electricsheepafrica/africa-conflict-zambia

---
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
- other
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- conflict-violence
- hxl
- zmb
pretty_name: "Zambia - Data on Conflict Events"
dataset_info:
splits:
- name: train
num_examples: 30
- name: test
num_examples: 7
---

# Zambia - Data on Conflict Events

**Publisher:** HDX · **Source:** [HDX](https://data.humdata.org/dataset/ucdp-data-for-zambia) · **License:** `cc-by-igo` · **Updated:** 2026-04-03

---

## Abstract

This dataset is UCDP's most disaggregated dataset, covering individual events of organized violence (phenomena of lethal violence occurring at a given time and place). These events are sufficiently fine-grained to be geo-coded down to the level of individual villages, with temporal durations disaggregated to single, individual days.
Sundberg, Ralph, and Erik Melander, 2013, “Introducing the UCDP Georeferenced Event Dataset”, Journal of Peace Research, vol.50, no.4, 523-532
Högbladh Stina, 2019, “UCDP GED Codebook version 19.1”, Department of Peace and Conflict Research, Uppsala University

Each row in this dataset represents first-level administrative unit observations. Temporal coverage is indicated by the `source_date`, `date_start` column(s). Geographic scope: **ZMB**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Conflict and security |
| **Unit of observation** | First-level administrative unit observations |
| **Rows (total)** | 38 |
| **Columns** | 50 (26 numeric, 20 categorical, 3 datetime) |
| **Train split** | 30 rows |
| **Test split** | 7 rows |
| **Geographic scope** | ZMB |
| **Publisher** | HDX |
| **HDX last updated** | 2026-04-03 |

---

## Variables

**Geographic** — `year` (range 1989.0–2001.0), `active_year`, `type_of_violence` (range 3.0–3.0), `dyad_dset_id` (range 89.0–567.0), `dyad_new_id` (range 934.0–1045.0) and 9 others.

**Temporal** — `source_date`, `date_prec` (range 1.0–4.0), `date_start`, `date_end`.

**Outcome / Measurement** — `number_of_sources` (range -1.0–2.0), `deaths_a` (range 0.0–0.0), `deaths_b`, `deaths_civilians`, `deaths_unknown`.

**Identifier / Metadata** — `id` (range 13183.0–435636.0), `relid` (DRC-1993-3-490-6, MZM-1990-3-1029-0, MZM-1989-3-1029-17), `code_status` (Clear), `conflict_dset_id` (range 89.0–567.0), `conflict_new_id` (range 467.0–578.0) and 14 others.

