electricsheepafrica/africa-main-source-of-water-for-doing-laundry

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: other
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- tabular-classification
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- water-sanitation-and-hygiene-wash
- ken
pretty_name: "Main source of water for doing laundry"
dataset_info:
splits:
- name: train
num_examples: 17
- name: test
num_examples: 4
---

# Main source of water for doing laundry

**Publisher:** Majidata (inactive) · **Source:** [HDX](https://data.humdata.org/dataset/main-source-of-water-for-doing-laundry) · **License:** `other-pd-nr` · **Updated:** 2023-05-16

---

## Abstract

This dataset shows the Main source of water for doing laundry in Kenya

Each row in this dataset represents tabular records. Data was last updated on HDX on 2023-05-16. Geographic scope: **KEN**.

*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Water, sanitation and hygiene (wash) |
| **Unit of observation** | Tabular records |
| **Rows (total)** | 22 |
| **Columns** | 8 (5 numeric, 3 categorical, 0 datetime) |
| **Train split** | 17 rows |
| **Test split** | 4 rows |
| **Geographic scope** | KEN |
| **Publisher** | Majidata (inactive) |
| **HDX last updated** | 2023-05-16 |

---

## Variables

**Geographic** — `watersrclndry` (Piped water (own connection, on the plot), Piped water(connection of someone else, outside the plot), Vandalised pipe).

**Identifier / Metadata** — `esa_source` (HDX), `esa_processed` (2026-04-07).

**Other** — `smpsrc` (range 2.0–26337.0), `smpdus` (range 91296.0–91296.0), `totdus` (range 1645735.0–1645735.0), `pcntdususingsrc` (range 0.0–28.85), `nousingsrc` (range 36.0–474760.0).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-main-source-of-water-for-doing-laundry")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

print(train.shape)
train.head()
```

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `watersrclndry` | object | 0.0% | Piped water (own connection, on the plot), Piped water(connection of someone else, outside the plot), Vandalised pipe |
| `smpsrc` | int64 | 0.0% | 2.0 – 26337.0 (mean 4149.8182) |
| `smpdus` | int64 | 0.0% | 91296.0 – 91296.0 (mean 91296.0) |
| `totdus` | int64 | 0.0% | 1645735.0 – 1645735.0 (mean 1645735.0) |
| `pcntdususingsrc` | float64 | 0.0% | 0.0 – 28.85 (mean 4.5459) |
| `nousingsrc` | int64 | 0.0% | 36.0 – 474760.0 (mean 74806.1818) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-07 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `smpsrc` | 2.0 | 26337.0 | 4149.8182 | 836.5 |
| `smpdus` | 91296.0 | 91296.0 | 91296.0 | 91296.0 |
| `totdus` | 1645735.0 | 1645735.0 | 1645735.0 | 1645735.0 |
| `pcntdususingsrc` | 0.0 | 28.85 | 4.5459 | 0.915 |
| `nousingsrc` | 36.0 | 474760.0 | 74806.1818 | 15079.0 |

---

## 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: `unnamed_6`. 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 Majidata (inactive) 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/main-source-of-water-for-doing-laundry) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_main_source_of_water_for_doing_laundry,
title = {Main source of water for doing laundry},
author = {Majidata (inactive)},
year = {2023},
url = {https://data.humdata.org/dataset/main-source-of-water-for-doing-laundry},
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.*