README.md

---
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-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- indicators
- poverty
- tza
pretty_name: "Tanzania - Poverty"
dataset_info:
  splits:
    - name: train
      num_examples: 79
    - name: test
      num_examples: 19
---

# Tanzania - Poverty

**Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-poverty-indicators-for-tanzania) · **License:** `cc-by` · **Updated:** 2026-03-27

---

## Abstract

Contains data from the World Bank's [data portal](http://data.worldbank.org/). There is also a [consolidated country dataset](https://data.humdata.org/dataset/world-bank-combined-indicators-for-tanzania) on HDX.

For countries with an active poverty monitoring program, the World Bank—in collaboration with national institutions, other development agencies, and civil society—regularly conducts analytical work to assess the extent and causes of poverty and inequality, examine the impact of growth and public policy, and review household survey data and measurement methods.  Data here includes poverty and inequality measures generated from analytical reports, from national poverty monitoring programs, and from the World Bank’s Development Research Group which has been producing internationally comparable and global poverty estimates and lines since 1990.

Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-03-27. Geographic scope: **TZA**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Poverty and economic vulnerability |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 99 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 79 rows |
| **Test split** | 19 rows |
| **Geographic scope** | TZA |
| **Publisher** | World Bank Group |
| **HDX last updated** | 2026-03-27 |

---

## Variables

**Geographic** — `country_name` (Tanzania), `country_iso3` (TZA), `year` (range 1991.0–2022.0).

**Outcome / Measurement** — `value` (range -0.15–99.4).

**Identifier / Metadata** — `indicator_name` (Population living in slums (% of urban population), Poverty headcount ratio at national poverty lines (% of population), Poverty headcount ratio at $3.00 a day (2021 PPP) (% of population)), `indicator_code` (EN.POP.SLUM.UR.ZS, SI.POV.NAHC, SI.POV.DDAY), `esa_source` (HDX), `esa_processed` (2026-04-12).

---

## Quick Start

```python
from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-world-bank-poverty-indicators-for-tanzania")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `country_name` | object | 0.0% | Tanzania |
| `country_iso3` | object | 0.0% | TZA |
| `year` | int64 | 0.0% | 1991.0 – 2022.0 (mean 2006.8182) |
| `indicator_name` | object | 0.0% | Population living in slums (% of urban population), Poverty headcount ratio at national poverty lines (% of population), Poverty headcount ratio at $3.00 a day (2021 PPP) (% of population) |
| `indicator_code` | object | 0.0% | EN.POP.SLUM.UR.ZS, SI.POV.NAHC, SI.POV.DDAY |
| `value` | float64 | 0.0% | -0.15 – 99.4 (mean 37.5232) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-12 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1991.0 | 2022.0 | 2006.8182 | 2007.0 |
| `value` | -0.15 | 99.4 | 37.5232 | 33.1 |

---

## 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 World Bank Group 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/world-bank-poverty-indicators-for-tanzania) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_world_bank_poverty_indicators_for_tanzania,
  title     = {Tanzania - Poverty},
  author    = {World Bank Group},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/world-bank-poverty-indicators-for-tanzania},
  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.*