Upload dataset folder
Browse files- README.md +147 -0
- data/train-00000-of-00001.parquet +3 -0
- metadata/source_snapshot.json +58 -0
README.md
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| 1 |
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---
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| 2 |
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license: cc-by-4.0
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| 3 |
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language:
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| 4 |
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- en
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| 5 |
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task_categories:
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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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- 1K<n<10K
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tags:
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- tabular
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- csv
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- africa
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- namibia
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- official-statistics
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- open-data
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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-00000-of-00001.parquet
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pretty_name: "Namibia - Environment | Africa (Namibia official open data)"
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---
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# Namibia - Environment | Africa (Namibia official open data)
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4,604 rows - 1 Africa country - 1960-2025 - Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)
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## TL;DR
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This dataset packages one official `CSV` resource from **Namibia** as
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ML-ready Parquet. The source file is the provenance boundary; all usable
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indicators or tabular columns from the resource stay together in this repo.
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## About the source
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- **Source:** [Namibia - Environment](https://data.humdata.org/dataset/world-bank-environment-indicators-for-namibia)
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- **Publisher:** World Bank Group
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- **Resource:** [Environment Indicators for Namibia](https://data.humdata.org/dataset/2b058af6-46e4-425c-bb79-23f1240e1dea/resource/f5a49b0b-6e6c-4ddc-96c9-b529a463170f/download/environment_nam.csv)
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- **Format:** `CSV`
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- **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
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- **Packaging mode:** `indicator_long`
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## Geographic coverage
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1 Africa country:
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| Country | Rows | First year | Last year | Name |
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|---------|-----:|-----------:|----------:|------|
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| `NAM` | 4,604 | 1960 | 2025 | `Namibia` |
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## Indicators or Resource Contents
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- `namibia-environment-49e8a587` - Namibia - Environment
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## Schema
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| Column | Type | Description | Example |
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|--------|------|-------------|---------|
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| `indicator_id` | `string` | Stable indicator identifier. | `namibia-environment-49e8a587` |
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| `indicator_name` | `string` | Human-readable indicator name. | `Namibia - Environment` |
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| `country_iso3` | `string` | ISO3 country code. | `NAM` |
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| `country_name` | `string` | Country name. | `Namibia` |
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| `year` | `Int64` | Observation year. | `2023` |
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| `value` | `float64` | Numeric observation value. | `47.142562159142` |
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| `unit` | `string` | Measurement unit, when available. | `source_units_unspecified` |
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| `dimension_country_name` | `string` | Source dimension. | `Namibia` |
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| `dimension_country_iso3` | `string` | Source dimension. | `NAM` |
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| `dimension_indicator_name` | `string` | Source dimension. | `Agricultural land (% of land area)` |
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| `dimension_indicator_code` | `string` | Source dimension. | `AG.LND.AGRI.ZS` |
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| `source_period_start_year` | `Int64` | First year inferred from source resource metadata. | `` |
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| `source_period_end_year` | `Int64` | Last year inferred from source resource metadata. | `` |
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| `source_period_label` | `string` | Human-readable period inferred from source resource metadata. | `` |
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| `source_provider` | `category` | Publishing organization. | `World Bank Group` |
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| `source_dataset` | `category` | Source package title. | `Namibia - Environment` |
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| `source_resource` | `category` | Source resource title. | `Environment Indicators for Namibia` |
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| `source_package_id` | `category` | CKAN package UUID. | `2b058af6-46e4-425c-bb79-23f1240e1dea` |
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| `source_resource_id` | `category` | CKAN resource UUID. | `f5a49b0b-6e6c-4ddc-96c9-b529a463170f` |
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| `source_url` | `category` | Original source resource URL. | `https://data.humdata.org/dataset/2b058af6-46e4-425c-bb79-23f1240e1dea/re` |
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| `license_id` | `category` | Source license identifier. | `cc-by` |
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| `retrieved_at` | `category` | UTC retrieval timestamp. | `2026-08-30T05:38:32Z` |
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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("electricsheepafrica/africa-namibia-namibia-environment-8e50432f")
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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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sample_country = df[df["country_iso3"] == "NAM"]
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```
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### Work with indicators
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```python
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if "indicator_id" in df.columns:
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print(df["indicator_id"].value_counts().head())
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sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])
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```
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## Citation
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```bibtex
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@misc{electric_sheep_africa_africa_namibia_namibia_environment_8e50432f_2025,
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title = {Namibia - Environment | Africa (Namibia official open data)},
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author = {World Bank Group},
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year = {2025},
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url = {https://data.humdata.org/dataset/world-bank-environment-indicators-for-namibia},
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publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
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howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-namibia-namibia-environment-8e50432f}}
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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 (c) World Bank Group. When using this dataset, please cite both the
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original source above and the Electric Sheep Africa repackaging.
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## About Electric Sheep
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Electric Sheep Africa is part of the Electric Sheep mission: a unified,
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ML-ready data layer for Africa on Hugging Face. We pull data from authoritative
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open sources, normalize the schemas, package as Parquet, and publish with
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consistent dataset cards so researchers and developers can use `load_dataset()`
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to start working in seconds.
