---
license: other
language:
- en
task_categories:
- tabular-classification
- tabular-regression
multilinguality: multilingual
size_categories:
- 100K<n<1M
tags:
- "tabular"
- "africa"
- "open-data"
- "official-statistics"
- "south-africa"
- "national-treasury-south-africa"
- "economics"
- "balance-sheet"
- "bsheet"
- "bsheet-facts-v1"
- "2016"
- "9104491-bytes"
- "ce5cc2b612618cd5f1dcf23be4617ac2000c2c8d"
- "municipal-money"
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-00000-of-00001.parquet
pretty_name: "Balance Sheet 2016 | Africa (National Treasury, South Africa)"
---

# Balance Sheet 2016 | Africa (National Treasury, South Africa)

**178,391 rows** - **1 Africa country/area** - **2016-2023** - **source table** - *Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*

![rows](https://img.shields.io/badge/rows-178391-blue)
![countries](https://img.shields.io/badge/countries-1-green)
![period](https://img.shields.io/badge/period-2016--2023-orange)
![indicators](https://img.shields.io/badge/indicators-0-purple)
![license](https://img.shields.io/badge/license-other-lightgrey)

## TL;DR

This dataset contains **178,391 rows** from **National Treasury, South Africa**, covering **Balance Sheet 2016**. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

## What This Dataset Measures

Economic datasets help analysts examine production, prices, public finance, trade flows, market conditions, and macroeconomic change.

Source-provided context: bsheet_facts_v1 bulk CSV group 2016.

## How To Read This Dataset

- **One row means:** one source record from the original tabular resource, with Electric Sheep Africa provenance columns added where available.
- **Primary geography column:** `country_iso3`.
- **Best time column:** `not detected`.
- **Time coverage basis:** source metadata.
- **Recommended join keys:** `country_iso3` where available plus source-specific keys.

## Coverage

| Dimension | Value |
|---|---:|
| Rows | 178,391 |
| Countries/areas | 1 |
| First period | 2016 |
| Last period | 2023 |
| Indicators | 0 |
| Columns | 23 |
| Source format | CSV |

## Geographic Coverage

Top areas shown below, sorted by row count when available:

| Area | Rows | First year | Last year | Name |
|------|-----:|-----------:|----------:|------|
| `ZAF` | 178,391 | 2016 | 2023 | `South Africa` |

## Indicators, Variables, Or Resource Contents

- This repo preserves one source tabular resource with its usable columns kept together.

## Schema

| Column | Type | Description | Example |
|--------|------|-------------|---------|
| `source_record_id` | `int64` | Stable row identifier assigned during Electric Sheep Africa engineering. | `0` |
| `country_iso3` | `dictionary<values=string, indices=int8, ordered=0>` | ISO3 country or area code. | `ZAF` |
| `country_name` | `dictionary<values=string, indices=int8, ordered=0>` | Country or area name. | `South Africa` |
| `demarcation_code` | `string` | Source column from the original resource. | `EC103` |
| `period_code` | `string` | Source column from the original resource. | `2016M07` |
| `item_code` | `int64` | Source column from the original resource. | `1404` |
| `amount` | `double` | Source column from the original resource. | `0.0` |
| `id` | `int64` | Source column from the original resource. | `3190600` |
| `financial_year` | `int64` | Source column from the original resource. | `2016` |
| `period_length` | `string` | Source column from the original resource. | `month` |
| `financial_period` | `int64` | Source column from the original resource. | `7` |
| `amount_type_code` | `string` | Source column from the original resource. | `ACT` |
| `source_period_start_year` | `int64` | Start year inferred from source metadata. | `2016` |
| `source_period_end_year` | `int64` | End year inferred from source metadata. | `2023` |
| `source_period_label` | `dictionary<values=string, indices=int8, ordered=0>` | Source column from the original resource. | `2016-2023` |
| `source_provider` | `dictionary<values=string, indices=int8, ordered=0>` | Publishing organization. | `National Treasury, South Africa` |
| `source_dataset` | `dictionary<values=string, indices=int8, ordered=0>` | Source dataset or package title. | `Balance Sheet - 2016` |
| `source_resource` | `dictionary<values=string, indices=int8, ordered=0>` | Source resource title, table name, or file name. | `Balance Sheet - 2016` |
| `source_package_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source package identifier. | `balance-sheet-2016-municipal-money-511c7e01c0793c` |
| `source_resource_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source resource identifier. | `municipal-money-511c7e01c0793c` |
| `source_url` | `dictionary<values=string, indices=int8, ordered=0>` | Original source URL or download URL. | `https://munimoney-media.s3.eu-west-1.amazonaws.com/munimoney-media/me...` |
| `license_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source license identifier. | `other-open` |
| `retrieved_at` | `dictionary<values=string, indices=int8, ordered=0>` | UTC source retrieval timestamp from the Electric Sheep Africa pipeline. | `2026-07-22T19:07:15Z` |

