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license: cc-by-4.0
language:
- en
task_categories:
- tabular-classification
- tabular-regression
multilinguality: monolingual
size_categories:
- 1K<n<10K
tags:
- tabular
- csv
- africa
- mali
- official-statistics
- open-data
- agriculture
configs:
- config_name: default
data_files:
- split: train
path: data/train-00000-of-00001.parquet
pretty_name: "Crop production: Humanitarian Response Plan (HRP) Countries Exposure Data for Disaster Risk Assessment | Africa (Mali official open data)"
---
# Crop production: Humanitarian Response Plan (HRP) Countries Exposure Data for Disaster Risk Assessment | Africa (Mali official open data)
1,257 rows - 1 Africa country - not-applicable - Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)
## TL;DR
This dataset packages one official `CSV` resource from **Mali** as
ML-ready Parquet. The source file is the provenance boundary; all usable
indicators or tabular columns from the resource stay together in this repo.
## About the source
- **Source:** [Crop production: Humanitarian Response Plan (HRP) Countries Exposure Data for Disaster Risk Assessment](https://data.humdata.org/dataset/climada-crop-production-dataset)
- **Publisher:** ETH Zürich - Weather and Climate Risks
- **Resource:** [somalia-admin1-crop-production.csv](https://data.humdata.org/dataset/eca4e1bd-ca2e-4fc7-925a-3273b1e30737/resource/7f73db3e-56f1-4c9b-99de-0c58ee8699ec/download/somalia-admin1-crop-production.csv)
- **Format:** `CSV`
- **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
- **Packaging mode:** `tabular_resource`
## Geographic coverage
1 Africa country:
| Country | Rows | First year | Last year | Name |
|---------|-----:|-----------:|----------:|------|
| `MLI` | 1,257 | n/a | n/a | `Mali` |
## Indicators or Resource Contents
- This source file is packaged as a normalized tabular resource.
## Schema
| Column | Type | Description | Example |
|--------|------|-------------|---------|
| `source_record_id` | `string` | Stable row identifier for tabular resources. | `7f73db3e-56f1-4c9b-99de-0c58ee8699ec:0` |
| `country_iso3` | `category` | ISO3 country code. | `MLI` |
| `country_name` | `category` | Country name. | `Mali` |
| `country_name_2` | `string` | Source column. | `#country` |
| `admin1_name` | `string` | Source column. | `#adm1+name` |
| `latitude` | `float64` | Source column. | `` |
| `longitude` | `float64` | Source column. | `` |
| `aggregation` | `string` | Source column. | `` |
| `indicator` | `string` | Source column. | `#indicator+name` |
| `value` | `float64` | Numeric observation value. | `` |
| `source_period_start_year` | `Int64` | First year inferred from source resource metadata. | `` |
| `source_period_end_year` | `Int64` | Last year inferred from source resource metadata. | `` |
| `source_period_label` | `string` | Human-readable period inferred from source resource metadata. | `` |
| `source_provider` | `category` | Publishing organization. | `ETH Zürich - Weather and Climate Risks` |
| `source_dataset` | `category` | Source package title. | `Crop production: Humanitarian Response Plan (HRP) Countries Exposure Dat` |
| `source_resource` | `category` | Source resource title. | `somalia-admin1-crop-production.csv` |
| `source_package_id` | `category` | CKAN package UUID. | `eca4e1bd-ca2e-4fc7-925a-3273b1e30737` |
| `source_resource_id` | `category` | CKAN resource UUID. | `7f73db3e-56f1-4c9b-99de-0c58ee8699ec` |
| `source_url` | `category` | Original source resource URL. | `https://data.humdata.org/dataset/eca4e1bd-ca2e-4fc7-925a-3273b1e30737/re` |
| `license_id` | `category` | Source license identifier. | `cc-by` |
| `retrieved_at` | `category` | UTC retrieval timestamp. | `2026-08-12T23:12:09Z` |
## Usage
```python
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-mali-crop-production-humanitarian-response-plan-hrp-countries-e-155f3908")
df = ds["train"].to_pandas()
print(df.head())
```
### Filter to one country
```python
sample_country = df[df["country_iso3"] == "MLI"]
```
### Work with indicators
```python
if "indicator_id" in df.columns:
print(df["indicator_id"].value_counts().head())
sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])
```
## Citation
```bibtex
@misc{electric_sheep_africa_africa_mali_crop_production_humanitarian_response_plan_hrp_countries_e_155f3908_2026,
title = {Crop production: Humanitarian Response Plan (HRP) Countries Exposure Data for Disaster Risk Assessment | Africa (Mali official open data)},
author = {ETH Zürich - Weather and Climate Risks},
year = {2026},
url = {https://data.humdata.org/dataset/climada-crop-production-dataset},
publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mali-crop-production-humanitarian-response-plan-hrp-countries-e-155f3908}}
}
```
## License
Released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
Original data (c) ETH Zürich - Weather and Climate Risks. 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 Hugging Face. 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 2026-08-13 via the Electric Sheep pipeline. Source URL:
https://data.humdata.org/dataset/eca4e1bd-ca2e-4fc7-925a-3273b1e30737/resource/7f73db3e-56f1-4c9b-99de-0c58ee8699ec/download/somalia-admin1-crop-production.csv
|