electricsheepafrica/africa-covid-19-vaccinations

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- other
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- covid-19
- hxl
- vaccination-immunization
- alb
- dza
- and
- aia
- arg
pretty_name: "Coronavirus (COVID-19) Vaccinations"
dataset_info:
splits:
- name: train
num_examples: 156996
- name: test
num_examples: 39249
---

# Coronavirus (COVID-19) Vaccinations

**Publisher:** HDX · **Source:** [HDX](https://data.humdata.org/dataset/covid-19-vaccinations) · **License:** `cc-by` · **Updated:** 2026-02-01

---

## Abstract

The data represent the number of COVID-19 vaccination doses administered per 100 people within a given population. This indicator does not reflect the total number of individuals who are fully vaccinated, as full vaccination typically requires two doses.

Each row in this dataset represents country-level aggregates. Temporal coverage is indicated by the `date` column(s). Geographic scope: **ALB, DZA, AND, AIA, ARG, AUT, AZE, BHR, and 85 others**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Demographics and population |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 196,246 |
| **Columns** | 18 (13 numeric, 4 categorical, 1 datetime) |
| **Train split** | 156,996 rows |
| **Test split** | 39,249 rows |
| **Geographic scope** | ALB, DZA, AND, AIA, ARG, AUT, AZE, BHR, and 85 others |
| **Publisher** | HDX |
| **HDX last updated** | 2026-02-01 |

---

## Variables

**Geographic** — `location` (World, High income, Europe), `iso_code` (OWID_WRL, OWID_HIC, OWID_EUR), `people_fully_vaccinated` (range 1.0–5177942957.0), `daily_vaccinations_raw` (range 0.0–49673198.0), `daily_vaccinations` (range 0.0–43691814.0) and 4 others.

**Temporal** — `date`.

**Outcome / Measurement** — `total_vaccinations` (range 0.0–13578774356.0), `total_boosters` (range 1.0–2817381093.0), `total_vaccinations_per_hundred` (range 0.0–410.23), `total_boosters_per_hundred` (range 0.0–150.47).

**Identifier / Metadata** — `esa_source` (HDX), `esa_processed` (2026-04-14).

**Other** — `people_vaccinated` (range 0.0–5631263739.0), `people_vaccinated_per_hundred` (range 0.0–129.07).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-covid-19-vaccinations")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `location` | object | 0.0% | World, High income, Europe |
| `iso_code` | object | 0.0% | OWID_WRL, OWID_HIC, OWID_EUR |
| `date` | datetime64[ns] | 0.0% | |
| `total_vaccinations` | float64 | 56.5% | 0.0 – 13578774356.0 (mean 561697983.4254) |
| `people_vaccinated` | float64 | 58.7% | 0.0 – 5631263739.0 (mean 248706410.7401) |
| `people_fully_vaccinated` | float64 | 60.2% | 1.0 – 5177942957.0 (mean 228663910.0734) |
| `total_boosters` | float64 | 72.7% | 1.0 – 2817381093.0 (mean 150581058.9016) |
| `daily_vaccinations_raw` | float64 | 63.8% | 0.0 – 49673198.0 (mean 739864.0267) |
| `daily_vaccinations` | float64 | 0.6% | 0.0 – 43691814.0 (mean 283875.8151) |
| `total_vaccinations_per_hundred` | float64 | 56.5% | 0.0 – 410.23 (mean 124.2796) |
| `people_vaccinated_per_hundred` | float64 | 58.7% | 0.0 – 129.07 (mean 53.5014) |
| `people_fully_vaccinated_per_hundred` | float64 | 60.2% | 0.0 – 126.89 (mean 48.6802) |
| `total_boosters_per_hundred` | float64 | 72.7% | 0.0 – 150.47 (mean 36.3015) |
| `daily_vaccinations_per_million` | float64 | 0.6% | 0.0 – 117113.0 (mean 1851.4776) |
| `daily_people_vaccinated` | float64 | 2.1% | 0.0 – 21071266.0 (mean 106070.6989) |
| `daily_people_vaccinated_per_hundred` | float64 | 2.1% | 0.0 – 11.711 (mean 0.075) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-14 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `total_vaccinations` | 0.0 | 13578774356.0 | 561697983.4254 | 14394348.0 |
| `people_vaccinated` | 0.0 | 5631263739.0 | 248706410.7401 | 6901087.5 |
| `people_fully_vaccinated` | 1.0 | 5177942957.0 | 228663910.0734 | 6191345.0 |
| `total_boosters` | 1.0 | 2817381093.0 | 150581058.9016 | 5765440.0 |
| `daily_vaccinations_raw` | 0.0 | 49673198.0 | 739864.0267 | 20531.0 |
| `daily_vaccinations` | 0.0 | 43691814.0 | 283875.8151 | 3871.0 |
| `total_vaccinations_per_hundred` | 0.0 | 410.23 | 124.2796 | 130.55 |
| `people_vaccinated_per_hundred` | 0.0 | 129.07 | 53.5014 | 64.3 |
| `people_fully_vaccinated_per_hundred` | 0.0 | 126.89 | 48.6802 | 57.92 |
| `total_boosters_per_hundred` | 0.0 | 150.47 | 36.3015 | 35.905 |
| `daily_vaccinations_per_million` | 0.0 | 117113.0 | 1851.4776 | 605.0 |
| `daily_people_vaccinated` | 0.0 | 21071266.0 | 106070.6989 | 771.0 |
| `daily_people_vaccinated_per_hundred` | 0.0 | 11.711 | 0.075 | 0.014 |

---

## 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 HDX and has not been independently validated by ESA.
- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
- The following columns have >20% missing values and should be treated with caution in modelling: `total_vaccinations`, `people_vaccinated`, `people_fully_vaccinated`, `total_boosters`, `daily_vaccinations_raw`, `total_vaccinations_per_hundred`, `people_vaccinated_per_hundred`, `people_fully_vaccinated_per_hundred`....
- This dataset spans 93 countries; geographic and methodological inconsistencies across national boundaries may affect cross-country comparability.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/covid-19-vaccinations) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_covid_19_vaccinations,
title = {Coronavirus (COVID-19) Vaccinations},
author = {HDX},
year = {2026},
url = {https://data.humdata.org/dataset/covid-19-vaccinations},
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.*