## Usage

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-south-africa-balance-sheet-2016-49e99f9c")
df = ds["train"].to_pandas()
print(df.head())
```

### Inspect Columns

```python
print(df.info())
print(df.head())
```

### Filter By Geography

```python
if "country_iso3" in df.columns:
    sample = df[df["country_iso3"] == "ZAF"]
```

### Time-Series Pattern

```python
if "value" in df.columns and "year" in df.columns:
    trend = df.sort_values("year")
```

### Pivot For Analysis

```python
if {"indicator_id", "year", "value"}.issubset(df.columns):
    matrix = df.pivot_table(index="year", columns="indicator_id", values="value")
    print(matrix.tail())
```

## Data Quality Notes

- No canonical year/date column was detected in the packaged table; use source metadata and domain context for temporal interpretation.
- Missing values are preserved rather than silently imputed.
- Column names are standardized for machine use; source meanings are preserved where known.
- Always confirm source methodology, units, and collection definitions before policy, production, or redistribution-sensitive use.

## Source And Provenance

- **Source:** [National Treasury, South Africa](https://municipaldata.treasury.gov.za/docs#cube-bsheet)
- **Publisher:** National Treasury, South Africa
- **Portal:** [https://municipaldata.treasury.gov.za](https://municipaldata.treasury.gov.za)
- **Resource:** [Balance Sheet - 2016](https://munimoney-media.s3.eu-west-1.amazonaws.com/munimoney-media/media/bulk_downloads/bsheet_facts_v1/bsheet_facts_v1_2016__2023-09-01.csv)
- **License:** other-open
- **Retrieved/generated:** `2026-07-22T19:15:50Z`
- **Hugging Face repo:** [electricsheepafrica/africa-south-africa-balance-sheet-2016-49e99f9c](https://huggingface.co/datasets/electricsheepafrica/africa-south-africa-balance-sheet-2016-49e99f9c)

## Transformations Applied

- Converted the source table to Parquet for efficient analytics and ML workflows.
- Added or preserved source provenance columns where available.
- Standardized README metadata, dataset loading configuration, schema documentation, and citation format.
- Preserved source-reported values without analytical imputation.

## Suggested Analyses

- Build time-series dashboards
- Compare economic indicators
- Join with population or sector data
- Check missingness before modeling
- Use `country_iso3` as the safest geography join key when present

## Citation

```bibtex
@misc{electric_sheep_africa_africa_south_africa_balance_sheet_2016_49e99f9c_2023,
  title        = {Balance Sheet 2016 | Africa (National Treasury, South Africa)},
  author       = {National Treasury, South Africa},
  year         = {2023},
  url          = {https://municipaldata.treasury.gov.za/docs#cube-bsheet},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-south-africa-balance-sheet-2016-49e99f9c}}
}
```

## License

Released under other-open.

Original data is published by National Treasury, South Africa. Electric Sheep Africa
engineering standardizes the data for discovery, loading, and analysis on
Hugging Face. Cite both the original source and this ML-ready dataset when used.

## About Electric Sheep Africa

Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.

---

Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://municipaldata.treasury.gov.za/docs#cube-bsheet