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README.md

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 ---
-dataset_info:
-  features:
-  - name: country_name
-    dtype: string
-  - name: country_m49
-    dtype: int64
-  - name: item
-    dtype: string
-  - name: year
-    dtype: int64
-  - name: value
-    dtype: float64
-  - name: unit
-    dtype: string
-  - name: flag
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 940402
-    num_examples: 11533
-  - name: test
-    num_bytes: 238825
-    num_examples: 2884
-  download_size: 167609
-  dataset_size: 1179227
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
+license: cc-by-4.0
+language:
+- en
+task_categories:
+- tabular-classification
+- tabular-regression
+- time-series-forecasting
+multilinguality: monolingual
+size_categories:
+- 10K<n<100K
+tags:
+- tabular
+- africa
+- faostat-(fao)
+- macro-economic-indicators
+- faostat
+- fao
+- agriculture
+- food-security
+- time-series
+pretty_name: "Macro Indicators — Annual growth US$ | Africa (FAOSTAT)"
 ---
+
+# Macro Indicators — Annual growth US$ | Africa (FAOSTAT)
+
+🌍 **14,417 observations** · **54 Africa countries** · **1971–2024** · *Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*
+
+![rows](https://img.shields.io/badge/rows-14,417-blue) ![countries](https://img.shields.io/badge/countries-54-green) ![years](https://img.shields.io/badge/years-1971–2024-orange) ![indicators](https://img.shields.io/badge/indicators-9-purple) ![license](https://img.shields.io/badge/license-cc-by-4.0-lightgrey)
+
+## TL;DR
+
+This dataset contains **14,417 observations** of `Macro-Economic Indicators` data across **54 Africa countries**, spanning **1971–2024**, covering **9 distinct indicators**.
+
+## About the source
+
+- **Source:** [FAOSTAT (FAO)](https://www.fao.org/faostat/en/#data/MK)
+- **Publisher:** Food and Agriculture Organization of the United Nations (FAO)
+- **License:** [cc-by-4.0](https://creativecommons.org/licenses/by/4.0/)
+- **Topic:** Macro-Economic Indicators
+
+## Geographic coverage
+
+54 Africa countries · top rows shown below, sorted by row count:
+
+| Country | Rows | First year | Last year |
+|---------|-----:|-----------:|----------:|
+| `Kenya` | 351 | 1971 | 2024 |
+| `Mauritius` | 318 | 1971 | 2024 |
+| `Botswana` | 316 | 1971 | 2024 |
+| `South Africa` | 302 | 1971 | 2024 |
+| `Mozambique` | 300 | 1971 | 2024 |
+| `Cameroon` | 297 | 1971 | 2024 |
+| `Eswatini` | 290 | 1971 | 2024 |
+| `Namibia` | 288 | 1971 | 2024 |
+| `Rwanda` | 287 | 1971 | 2024 |
+| `United Republic of Tanzania` | 286 | 1971 | 2024 |
+| `Burkina Faso` | 285 | 1971 | 2024 |
+| `Burundi` | 284 | 1971 | 2024 |
+| `Lesotho` | 283 | 1971 | 2024 |
+| `Tunisia` | 283 | 1971 | 2024 |
+| `Uganda` | 282 | 1971 | 2024 |
+| ... | _39 more countries_ | | |
+
+## Indicators (sample)
+
+- `Gross Domestic Product`
+- `Gross Fixed Capital Formation`
+- `Value Added (Agriculture, Forestry and Fishing)`
+- `Value Added (Total Manufacturing)`
+- `Gross National Income`
+- `Value Added (Agriculture)`
+- `Value Added (Manufacture of food, beverages and tobacco products)`
+- `Value Added (Manufacture of food and beverages)`
+- `Value Added (Manufacture of tobacco products)`
+
+## Schema
+
+| Column | Type | Description | Example |
+|--------|------|-------------|---------|
+| `country_name` | `string` | — | `Algeria` |
+| `country_m49` | `int64` | — | `12` |
+| `item` | `string` | — | `Gross Domestic Product` |
+| `year` | `int64` | — | `1971` |
+| `value` | `float64` | — | `4.045599` |
+| `unit` | `string` | — | `%` |
+| `flag` | `string` | — | `X` |
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("electricsheepafrica/africa-macro-indicators-annual-growth-us")
+df = ds["train"].to_pandas()
+print(df.head())
+```
+
+### Filter to one country
+
+```python
+kenya = df[df["country_name"] == "KEN"]
+```
+
+### Time-series for a single indicator
+
+```python
+sample = (df[df["item"] == "Gross Domestic Product"]
+          .sort_values("year"))
+sample.plot(x="year", y="value", title="Gross Domestic Product")
+```
+
+### Pivot to country × year matrix
+
+```python
+matrix = (df[df["item"] == "Gross Domestic Product"]
+          .pivot_table(index="year", columns="country_name", values="value"))
+print(matrix.tail())
+```
+
+## Citation
+
+```bibtex
+@misc{africa_macro_indicators_annual_growth_us_2024,
+  title        = {Macro Indicators — Annual growth US$ | Africa (FAOSTAT)},
+  author       = {Food and Agriculture Organization of the United Nations (FAO)},
+  year         = {2024},
+  url          = {https://www.fao.org/faostat/en/#data/MK},
+  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
+  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-macro-indicators-annual-growth-us}}
+}
+```
+
+## License
+
+Released under [cc-by-4.0](https://creativecommons.org/licenses/by/4.0/).
+
+Original data © Food and Agriculture Organization of the United Nations (FAO). When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.
+
+## About Electric Sheep
+
+Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa on HuggingFace. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use `load_dataset()` to start working in seconds.
+
+Browse the full collection: [huggingface.co/electricsheepafrica](https://huggingface.co/electricsheepafrica)
+
+---
+
+_Provenance: ingested 2026-06-17 via the Electric Sheep pipeline. Source URL: https://www.fao.org/faostat/en/#data/MK_