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Browse the full collection: [huggingface.co/electricsheepafrica](https://huggingface.co/electricsheepafrica)
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---
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Provenance: ingested 2026-08-30 via the Electric Sheep pipeline. Source URL:
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https://data.humdata.org/dataset/2b058af6-46e4-425c-bb79-23f1240e1dea/resource/f5a49b0b-6e6c-4ddc-96c9-b529a463170f/download/environment_nam.csv
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data/train-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:9c13edd0e94d57847f458037f558ab5ba4e279f087c7b6740807705808d6623c
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size 50305
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metadata/source_snapshot.json
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{
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"columns": [
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"indicator_id",
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"indicator_name",
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"country_iso3",
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"country_name",
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"year",
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"value",
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| 9 |
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"unit",
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"dimension_country_name",
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"dimension_country_iso3",
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"dimension_indicator_name",
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"dimension_indicator_code",
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"source_period_start_year",
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"source_period_end_year",
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"source_period_label",
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"source_provider",
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"source_dataset",
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"source_resource",
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"source_package_id",
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"source_resource_id",
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"source_url",
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"license_id",
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"retrieved_at"
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],
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"generated_at": "2026-08-30T05:54:51Z",
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"indicator_count": 1,
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"mode": "indicator_long",
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"repo_id": "electricsheepafrica/africa-namibia-namibia-environment-8e50432f",
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| 30 |
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"rows": 4604,
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"source": {
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| 32 |
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"api_base_url": "https://data.humdata.org/api/3/action",
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"country_iso3": "NAM",
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"country_name": "Namibia",
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"group_names": "nam",
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| 36 |
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"license_id": "cc-by",
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| 37 |
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"license_title": "Creative Commons Attribution International (CC BY)",
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| 38 |
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"license_url": "http://www.opendefinition.org/licenses/cc-by",
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| 39 |
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"organization_name": "world-bank-group",
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| 40 |
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"organization_title": "World Bank Group",
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| 41 |
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"package_id": "2b058af6-46e4-425c-bb79-23f1240e1dea",
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| 42 |
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"package_name": "world-bank-environment-indicators-for-namibia",
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"package_notes": "Contains data from the World Bank's [data portal](http://data.worldbank.org/). There is also a [consolidated country dataset](https://data.humdata.org/dataset/world-bank-combined-indicators-for-namibia) on HDX. Natural and man-made environmental resources – fresh water, clean air, forests, grasslands, marine resources, and agro-ecosystems – provide sustenance and a foundation for social and economic development. The need to safeguard these resources crosses all borders. Today, the World Bank is one of the key promoters and financiers of environmental upgrading in the developing world. Data here cover forests, biodiversity, emissions, and pollution. Other indicators relevant to the environment are found under data pages for Agriculture & Rural Development, Energy & Mining, Infrastructure, and Urban Development.",
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| 44 |
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"package_page_url": "https://data.humdata.org/dataset/world-bank-environment-indicators-for-namibia",
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"package_title": "Namibia - Environment",
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| 46 |
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"portal_url": "https://data.humdata.org",
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"resource_description": "csv containing Environment indicators Indicators: Access to clean fuels and technologies for cooking, Access to electricity, Adjusted net savings, Adjusted savings, Agricultural land, Annual freshwater withdrawals, Aquaculture production, Arable land, Average precipitation in depth, Bird species, Capture fisheries production, Carbon dioxide, Carbon intensity of GDP, Coal rents, Droughts, Electricity production from oil, Electricity production from renewable sources, Energy intensity level of primary energy, Energy related methane emissions, F-gases emissions from Industrial Processes, Fish species, Forest area, Forest rents, Land area, Land area where elevation is below 5 meters, Level of water stress, Mammal species, Marine protected areas, Methane, Mineral rents, Mortality rate attributed to household and ambient air pollution, Mortality rate attributed to unintentional poisoning, Mortality rate attributed to unsafe water, Natural gas rents, Nitrous oxide, Nitrous oxide emissions in industrial and energy processes, Oil rents, PM2.5 air pollution, PM2.5 pollution, People practicing open defecation, People using at least basic drinking water services, People using at least basic sanitation services, People with basic handwashing facilities including soap and water, Plant species, Population living in areas where elevation is below 5 meters, Population living in slums, Renewable electricity output, Renewable energy consumption, Renewable internal freshwater resources, Renewable internal freshwater resources per capita, Rural land area, Rural land area where elevation is below 5 meters, Rural population living in areas where elevation is below 5 meters, Surface area, Terrestrial and marine protected areas, Terrestrial protected areas, Total fisheries production, Total greenhouse gas emissions excluding LULUCF, Total greenhouse gas emissions excluding LULUCF per capita, Total greenhouse gas emissions including LULUCF, Total natural resources rents, Urban land area, Urban land area where elevation is below 5 meters, Urban population living in areas where elevation is below 5 meters, Water productivity",
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"resource_format": "CSV",
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| 49 |
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"resource_id": "f5a49b0b-6e6c-4ddc-96c9-b529a463170f",
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| 50 |
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"resource_last_modified": "2026-07-17T00:52:43.496782",
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| 51 |
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"resource_name": "Environment Indicators for Namibia",
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| 52 |
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"resource_position": "0",
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| 53 |
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"resource_url": "https://data.humdata.org/dataset/2b058af6-46e4-425c-bb79-23f1240e1dea/resource/f5a49b0b-6e6c-4ddc-96c9-b529a463170f/download/environment_nam.csv",
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| 54 |
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"tag_names": "environment,indicators"
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| 55 |
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},
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| 56 |
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"year_max": 2025,
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| 57 |
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"year_min": 1960
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| 58 |
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}
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