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README.md
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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- split: test
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path: data/test-*
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---
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license: cc-by-4.0
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language:
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- en
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task_categories:
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- tabular-classification
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- tabular-regression
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- time-series-forecasting
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multilinguality: monolingual
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size_categories:
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- n<1K
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tags:
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- tabular
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- europe
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- our-world-in-data
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- literacy
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- owid
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- long-run-series
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- time-series
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pretty_name: "Literacy | Europe (Our World in Data)"
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---
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# Literacy | Europe (Our World in Data)
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🇪🇺 **85 observations** · **24 Europe countries** · **1978–2022** · *Repackaged by [Electric Sheep Europe](https://huggingface.co/electricsheepeurope)*
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## TL;DR
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This dataset contains **85 observations** of `Literacy` data across **24 Europe countries**, spanning **1978–2022**.
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## About the source
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- **Source:** [Our World in Data](https://ourworldindata.org/grapher/literacy)
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- **Publisher:** Our World in Data
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- **License:** [cc-by-4.0](https://creativecommons.org/licenses/by/4.0/)
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- **Topic:** Literacy
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## Geographic coverage
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24 Europe countries · top rows shown below, sorted by row count:
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| Country | Rows | First year | Last year |
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|---------|-----:|-----------:|----------:|
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| `ESP` | 18 | 1981 | 2021 |
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| `ALB` | 5 | 2001 | 2017 |
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| `MNE` | 5 | 1981 | 2018 |
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| `GRC` | 4 | 1981 | 2009 |
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| `RUS` | 4 | 1989 | 2021 |
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| `MLT` | 4 | 1985 | 2011 |
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| `ITA` | 4 | 1981 | 2019 |
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| `BLR` | 4 | 1989 | 2019 |
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| `ROU` | 4 | 1992 | 2021 |
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| `SRB` | 4 | 2003 | 2019 |
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| `BIH` | 3 | 1991 | 2013 |
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| `EST` | 3 | 1989 | 2011 |
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| `LVA` | 3 | 1989 | 2011 |
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| `PRT` | 3 | 1981 | 2011 |
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| `MDA` | 3 | 1989 | 2014 |
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| ... | _9 more countries_ | | |
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## Schema
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| Column | Type | Description | Example |
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|--------|------|-------------|---------|
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| `country_name` | `string` | — | `Albania` |
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| `country_iso3` | `string` | — | `ALB` |
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| `year` | `int64` | — | `2001` |
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| `Literacy rate among adults` | `float64` | — | `99.0` |
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## Usage
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```python
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from datasets import load_dataset
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ds = load_dataset("electricsheepeurope/europe-owid-literacy")
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df = ds["train"].to_pandas()
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print(df.head())
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```
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### Filter to one country
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```python
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germany = df[df["country_iso3"] == "DEU"]
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```
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### Time-series for a single indicator
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```python
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sample = df.sort_values("year")
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sample.plot(x="year", y="Literacy rate among adults")
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```
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## Citation
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```bibtex
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@misc{europe_owid_literacy_2022,
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title = {Literacy | Europe (Our World in Data)},
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author = {Our World in Data},
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year = {2022},
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url = {https://ourworldindata.org/grapher/literacy},
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publisher = {HuggingFace Datasets, repackaged by Electric Sheep Europe},
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howpublished = {\url{https://huggingface.co/datasets/electricsheepeurope/europe-owid-literacy}}
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}
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```
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## License
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Released under [cc-by-4.0](https://creativecommons.org/licenses/by/4.0/).
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Original data © Our World in Data. When using this dataset, please cite both the original source above and the Electric Sheep Europe repackaging.
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## About Electric Sheep
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Electric Sheep Europe is part of the Electric Sheep mission: a unified, ML-ready data layer for Europe 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.
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Browse the full collection: [huggingface.co/electricsheepeurope](https://huggingface.co/electricsheepeurope)
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---
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_Provenance: ingested 2026-06-06 via the Electric Sheep pipeline. Source URL: https://ourworldindata.org/grapher/literacy_
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