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README.md

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 ---
-dataset_info:
-  features:
-  - name: country_name
-    dtype: string
-  - name: country_iso3
-    dtype: string
-  - name: year
-    dtype: int64
-  - name: Pregnant women with anemia
-    dtype: float64
-  - name: Children with anemia
-    dtype: float64
-  - name: World region according to OWID
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 55798
-    num_examples: 1036
-  - name: test
-    num_bytes: 13749
-    num_examples: 260
-  download_size: 16538
-  dataset_size: 69547
-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
+- our-world-in-data
+- anemia-pregnant-women-vs-children
+- owid
+- long-run-series
+- time-series
+pretty_name: "Anemia Pregnant Women Vs Children | Africa (Our World in Data)"
 ---
+
+# Anemia Pregnant Women Vs Children | Africa (Our World in Data)
+
+🌍 **1,296 observations** · **54 Africa countries** · **2000–2023** · *Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*
+
+![rows](https://img.shields.io/badge/rows-1,296-blue) ![countries](https://img.shields.io/badge/countries-54-green) ![years](https://img.shields.io/badge/years-2000–2023-orange) ![license](https://img.shields.io/badge/license-cc-by-4.0-lightgrey)
+
+## TL;DR
+
+This dataset contains **1,296 observations** of `Anemia Pregnant Women Vs Children` data across **54 Africa countries**, spanning **2000–2023**.
+
+## About the source
+
+- **Source:** [Our World in Data](https://ourworldindata.org/grapher/anemia-pregnant-women-vs-children)
+- **Publisher:** Our World in Data
+- **License:** [cc-by-4.0](https://creativecommons.org/licenses/by/4.0/)
+- **Topic:** Anemia Pregnant Women Vs Children
+
+## Geographic coverage
+
+54 Africa countries · top rows shown below, sorted by row count:
+
+| Country | Rows | First year | Last year |
+|---------|-----:|-----------:|----------:|
+| `AGO` | 24 | 2000 | 2023 |
+| `BDI` | 24 | 2000 | 2023 |
+| `BEN` | 24 | 2000 | 2023 |
+| `BFA` | 24 | 2000 | 2023 |
+| `BWA` | 24 | 2000 | 2023 |
+| `CAF` | 24 | 2000 | 2023 |
+| `CIV` | 24 | 2000 | 2023 |
+| `CMR` | 24 | 2000 | 2023 |
+| `COD` | 24 | 2000 | 2023 |
+| `COG` | 24 | 2000 | 2023 |
+| `COM` | 24 | 2000 | 2023 |
+| `CPV` | 24 | 2000 | 2023 |
+| `DJI` | 24 | 2000 | 2023 |
+| `DZA` | 24 | 2000 | 2023 |
+| `EGY` | 24 | 2000 | 2023 |
+| ... | _39 more countries_ | | |
+
+## Schema
+
+| Column | Type | Description | Example |
+|--------|------|-------------|---------|
+| `country_name` | `string` | — | `Algeria` |
+| `country_iso3` | `string` | — | `DZA` |
+| `year` | `int64` | — | `2000` |
+| `Pregnant women with anemia` | `float64` | — | `36.1` |
+| `Children with anemia` | `float64` | — | `39.9` |
+| `World region according to OWID` | `string` | — | `Africa` |
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("electricsheepafrica/africa-owid-anemia-pregnant-women-vs-children")
+df = ds["train"].to_pandas()
+print(df.head())
+```
+
+### Filter to one country
+
+```python
+kenya = df[df["country_iso3"] == "KEN"]
+```
+
+### Time-series for a single indicator
+
+```python
+sample = df.sort_values("year")
+sample.plot(x="year", y="Pregnant women with anemia")
+```
+
+## Citation
+
+```bibtex
+@misc{africa_owid_anemia_pregnant_women_vs_children_2023,
+  title        = {Anemia Pregnant Women Vs Children | Africa (Our World in Data)},
+  author       = {Our World in Data},
+  year         = {2023},
+  url          = {https://ourworldindata.org/grapher/anemia-pregnant-women-vs-children},
+  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
+  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-owid-anemia-pregnant-women-vs-children}}
+}
+```
+
+## License
+
+Released under [cc-by-4.0](https://creativecommons.org/licenses/by/4.0/).
+
+Original data © Our World in Data. 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 2026-06-01 via the Electric Sheep pipeline. Source URL: https://ourworldindata.org/grapher/anemia-pregnant-women-vs-children_