Upload dataset folder
Browse files- README.md +147 -0
- data/train-00000-of-00001.parquet +3 -0
- metadata/source_snapshot.json +57 -0
README.md
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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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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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- mali
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- official-statistics
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- open-data
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- agriculture
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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: "Crop production: Humanitarian Response Plan (HRP) Countries Exposure Data for Disaster Risk Assessment | Africa (Mali official open data)"
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---
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# Crop production: Humanitarian Response Plan (HRP) Countries Exposure Data for Disaster Risk Assessment | Africa (Mali official open data)
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1,185 rows - 1 Africa country - not-applicable - 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 **Mali** 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:** [Crop production: Humanitarian Response Plan (HRP) Countries Exposure Data for Disaster Risk Assessment](https://data.humdata.org/dataset/climada-crop-production-dataset)
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- **Publisher:** ETH Zürich - Weather and Climate Risks
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- **Resource:** [cameroon-admin1-crop-production.csv](https://data.humdata.org/dataset/eca4e1bd-ca2e-4fc7-925a-3273b1e30737/resource/3572a14f-7ed4-4857-b95c-62b1fbb3fadc/download/cameroon-admin1-crop-production.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:** `tabular_resource`
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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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| `MLI` | 1,185 | n/a | n/a | `Mali` |
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## Indicators or Resource Contents
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- This source file is packaged as a normalized tabular resource.
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## Schema
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| Column | Type | Description | Example |
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|--------|------|-------------|---------|
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| `source_record_id` | `string` | Stable row identifier for tabular resources. | `3572a14f-7ed4-4857-b95c-62b1fbb3fadc:0` |
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| `country_iso3` | `category` | ISO3 country code. | `MLI` |
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| `country_name` | `category` | Country name. | `Mali` |
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| `country_name_2` | `string` | Source column. | `#country` |
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| `admin1_name` | `string` | Source column. | `#adm1+name` |
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| `latitude` | `float64` | Source column. | `` |
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| `longitude` | `float64` | Source column. | `` |
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| `aggregation` | `string` | Source column. | `` |
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| `indicator` | `string` | Source column. | `#indicator+name` |
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| `value` | `float64` | Numeric observation value. | `` |
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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. | `ETH Zürich - Weather and Climate Risks` |
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| `source_dataset` | `category` | Source package title. | `Crop production: Humanitarian Response Plan (HRP) Countries Exposure Dat` |
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| `source_resource` | `category` | Source resource title. | `cameroon-admin1-crop-production.csv` |
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| `source_package_id` | `category` | CKAN package UUID. | `eca4e1bd-ca2e-4fc7-925a-3273b1e30737` |
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| `source_resource_id` | `category` | CKAN resource UUID. | `3572a14f-7ed4-4857-b95c-62b1fbb3fadc` |
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| `source_url` | `category` | Original source resource URL. | `https://data.humdata.org/dataset/eca4e1bd-ca2e-4fc7-925a-3273b1e30737/re` |
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| `license_id` | `category` | Source license identifier. | `cc-by` |
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| `retrieved_at` | `category` | UTC retrieval timestamp. | `2026-08-12T23:12:09Z` |
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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-mali-crop-production-humanitarian-response-plan-hrp-countries-e-db9820c5")
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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"] == "MLI"]
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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_mali_crop_production_humanitarian_response_plan_hrp_countries_e_db9820c5_2026,
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title = {Crop production: Humanitarian Response Plan (HRP) Countries Exposure Data for Disaster Risk Assessment | Africa (Mali official open data)},
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author = {ETH Zürich - Weather and Climate Risks},
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year = {2026},
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url = {https://data.humdata.org/dataset/climada-crop-production-dataset},
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publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
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howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mali-crop-production-humanitarian-response-plan-hrp-countries-e-db9820c5}}
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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) ETH Zürich - Weather and Climate Risks. 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 2026-08-13 via the Electric Sheep pipeline. Source URL:
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https://data.humdata.org/dataset/eca4e1bd-ca2e-4fc7-925a-3273b1e30737/resource/3572a14f-7ed4-4857-b95c-62b1fbb3fadc/download/cameroon-admin1-crop-production.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:b7dc8865807d025cb413dbe3d22ac4ec0dd2a8258c7a10a3d46e41a07f0d144f
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size 21008
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metadata/source_snapshot.json
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{
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"columns": [
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| 3 |
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"source_record_id",
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| 4 |
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"country_iso3",
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| 5 |
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"country_name",
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| 6 |
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"country_name_2",
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| 7 |
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"admin1_name",
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| 8 |
