electricsheepafrica/africa-national-registered-medical-personnel-2000-to-2013

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: other
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- tabular-classification
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- health
- health-facilities
- ken
pretty_name: "National Registered Medical Personnel: 2000 to 2013"
dataset_info:
splits:
- name: train
num_examples: 8
- name: test
num_examples: 2
---

# National Registered Medical Personnel: 2000 to 2013

**Publisher:** Kenya National Bureau of Statistics (inactive) · **Source:** [HDX](https://data.humdata.org/dataset/national-registered-medical-personnel-2000-to-2013) · **License:** `other-pd-nr` · **Updated:** 2025-02-06

---

## Abstract

This dataset shows the Nationally Registered Medical Personnel: 2000 to 2013

Each row in this dataset represents time-series observations. Data was last updated on HDX on 2025-02-06. 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)** | 11 |
| **Columns** | 17 (14 numeric, 3 categorical, 0 datetime) |
| **Train split** | 8 rows |
| **Test split** | 2 rows |
| **Geographic scope** | KEN |
| **Publisher** | Kenya National Bureau of Statistics (inactive) |
| **HDX last updated** | 2025-02-06 |

---

## Variables

**Geographic** — `type_of_personnel_over_the_years` (PharmTechnologist, Registered Nurses, Pharmacists).

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

**Other** — `2000` (range 0.0–55732.0), `2001` (range 0.0–57208.0), `2002` (range 0.0–59049.0), `2003` (range 0.0–60599.0), `2004` (range 280.0–67993.0) and 9 others.

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-national-registered-medical-personnel-2000-to-2013")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `type_of_personnel_over_the_years` | object | 0.0% | PharmTechnologist, Registered Nurses, Pharmacists |
| `2000` | int64 | 0.0% | 0.0 – 55732.0 (mean 10133.0909) |
| `2001` | int64 | 0.0% | 0.0 – 57208.0 (mean 10401.4545) |
| `2002` | int64 | 0.0% | 0.0 – 59049.0 (mean 10736.1818) |
| `2003` | int64 | 0.0% | 0.0 – 60599.0 (mean 11018.0) |
| `2004` | int64 | 0.0% | 280.0 – 67993.0 (mean 11929.0909) |
| `2005` | int64 | 0.0% | 367.0 – 65914.0 (mean 11984.3636) |
| `2006` | int64 | 0.0% | 478.0 – 67175.0 (mean 12213.6364) |
| `2007` | int64 | 0.0% | 585.0 – 73236.0 (mean 13315.6364) |
| `2008` | int64 | 0.0% | 657.0 – 76883.0 (mean 13978.7273) |
| `2009` | int64 | 0.0% | 859.0 – 95390.0 (mean 17343.6364) |
| `2010` | int64 | 0.0% | 898.0 – 100411.0 (mean 18256.5455) |
| `2011` | int64 | 0.0% | 930.0 – 95960.0 (mean 17447.2727) |
| `2012` | int64 | 0.0% | 985.0 – 104913.0 (mean 19075.0909) |
| `2013` | int64 | 0.0% | 1045.0 – 112576.0 (mean 20468.3636) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-07 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `2000` | 0.0 | 55732.0 | 10133.0909 | 4492.0 |
| `2001` | 0.0 | 57208.0 | 10401.4545 | 4610.0 |
| `2002` | 0.0 | 59049.0 | 10736.1818 | 4740.0 |
| `2003` | 0.0 | 60599.0 | 11018.0 | 4804.0 |
| `2004` | 280.0 | 67993.0 | 11929.0909 | 4953.0 |
| `2005` | 367.0 | 65914.0 | 11984.3636 | 5059.0 |
| `2006` | 478.0 | 67175.0 | 12213.6364 | 5285.0 |
| `2007` | 585.0 | 73236.0 | 13315.6364 | 5969.0 |
| `2008` | 657.0 | 76883.0 | 13978.7273 | 5969.0 |
| `2009` | 859.0 | 95390.0 | 17343.6364 | 6800.0 |
| `2010` | 898.0 | 100411.0 | 18256.5455 | 7129.0 |
| `2011` | 930.0 | 95960.0 | 17447.2727 | 7549.0 |
| `2012` | 985.0 | 104913.0 | 19075.0909 | 8069.0 |
| `2013` | 1045.0 | 112576.0 | 20468.3636 | 8637.0 |

---

## 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`. 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 National Bureau of Statistics (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/national-registered-medical-personnel-2000-to-2013) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_national_registered_medical_personnel_2000_to_2013,
title = {National Registered Medical Personnel: 2000 to 2013},
author = {Kenya National Bureau of Statistics (inactive)},
year = {2025},
url = {https://data.humdata.org/dataset/national-registered-medical-personnel-2000-to-2013},
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.*