column(s) with >80% missing values were removed: `activite`, `tri_isolement`, `infra`, `nan`, `unnamed_24`, `unnamed_25`.... 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 WASH Cluster Guinea (inactive) and has not been independently validated by ESA.
+- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
+- The following columns have >20% missing values and should be treated with caution in modelling: `x`, `y`, `sourcecoord`, `nom_localite`, `nom_hop`, `prefecture_prioritaire`, `acteur`, `kit`....
+- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/health-centers-data-base) for the publisher's own methodology notes and caveats.
+
+---
+
+## Citation
+
+```bibtex
+@dataset{hdx_africa_health_centers_data_base,
+  title     = {Guinea: Health Centers Data Base},
+  author    = {WASH Cluster Guinea (inactive)},
+  year      = {2023},
+  url       = {https://data.humdata.org/dataset/health-centers-data-base},
+  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.*