**Other** — `where_prec` (range 1.0–6.0), `where_description`, `adm_1`, `adm_2`, `geom_wkt` and 3 others.

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-conflict-zambia")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `id` | int64 | 0.0% | 13183.0 – 435636.0 (mean 303373.2632) |
| `relid` | object | 0.0% | DRC-1993-3-490-6, MZM-1990-3-1029-0, MZM-1989-3-1029-17 |
| `year` | int64 | 0.0% | 1989.0 – 2001.0 (mean 1990.2632) |
| `active_year` | bool | 0.0% | |
| `code_status` | object | 0.0% | Clear |
| `type_of_violence` | int64 | 0.0% | 3.0 – 3.0 (mean 3.0) |
| `conflict_dset_id` | int64 | 0.0% | 89.0 – 567.0 (mean 468.0526) |
| `conflict_new_id` | int64 | 0.0% | 467.0 – 578.0 (mean 555.3421) |
| `conflict_name` | object | 0.0% | Renamo - Civilians, Government of Angola - Civilians, Government of DR Congo (Zaire) - Civilians |
| `dyad_dset_id` | int64 | 0.0% | 89.0 – 567.0 (mean 468.0526) |
| `dyad_new_id` | int64 | 0.0% | 934.0 – 1045.0 (mean 1022.3421) |
| `dyad_name` | object | 0.0% | Renamo - Civilians, Government of Angola - Civilians, Government of DR Congo (Zaire) - Civilians |
| `side_a_dset_id` | int64 | 0.0% | 89.0 – 567.0 (mean 468.0526) |
| `side_a_new_id` | int64 | 0.0% | 89.0 – 567.0 (mean 468.0526) |
| `side_a` | object | 0.0% | Renamo, Government of Angola, Government of DR Congo (Zaire) |
| `side_b_dset_id` | int64 | 0.0% | 9999.0 – 9999.0 (mean 9999.0) |
| `side_b_new_id` | int64 | 0.0% | 1.0 – 1.0 (mean 1.0) |
| `side_b` | object | 0.0% | Civilians |
| `number_of_sources` | int64 | 0.0% | -1.0 – 2.0 (mean 0.9737) |
| `source_article` | object | 0.0% | "Mozambique history,1989-10-31,RENAMO incursions against Zambia in Eastern province from 4 June to 5 october 1989", "Mozambique history,1989-03-31,MNR (RENAMO) ACTIVITIES AGAINST ZAMBIA IN EASTERN PROVINCE", "Mozambique history,1989-11-30,MNR (RENAMO) activities against Zambia for the months of October - November 1989" |
| `source_office` | object | 5.3% | Mozambique history, Reuters News, Reuters News;Mozambique history |
| `source_date` | datetime64[ns] | 13.2% | |
| `source_headline` | object | 5.3% | RENAMO incursions against Zambia in Eastern province from 4 June to 5 october 1989, MNR (RENAMO) ACTIVITIES AGAINST ZAMBIA IN EASTERN PROVINCE, MNR (RENAMO) activities against Zambia for the months of October - November 1989 |
| `source_original` | object | 0.0% | Zambian Intelligence Report, Zambia Intelligence Report, Sec of State for Defense and Security |
| `where_prec` | int64 | 0.0% | 1.0 – 6.0 (mean 2.1842) |
| `where_coordinates` | object | 0.0% | |
| `where_description` | object | 0.0% | |
| `adm_1` | object | 2.6% | |
| `adm_2` | object | 5.3% | |
| `latitude` | float64 | 0.0% | -16.3235 – 14.2572 (mean -13.5926) |
| `longitude` | float64 | 0.0% | 22.1058 – 32.6422 (mean 30.6764) |
| `geom_wkt` | object | 0.0% | |
| `priogrid_gid` | int64 | 0.0% | 106245.0 – 150185.0 (mean 110070.3947) |
| `country` | object | 0.0% | |
| `iso3` | object | 0.0% | |
| `country_id` | int64 | 0.0% | 551.0 – 551.0 (mean 551.0) |
| `region` | object | 0.0% | |
| `event_clarity` | int64 | 0.0% | 1.0 – 2.0 (mean 1.0263) |
| `date_prec` | int64 | 0.0% | 1.0 – 4.0 (mean 1.2368) |
| `date_start` | datetime64[ns] | 0.0% | |
| `date_end` | datetime64[ns] | 0.0% | |
| `deaths_a` | int64 | 0.0% | 0.0 – 0.0 (mean 0.0) |
| `deaths_b` | int64 | 0.0% | |
| `deaths_civilians` | int64 | 0.0% | |
| `deaths_unknown` | int64 | 0.0% | |
| `best` | int64 | 0.0% | |
| `high` | int64 | 0.0% | |
| `low` | int64 | 0.0% | |
| `esa_source` | object | 0.0% | |
| `esa_processed` | object | 0.0% | |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `id` | 13183.0 | 435636.0 | 303373.2632 | 435591.5 |
| `year` | 1989.0 | 2001.0 | 1990.2632 | 1989.0 |
| `type_of_violence` | 3.0 | 3.0 | 3.0 | 3.0 |
| `conflict_dset_id` | 89.0 | 567.0 | 468.0526 | 498.0 |
| `conflict_new_id` | 467.0 | 578.0 | 555.3421 | 562.0 |
| `dyad_dset_id` | 89.0 | 567.0 | 468.0526 | 498.0 |
| `dyad_new_id` | 934.0 | 1045.0 | 1022.3421 | 1029.0 |
| `side_a_dset_id` | 89.0 | 567.0 | 468.0526 | 498.0 |
| `side_a_new_id` | 89.0 | 567.0 | 468.0526 | 498.0 |
| `side_b_dset_id` | 9999.0 | 9999.0 | 9999.0 | 9999.0 |
| `side_b_new_id` | 1.0 | 1.0 | 1.0 | 1.0 |
| `number_of_sources` | -1.0 | 2.0 | 0.9737 | 1.0 |
| `where_prec` | 1.0 | 6.0 | 2.1842 | 2.0 |
| `latitude` | -16.3235 | 14.2572 | -13.5926 | -14.2762 |
| `longitude` | 22.1058 | 32.6422 | 30.6764 | 31.4093 |

---

## 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) with >80% missing values were removed: `gwnoa`, `gwnob`. 3 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.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/ucdp-data-for-zambia) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_conflict_zambia,
title = {Zambia - Data on Conflict Events},
author = {HDX},
year = {2026},
url = {https://data.humdata.org/dataset/ucdp-data-for-zambia},
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.*