electricsheepafrica/africa-kenya-nakuru-county-monthly-new-born-health-statistics

---
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:
- tabular-classification
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- births
- children
- ken
pretty_name: "Kenya - Nakuru county monthly child health statistics"
dataset_info:
splits:
- name: train
num_examples: 182
- name: test
num_examples: 45
---

# Kenya - Nakuru county monthly child health statistics

**Publisher:** Kenya Open Data Initiative (inactive) · **Source:** [HDX](https://data.humdata.org/dataset/kenya-nakuru-county-monthly-new-born-health-statistics) · **License:** `cc-by` · **Updated:** 2023-10-18

---

## Abstract

Nakuru county monthly child health statistics

Each row in this dataset represents time-series observations. Temporal coverage is indicated by the `date` column(s). Geographic scope: **KEN**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Public health |
| **Unit of observation** | Time-series observations |
| **Rows (total)** | 228 |
| **Columns** | 6 (1 numeric, 4 categorical, 1 datetime) |
| **Train split** | 182 rows |
| **Test split** | 45 rows |
| **Geographic scope** | KEN |
| **Publisher** | Kenya Open Data Initiative (inactive) |
| **HDX last updated** | 2023-10-18 |

---

## Variables

**Geographic** — `no_of_births_in_nakuru_county` (25, 31, 37).

**Temporal** — `date`.

**Identifier / Metadata** — `objectid` (range 0.0–227.0), `esa_source` (HDX), `esa_processed` (2026-04-10).

**Other** — `new_born_health` (Live birth, Fresh Still Birth, Macerated still Birth).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-kenya-nakuru-county-monthly-new-born-health-statistics")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `new_born_health` | object | 0.0% | Live birth, Fresh Still Birth, Macerated still Birth |
| `no_of_births_in_nakuru_county` | object | 0.0% | 25, 31, 37 |
| `date` | datetime64[ns] | 0.0% | |
| `objectid` | int64 | 0.0% | 0.0 – 227.0 (mean 113.5) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-10 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `objectid` | 0.0 | 227.0 | 113.5 | 113.5 |

---

## 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) 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 Kenya Open Data Initiative (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/kenya-nakuru-county-monthly-new-born-health-statistics) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_kenya_nakuru_county_monthly_new_born_health_statistics,
title = {Kenya - Nakuru county monthly child health statistics},
author = {Kenya Open Data Initiative (inactive)},
year = {2023},
url = {https://data.humdata.org/dataset/kenya-nakuru-county-monthly-new-born-health-statistics},
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.*