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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: 520130
-    num_examples: 6355
-  - name: test
-    num_bytes: 131380
-    num_examples: 1589
-  download_size: 84915
-  dataset_size: 651510
-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:
+- 1K<n<10K
+tags:
+- tabular
+- africa
+- faostat-(fao)
+- population-and-employment
+- faostat
+- fao
+- agriculture
+- food-security
+- time-series
+pretty_name: "Annual population — Total Population - Female | Africa (FAOSTAT)"
 ---
+
+# Annual population — Total Population - Female | Africa (FAOSTAT)
+
+🌍 **7,944 observations** · **54 Africa countries** · **1950–2100** · *Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*
+
+![rows](https://img.shields.io/badge/rows-7,944-blue) ![countries](https://img.shields.io/badge/countries-54-green) ![years](https://img.shields.io/badge/years-1950–2100-orange) ![indicators](https://img.shields.io/badge/indicators-1-purple) ![license](https://img.shields.io/badge/license-cc-by-4.0-lightgrey)
+
+## TL;DR
+
+This dataset contains **7,944 observations** of `Population and Employment` data across **54 Africa countries**, spanning **1950–2100**, covering **1 distinct indicators**.
+
+## About the source
+
+- **Source:** [FAOSTAT (FAO)](https://www.fao.org/faostat/en/#data/OA)
+- **Publisher:** Food and Agriculture Organization of the United Nations (FAO)
+- **License:** [cc-by-4.0](https://creativecommons.org/licenses/by/4.0/)
+- **Topic:** Population and Employment
+
+## Geographic coverage
+
+54 Africa countries · top rows shown below, sorted by row count:
+
+| Country | Rows | First year | Last year |
+|---------|-----:|-----------:|----------:|
+| `Algeria` | 151 | 1950 | 2100 |
+| `Angola` | 151 | 1950 | 2100 |
+| `Benin` | 151 | 1950 | 2100 |
+| `Botswana` | 151 | 1950 | 2100 |
+| `Burkina Faso` | 151 | 1950 | 2100 |
+| `Burundi` | 151 | 1950 | 2100 |
+| `Cabo Verde` | 151 | 1950 | 2100 |
+| `Cameroon` | 151 | 1950 | 2100 |
+| `Central African Republic` | 151 | 1950 | 2100 |
+| `Chad` | 151 | 1950 | 2100 |
+| `Comoros` | 151 | 1950 | 2100 |
+| `Congo` | 151 | 1950 | 2100 |
+| `Côte d'Ivoire` | 151 | 1950 | 2100 |
+| `Democratic Republic of the Congo` | 151 | 1950 | 2100 |
+| `Djibouti` | 151 | 1950 | 2100 |
+| ... | _39 more countries_ | | |
+
+## Indicators (sample)
+
+- `Population - Est. & Proj.`
+
+## Schema
+
+| Column | Type | Description | Example |
+|--------|------|-------------|---------|
+| `country_name` | `string` | — | `Algeria` |
+| `country_m49` | `int64` | — | `12` |
+| `item` | `string` | — | `Population - Est. & Proj.` |
+| `year` | `int64` | — | `1950` |
+| `value` | `float64` | — | `4405.596` |
+| `unit` | `string` | — | `1000 No` |
+| `flag` | `string` | — | `X` |
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("electricsheepafrica/africa-annual-population-total-population-female")
+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"] == "Population - Est. & Proj."]
+          .sort_values("year"))
+sample.plot(x="year", y="value", title="Population - Est. & Proj.")
+```
+
+### Pivot to country × year matrix
+
+```python
+matrix = (df[df["item"] == "Population - Est. & Proj."]
+          .pivot_table(index="year", columns="country_name", values="value"))
+print(matrix.tail())
+```
+
+## Citation
+
+```bibtex
+@misc{africa_annual_population_total_population_female_2100,
+  title        = {Annual population — Total Population - Female | Africa (FAOSTAT)},
+  author       = {Food and Agriculture Organization of the United Nations (FAO)},
+  year         = {2100},
+  url          = {https://www.fao.org/faostat/en/#data/OA},
+  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
+  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-annual-population-total-population-female}}
+}
+```
+
+## 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/OA_