Datasets:
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
1K - 10K
Tags:
africa
humanitarian
hdx
electric-sheep-africa
cyclones-hurricanes-typhoons
operational-presence
License:
Add README.md
Browse files
README.md
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multilinguality:
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- monolingual
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size_categories:
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- n<
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source_datasets:
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- original
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task_categories:
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- humanitarian
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- hdx
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- electric-sheep-africa
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-
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- operational-presence
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- who-is-doing-what-and-where-3w-4w-5w
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- phl
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pretty_name:
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dataset_info:
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features:
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- name: esa_source
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dtype: string
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- name: esa_processed
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dtype: string
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splits:
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num_bytes: 26166
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num_examples: 1246
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download_size: 4131
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dataset_size: 130767
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configs:
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- config_name: default
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data_files:
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path: data/train-*
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path: data/test-*
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---
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# Philippines
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**Publisher:**
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---
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## Abstract
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Each row in this dataset represents
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*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*
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| **Domain** | Humanitarian and development data |
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| **Unit of observation** |
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| **Rows (total)** |
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| **Columns** |
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| **Train split** |
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| **Test split** |
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| **Geographic scope** | PHL |
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| **Publisher** |
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| **HDX last updated** |
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---
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## Variables
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**
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**Identifier / Metadata** — `esa_source`, `esa_processed`.
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**Other** — `organization` (PHILIPPINE RED CROSS, PHILIPPINE DISASTER RESILIENCE FOUNDATION, ADVENTIST DEVELOPMENT AND RELIEF AGENCY (ADRA)), `partner` (PRC, UNSPECIFIED, Adventist Community Services (ACS)), `cluster` (Health, WASH, NFI), `sub_cluster` (UNSPECIFIED, Food Security, Agriculture and Livelihood, PSS), `evacuation_site` (UNSPECIFIED, Cabuyao, Concepcion Elementary School) and 6 others.
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---
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| Column | Type | Null % | Range / Sample Values |
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| `partner` | object | 0.8% | PRC, UNSPECIFIED, Adventist Community Services (ACS) |
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| `cluster` | object | 0.0% | Health, WASH, NFI |
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| `sub_cluster` | object | 0.0% | UNSPECIFIED, Food Security, Agriculture and Livelihood, PSS |
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| `region` | object | 0.0% | REGION IV-A (CALABARZON), Region IV-A (CALABARZON), NATIONAL CAPITAL REGION (NCR) |
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| `province` | object | 0.0% | BATANGAS, CAVITE, LAGUNA |
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| `city_municipality` | object | 0.0% | UNSPECIFIED, BATANGAS CITY (CAPITAL), BAUAN |
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| `barangay` | object | 0.0% | UNSPECIFIED, Barangay 2, Batangas Sports Complex |
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| `evacuation_site` | object | 0.2% | UNSPECIFIED, Cabuyao, Concepcion Elementary School |
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| `activity` | object | 0.0% | |
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| `status_ongoing_completed_planned` | object | 0.0% | |
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| `start` | datetime64[ns] | 3.7% | |
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| `finish` | object | 0.0% | |
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| `remarks` | object | 0.2% | |
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| `region_code` | object | 0.2% | |
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| `province_code` | object | 0.2% | |
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| `mun_city_code` | object | 0.2% | |
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| `mun` | object | 0.2% | |
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| `pro` | object | 0.2% | |
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| `esa_source` | object | 0.0% | |
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| `esa_processed` | object | 0.0% | |
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---
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## Curation
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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`.
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---
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## Limitations
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- Data originates from
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- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
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- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/philippines-who-
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---
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```bibtex
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@dataset{hdx_asia_operational_presence_all,
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title = {Philippines
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author = {
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year = {
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url = {https://data.humdata.org/dataset/philippines-who-
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note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
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}
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```
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multilinguality:
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- monolingual
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size_categories:
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- 1K<n<10K
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source_datasets:
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- original
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task_categories:
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- humanitarian
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- hdx
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- electric-sheep-africa
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- cyclones-hurricanes-typhoons
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- operational-presence
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- shelter
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- who-is-doing-what-and-where-3w-4w-5w
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- phl
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pretty_name: "Philippines - Who does What, Where, and When (4W) typhoon Goni and Vamco"
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dataset_info:
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splits:
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- name: train
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num_examples: 4981
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- name: test
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num_examples: 1245
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---
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# Philippines - Who does What, Where, and When (4W) typhoon Goni and Vamco
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**Publisher:** Global Shelter Cluster (inactive) · **Source:** [HDX](https://data.humdata.org/dataset/philippines-who-does-what-where-and-when-4w-for-typhoon-goni-and-vamco-01-december-2020) · **License:** `cc-by` · **Updated:** 2025-03-07
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---
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## Abstract
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Shelter Cluster 4W report (Who does What, Where, and When) for typhoon Goni (Rolly) and Vamco (Ulysses) in the Philippines
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Each row in this dataset represents tabular records. Data was last updated on HDX on 2025-03-07. Geographic scope: **PHL**.
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*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*
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|---|---|
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| **Domain** | Humanitarian and development data |
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| **Unit of observation** | Tabular records |
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| **Rows (total)** | 6,227 |
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| **Columns** | 2 (0 numeric, 2 categorical, 0 datetime) |
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| **Train split** | 4,981 rows |
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| **Test split** | 1,245 rows |
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| **Geographic scope** | PHL |
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| **Publisher** | Global Shelter Cluster (inactive) |
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| **HDX last updated** | 2025-03-07 |
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---
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## Variables
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**Identifier / Metadata** — `esa_source` (HDX), `esa_processed` (2026-05-04).
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---
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| Column | Type | Null % | Range / Sample Values |
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| `esa_source` | object | 0.0% | HDX |
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| `esa_processed` | object | 0.0% | 2026-05-04 |
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---
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## Curation
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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`. 38 column(s) with >80% missing values were removed: `unnamed_0`, `unnamed_1`, `unnamed_2`, `unnamed_3`, `unnamed_4`, `unnamed_5`.... The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.
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---
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## Limitations
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- Data originates from Global Shelter Cluster (inactive) and has not been independently validated by ESA.
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- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
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- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/philippines-who-does-what-where-and-when-4w-for-typhoon-goni-and-vamco-01-december-2020) for the publisher's own methodology notes and caveats.
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---
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```bibtex
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@dataset{hdx_asia_operational_presence_all,
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title = {Philippines - Who does What, Where, and When (4W) typhoon Goni and Vamco},
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author = {Global Shelter Cluster (inactive)},
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year = {2025},
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url = {https://data.humdata.org/dataset/philippines-who-does-what-where-and-when-4w-for-typhoon-goni-and-vamco-01-december-2020},
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note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
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}
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```
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