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electricsheepafrica/africa-hrp-projects-lso

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Hugging Face2026-04-07 更新2026-04-12 收录
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https://hf-mirror.com/datasets/electricsheepafrica/africa-hrp-projects-lso
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--- annotations_creators: - no-annotation language_creators: - found language: - en license: cc-by-4.0 multilinguality: - monolingual size_categories: - n<1K source_datasets: - original task_categories: - other task_ids: [] tags: - africa - humanitarian - hdx - electric-sheep-africa - humanitarian-response-plan-hrp - hxl - who-is-doing-what-and-where-3w-4w-5w - lso pretty_name: "Lesotho: Response Plan projects" dataset_info: splits: - name: train num_examples: 11 - name: test num_examples: 2 --- # Lesotho: Response Plan projects **Publisher:** OCHA Humanitarian Programme Cycle Tools (HPC Tools) · **Source:** [HDX](https://data.humdata.org/dataset/hrp-projects-lso) · **License:** `cc-by-igo` · **Updated:** 2026-03-17 --- ## Abstract Projects proposed, in progress, or completed as part of the annual Lesotho Humanitarian Response Plans (HRPs) or other Humanitarian Programme Cycle plans. The original data is available on https://hpc.tools **Important:** some projects in Lesotho might be missing, and others might not apply specifically to Lesotho. See _Caveats_ under the _Additional information_ tab. Each row in this dataset represents time-series observations. Temporal coverage is indicated by the `startdate`, `enddate` column(s). Geographic scope: **LSO**. *Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).* --- ## Dataset Characteristics | | | |---|---| | **Domain** | Humanitarian and development data | | **Unit of observation** | Time-series observations | | **Rows (total)** | 14 | | **Columns** | 13 (1 numeric, 10 categorical, 2 datetime) | | **Train split** | 11 rows | | **Test split** | 2 rows | | **Geographic scope** | LSO | | **Publisher** | OCHA Humanitarian Programme Cycle Tools (HPC Tools) | | **HDX last updated** | 2026-03-17 | --- ## Variables **Geographic** — `locations` (LSO, #country+code). **Temporal** — `startdate`, `enddate`. **Identifier / Metadata** — `name` (Food Security, Health, Protection), `versioncode` (#activity+code+v_hpc, FLSO1920-EDU-165928-1, FLSO1920-FSC-165918-1), `response_plan_code` (FLSO1920, #response+plan+code), `esa_source` (HDX), `esa_processed` (2026-04-07). **Other** — `currentrequestedfunds` (range 30000.0–12000000.0), `objective` (Food Security, Health, Protection), `globalclusters` (Food Security, Health, Protection), `organizations` (United Nations Children's Fund, #org+prog+name, Food and Agriculture Organization of the United Nations), `plans` (Lesotho Flash Appeal 2019-2020, #response+plan+name). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-hrp-projects-lso") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() ``` --- ## Schema | Column | Type | Null % | Range / Sample Values | |---|---|---|---| | `name` | object | 0.0% | Food Security, Health, Protection | | `versioncode` | object | 0.0% | #activity+code+v_hpc, FLSO1920-EDU-165928-1, FLSO1920-FSC-165918-1 | | `currentrequestedfunds` | float64 | 7.1% | 30000.0 – 12000000.0 (mean 2595769.2308) | | `objective` | object | 0.0% | Food Security, Health, Protection | | `startdate` | datetime64[ns] | 7.1% | | | `enddate` | datetime64[ns] | 7.1% | | | `globalclusters` | object | 0.0% | Food Security, Health, Protection | | `locations` | object | 0.0% | LSO, #country+code | | `organizations` | object | 0.0% | United Nations Children's Fund, #org+prog+name, Food and Agriculture Organization of the United Nations | | `plans` | object | 0.0% | Lesotho Flash Appeal 2019-2020, #response+plan+name | | `response_plan_code` | object | 0.0% | FLSO1920, #response+plan+code | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-07 | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `currentrequestedfunds` | 30000.0 | 12000000.0 | 2595769.2308 | 505000.0 | --- ## Curation Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (`N/A`, `null`, `none`, `-`, `unknown`, `no data`, `#N/A`) were unified to `NaN`. 1 column(s) with >80% missing values were removed: `partners`. 3 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet. --- ## Limitations - Data originates from OCHA Humanitarian Programme Cycle Tools (HPC Tools) and has not been independently validated by ESA. - Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection. - Refer to the [original HDX dataset page](https://data.humdata.org/dataset/hrp-projects-lso) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_hrp_projects_lso, title = {Lesotho: Response Plan projects}, author = {OCHA Humanitarian Programme Cycle Tools (HPC Tools)}, year = {2026}, url = {https://data.humdata.org/dataset/hrp-projects-lso}, note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)} } ``` --- *[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*
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