electricsheepafrica/africa-ethiopia-climate-data
收藏Hugging Face2026-04-20 更新2026-04-26 收录
下载链接：
https://hf-mirror.com/datasets/electricsheepafrica/africa-ethiopia-climate-data
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资源简介：
---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- tabular-classification
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- agriculture-livestock
- climate-weather
- environment
- health
- eth
pretty_name: "Ethiopia - Climate data"
dataset_info:
splits:
- name: train
num_examples: 2478
- name: test
num_examples: 619
---
# Ethiopia - Climate data
**Publisher:** 3iS · **Source:** [HDX](https://data.humdata.org/dataset/ethiopia-climate-data) · **License:** `cc-by` · **Updated:** 2025-04-15
---
## Abstract
Climate data estimated using satellite images using Google Earth Engine (GEE) and Amazon Sagemaker with Geospatial Capabilities.
Each row in this dataset represents tabular records. Temporal coverage is indicated by the `mm_precipitation_chirps_at_shabelle_1981_11_26_to_2024_11_26` column(s). Geographic scope: **ETH**.
*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*
---
## Dataset Characteristics
| | |
|---|---|
| **Domain** | Public health |
| **Unit of observation** | Tabular records |
| **Rows (total)** | 3,098 |
| **Columns** | 4 (1 numeric, 2 categorical, 1 datetime) |
| **Train split** | 2,478 rows |
| **Test split** | 619 rows |
| **Geographic scope** | ETH |
| **Publisher** | 3iS |
| **HDX last updated** | 2025-04-15 |
---
## Variables
**Identifier / Metadata** — `unnamed_1` (range 0.0–81.2188), `esa_source` (HDX), `esa_processed` (2026-04-19).
**Other** — `mm_precipitation_chirps_at_shabelle_1981_11_26_to_2024_11_26`.
---
## Quick Start
```python
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-ethiopia-climate-data")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()
print(train.shape)
train.head()
```
---
## Schema
| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `mm_precipitation_chirps_at_shabelle_1981_11_26_to_2024_11_26` | datetime64[ns] | 0.0% | |
| `unnamed_1` | float64 | 0.0% | 0.0 – 81.2188 (mean 3.8296) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-19 |
---
## Numeric Summary
| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `unnamed_1` | 0.0 | 81.2188 | 3.8296 | 0.5398 |
---
## 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`. 2 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 3iS 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/ethiopia-climate-data) for the publisher's own methodology notes and caveats.
---
## Citation
```bibtex
@dataset{hdx_africa_ethiopia_climate_data,
title = {Ethiopia - Climate data},
author = {3iS},
year = {2025},
url = {https://data.humdata.org/dataset/ethiopia-climate-data},
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.*
提供机构：
electricsheepafrica
