electricsheepafrica/africa-ucdp-data-for-zimbabwe

---
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
- zwe
pretty_name: "Zimbabwe - Data on Conflict Events"
dataset_info:
splits:
- name: train
num_examples: 54
- name: test
num_examples: 13
---

# Zimbabwe - Data on Conflict Events

**Publisher:** HDX · **Source:** [HDX](https://data.humdata.org/dataset/ucdp-data-for-zimbabwe) · **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 `date_start`, `date_end` column(s). Geographic scope: **ZWE**.

*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)** | 68 |
| **Columns** | 48 (27 numeric, 18 categorical, 2 datetime) |
| **Train split** | 54 rows |
| **Test split** | 13 rows |
| **Geographic scope** | ZWE |
| **Publisher** | HDX |
| **HDX last updated** | 2026-04-03 |

---

## Variables

**Geographic** — `year` (range 1989.0–2020.0), `active_year`, `type_of_violence` (range 3.0–3.0), `dyad_dset_id` (range 101.0–498.0), `dyad_new_id` (range 943.0–1029.0) and 9 others.

**Temporal** — `date_prec` (range 1.0–5.0), `date_start`, `date_end`.

**Outcome / Measurement** — `number_of_sources` (range -1.0–3.0), `deaths_a` (range 0.0–0.0), `deaths_b`, `deaths_civilians`, `deaths_unknown`.

**Identifier / Metadata** — `id` (range 15245.0–435646.0), `relid` (ZIM-1995-3-552-2, ZIM-2008-3-552-46, ZIM-2011-3-552-1), `code_status` (Clear), `conflict_dset_id` (range 101.0–498.0), `conflict_new_id` (range 476.0–562.0) and 12 others.

**Other** — `where_prec` (range 1.0–6.0), `where_description` (Zimbabwe, Chiadzwa, a part of Marange, Harare city (near)), `adm_1`, `adm_2`, `geom_wkt` and 4 others.

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-ucdp-data-for-zimbabwe")
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% | 15245.0 – 435646.0 (mean 76156.7941) |
| `relid` | object | 0.0% | ZIM-1995-3-552-2, ZIM-2008-3-552-46, ZIM-2011-3-552-1 |
| `year` | int64 | 0.0% | 1989.0 – 2020.0 (mean 2007.3824) |
| `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% | 101.0 – 498.0 (mean 136.0294) |
| `conflict_new_id` | int64 | 0.0% | 476.0 – 562.0 (mean 483.5882) |
| `conflict_name` | object | 0.0% | Government of Zimbabwe (Rhodesia) - Civilians, Renamo - Civilians |
| `dyad_dset_id` | int64 | 0.0% | 101.0 – 498.0 (mean 136.0294) |
| `dyad_new_id` | int64 | 0.0% | 943.0 – 1029.0 (mean 950.5882) |
| `dyad_name` | object | 0.0% | Government of Zimbabwe (Rhodesia) - Civilians, Renamo - Civilians |
| `side_a_dset_id` | int64 | 0.0% | 101.0 – 498.0 (mean 136.0294) |
| `side_a_new_id` | int64 | 0.0% | 101.0 – 498.0 (mean 136.0294) |
| `side_a` | object | 0.0% | Government of Zimbabwe (Rhodesia), Renamo |
| `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 – 3.0 (mean -0.5147) |
| `source_article` | object | 0.0% | HRW 2009-06-26 "Diamonds in the rough" http://www.hrw.org/sites/default/files/reports/zimbabwe0609web.pdf, SPT 2008-05-21, "Punishing dissent, silencing citizens: The Zimbabwe elections 2008, Amnesty International2008-06-20 "Twelve bodies found in Zimbabwe - victims tortured to death |
| `source_original` | object | 11.8% | MDC, victim interviews, Zimbabwe Association of Doctors for Human Rights |
| `where_prec` | int64 | 0.0% | 1.0 – 6.0 (mean 2.0588) |
| `where_coordinates` | object | 0.0% | Harare town, Chiadzwa mining area, Zimbabwe (Rhodesia) |
| `where_description` | object | 0.0% | Zimbabwe, Chiadzwa, a part of Marange, Harare city (near) |
| `adm_1` | object | 11.8% | |
| `adm_2` | object | 19.1% | |
| `latitude` | float64 | 0.0% | -21.3584 – -16.4051 (mean -18.329) |
| `longitude` | float64 | 0.0% | 25.8307 – 32.8333 (mean 30.9633) |
| `geom_wkt` | object | 0.0% | |
| `priogrid_gid` | int64 | 0.0% | 99062.0 – 106263.0 (mean 103372.0735) |
| `country` | object | 0.0% | |
| `iso3` | object | 0.0% | |
| `country_id` | int64 | 0.0% | 552.0 – 552.0 (mean 552.0) |
| `region` | object | 0.0% | |
| `event_clarity` | int64 | 0.0% | 1.0 – 2.0 (mean 1.1324) |
| `date_prec` | int64 | 0.0% | 1.0 – 5.0 (mean 2.0147) |
| `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% | |
| `gwnoa` | float64 | 8.8% | |
| `esa_source` | object | 0.0% | |
| `esa_processed` | object | 0.0% | |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `id` | 15245.0 | 435646.0 | 76156.7941 | 28544.5 |
| `year` | 1989.0 | 2020.0 | 2007.3824 | 2008.0 |
| `type_of_violence` | 3.0 | 3.0 | 3.0 | 3.0 |
| `conflict_dset_id` | 101.0 | 498.0 | 136.0294 | 101.0 |
| `conflict_new_id` | 476.0 | 562.0 | 483.5882 | 476.0 |
| `dyad_dset_id` | 101.0 | 498.0 | 136.0294 | 101.0 |
| `dyad_new_id` | 943.0 | 1029.0 | 950.5882 | 943.0 |
| `side_a_dset_id` | 101.0 | 498.0 | 136.0294 | 101.0 |
| `side_a_new_id` | 101.0 | 498.0 | 136.0294 | 101.0 |
| `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 | 3.0 | -0.5147 | -1.0 |
| `where_prec` | 1.0 | 6.0 | 2.0588 | 1.0 |
| `latitude` | -21.3584 | -16.4051 | -18.329 | -17.9664 |
| `longitude` | 25.8307 | 32.8333 | 30.9633 | 31.056 |

---

## 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`. 4 column(s) with >80% missing values were removed: `source_office`, `source_date`, `source_headline`, `gwnob`. 2 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-zimbabwe) for the publisher's own methodology notes and caveats.

---

## Citation

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