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"latitude",
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| 9 |
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"longitude",
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| 10 |
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"aggregation",
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| 11 |
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"indicator",
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| 12 |
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"value",
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| 13 |
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"source_period_start_year",
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| 14 |
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"source_period_end_year",
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| 15 |
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"source_period_label",
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| 16 |
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"source_provider",
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| 17 |
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"source_dataset",
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| 18 |
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"source_resource",
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| 19 |
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"source_package_id",
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| 20 |
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"source_resource_id",
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| 21 |
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"source_url",
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| 22 |
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"license_id",
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| 23 |
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"retrieved_at"
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| 24 |
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],
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| 25 |
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"generated_at": "2026-08-13T00:19:55Z",
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| 26 |
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"indicator_count": 0,
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| 27 |
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"mode": "tabular_resource",
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| 28 |
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"repo_id": "electricsheepafrica/africa-mali-crop-production-humanitarian-response-plan-hrp-countries-e-db9820c5",
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| 29 |
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"rows": 1185,
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| 30 |
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"source": {
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| 31 |
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"api_base_url": "https://data.humdata.org/api/3/action",
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| 32 |
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"country_iso3": "MLI",
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| 33 |
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"country_name": "Mali",
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| 34 |
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"group_names": "afg,bfa,bdi,cmr,caf,tcd,col,cod,eth,hti,mli,moz,mmr,ner,nga,som,ssd,pse,sdn,syr,ukr,ven,yem",
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| 35 |
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"license_id": "cc-by",
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| 36 |
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"license_title": "Creative Commons Attribution International (CC BY)",
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| 37 |
+
"license_url": "http://www.opendefinition.org/licenses/cc-by",
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| 38 |
+
"organization_name": "eth-zurich-weather-and-climate-risks",
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| 39 |
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"organization_title": "ETH Zürich - Weather and Climate Risks",
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| 40 |
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"package_id": "eca4e1bd-ca2e-4fc7-925a-3273b1e30737",
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| 41 |
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"package_name": "climada-crop-production-dataset",
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| 42 |
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"package_notes": "Historical and twenty-first century crop production in tons. Global gridded (4km resolution) crop yield simulations for maize, rice, soybean, and wheat, encompassing an ensemble of transient yield simulation output from eight global gridded crop models driven by bias-corrected output from five global climate models, as facilitated by the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP, isimip.org)",
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| 43 |
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"package_page_url": "https://data.humdata.org/dataset/climada-crop-production-dataset",
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| 44 |
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"package_title": "Crop production: Humanitarian Response Plan (HRP) Countries Exposure Data for Disaster Risk Assessment",
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| 45 |
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"portal_url": "https://data.humdata.org",
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| 46 |
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"resource_description": "Gridded crop-production data for four crops under two irrigation conditions for Cameroon with admin1 name column",
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| 47 |
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"resource_format": "CSV",
|
| 48 |
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"resource_id": "3572a14f-7ed4-4857-b95c-62b1fbb3fadc",
|
| 49 |
+
"resource_last_modified": "2025-09-03T09:34:00.651690",
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| 50 |
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"resource_name": "cameroon-admin1-crop-production.csv",
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| 51 |
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"resource_position": "4",
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| 52 |
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"resource_url": "https://data.humdata.org/dataset/eca4e1bd-ca2e-4fc7-925a-3273b1e30737/resource/3572a14f-7ed4-4857-b95c-62b1fbb3fadc/download/cameroon-admin1-crop-production.csv",
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| 53 |
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"tag_names": "geodata,hazards and risk,humanitarian response plan-hrp,hxl"
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| 54 |
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},
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| 55 |
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"year_max": null,
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| 56 |
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"year_min": null
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| 57 |
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}
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