Standardize Electric Sheep Africa dataset card

README.md

@@ -2,66 +2,141 @@
 license: cc-by-4.0
 language:
 - en
+task_categories:
+- tabular-classification
+- tabular-regression
+multilinguality: monolingual
+size_categories:
+- 100K<n<1M
 tags:
-- africa
-- faostat
-- agriculture
-- food-security
-- tabular
-pretty_name: "Macro Indicators — Africa (FAOSTAT)"
+- "africa"
+- "electric-sheep-africa"
+- "open-data"
+- "metadata-backed"
+- "agriculture-food"
+- "parquet"
+- "tabular"
+- "text"
+- "faostat"
+- "agriculture"
+- "food-security"
+- "food"
+- "fisheries"
+- "forestry"
+pretty_name: "Macro Indicators — Africa (FAOSTAT) | Africa (Electric Sheep Africa metadata inventory)"
 ---
 
-# Macro Indicators — Africa
-
-**Source:** [FAOSTAT — Macro Indicators](https://www.fao.org/faostat/en/#data/MK)
-**Domain code:** `MK`
-**Publisher:** Food and Agriculture Organization of the United Nations (FAO)
-**Coverage:** 51 African countries · 1970–2024 · 154,509 rows
-**Items:** 11 · **Elements:** 20
-
-## About
-
-FAOSTAT is the world's largest and most comprehensive statistical database on food, agriculture, fisheries,
-forestry, and rural development. This dataset contains the **Macro Indicators** domain filtered to all available
-African countries, repackaged in ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).
-
-## Schema
-
-| Column | Type |
-|--------|------|
-| `Domain Code` | object |
-| `Domain` | object |
-| `Area Code` | int64 |
-| `Area` | object |
-| `Element Code` | int64 |
-| `Element` | object |
-| `Item Code` | int64 |
-| `Item` | object |
-| `Year Code` | int64 |
-| `Year` | object |
-| `Unit` | object |
-| `Value` | float64 |
+# Macro Indicators — Africa (FAOSTAT) | Africa (Electric Sheep Africa metadata inventory)
+
+**Size category:** `100K<n<1M` - **Formats:** `parquet` - **Sector:** agriculture_food - *Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*
+
+![size](https://img.shields.io/badge/size-100K%3Cn%3C1M-blue)
+![sector](https://img.shields.io/badge/sector-agriculture_food-green)
+![downloads](https://img.shields.io/badge/HF_downloads-7-orange)
+![license](https://img.shields.io/badge/license-cc--by--4.0-lightgrey)
+
+## TL;DR
+
+This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
+
+## What This Dataset Covers
+
+Public datasets help analysts inspect structured evidence, build reproducible workflows, and compare patterns across domains.
+
+Dataset context from the existing Hugging Face card: Macro Indicators — Africa Source: FAOSTAT — Macro Indicators Domain code: MK Publisher: Food and Agriculture Organization of the United Nations (FAO) Coverage: 51 African countries · 1970–2024 · 154,509 rows Items: 11 · Elements: 20 About FAOSTAT is the world's largest and most comprehensive statistical database on food, agriculture, fisheries, forestry, and rural development. This dataset contains the Macro Indicators domain filtered to all available African countries… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-faostat-macro-indicators-mk.
+
+## Dataset Profile
+
+| Field | Value |
+|---|---|
+| Hugging Face repo | [`electricsheepafrica/africa-faostat-macro-indicators-mk`](https://huggingface.co/datasets/electricsheepafrica/africa-faostat-macro-indicators-mk) |
+| Sector | agriculture_food |
+| Topic tags | faostat, agriculture, food-security, tabular |
+| Modalities | `tabular`, `text` |
+| Formats | `parquet` |
+| Size category | `100K<n<1M` |
+| Countries | Africa-wide or source-defined African coverage |
+| ISO3 coverage | `not declared` |
+| Last modified on HF | `2026-05-04 02:07:55+00:00` |
+| Inventory snapshot | `2026-07-16T16:00:34Z` |
+
+## How To Read This Dataset
+
+- Start from the repository files and the dataset viewer when available.
+- Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
+- Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
+- Preserve missing values until you have a defensible imputation rule.
 
 ## Usage
 
 ```python
 from datasets import load_dataset
-ds = load_dataset("electricsheepafrica/africa-faostat-mk")
-df = ds["train"].to_pandas()
+
+ds = load_dataset("electricsheepafrica/africa-faostat-macro-indicators-mk")
+print(ds)
+
+split_name = next(iter(ds))
+table = ds[split_name]
+print(table.features)
+print(table[:3])
 ```
 
-## Citation
+### Convert To Pandas When Tabular
+
+```python
+from datasets import Dataset
 
+first_split = ds[next(iter(ds))]
+if isinstance(first_split, Dataset):
+    df = first_split.to_pandas()
+    print(df.head())
 ```
-@misc{faostat_mk_africa,
-  title     = {Macro Indicators — Africa},
-  author    = {Food and Agriculture Organization of the United Nations},
-  year      = {2024},
-  url       = {https://www.fao.org/faostat/en/#data/MK},
-  note      = {Repackaged by Electric Sheep Africa}
+
+## Data Quality Notes
+
+- This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
+- Exact schema, row counts, and source files should be inspected in the repository data files.
+- Metadata gaps from the inventory: country, upstream_publisher.
+- Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.
+
+## Source And Provenance
+
+- **Source context:** Electric Sheep Africa metadata inventory
+- **Publisher/source attribution:** Public dataset metadata
+- **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
+- **Hugging Face URL:** [https://huggingface.co/datasets/electricsheepafrica/africa-faostat-macro-indicators-mk](https://huggingface.co/datasets/electricsheepafrica/africa-faostat-macro-indicators-mk)
+- **Inventory retrieved at:** `2026-07-16T16:00:34Z`
+
+## Suggested Analyses
+
+- Inspect schema and missingness before modeling.
+- Profile variables by geography, time, and subgroup columns where present.
+- Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
+- Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.
+
+## Citation
+
+```bibtex
+@misc{electric_sheep_africa_africa_faostat_macro_indicators_mk_2026,
+  title        = {Macro Indicators — Africa (FAOSTAT) | Africa (Electric Sheep Africa metadata inventory)},
+  author       = {Public dataset metadata},
+  year         = {2026},
+  url          = {https://huggingface.co/datasets/electricsheepafrica/africa-faostat-macro-indicators-mk},
+  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
+  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-faostat-macro-indicators-mk}}
 }
 ```
 
 ## License
 
-[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) — FAO open data.
+Released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
+
+Original source rights remain with the original publisher or data provider. Electric Sheep Africa engineering standardizes discovery metadata, documentation, and usage guidance for analysis on Hugging Face.
+
+## About Electric Sheep Africa
+
+Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.
+
+---
+
+Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: `catalog/esa_metadata_inventory/master_metadata.jsonl`.