electricsheepafrica/africa-south-africa-income-and-expenditure-2020-47301f2e

Income and Expenditure 2020 | Africa (National Treasury, South Africa)

16,080 rows - 1 Africa country/area - 2020-2023 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 16,080 rows from National Treasury, South Africa, covering Income and Expenditure 2020. 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: incexp_facts_v1 bulk CSV group 2020.

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	16,080
Countries/areas	1
First period	2020
Last period	2023
Indicators	0
Columns	24
Source format	CSV

Geographic Coverage

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

Area	Rows	First year	Last year	Name
ZAF	16,080	2020	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.	EC142
period_code	string	Source column from the original resource.	2020IBY1
function_code	int64	Source column from the original resource.	101
item_code	int64	Source column from the original resource.	100
amount	double	Source column from the original resource.	0.0
id	int64	Source column from the original resource.	132338860
financial_year	int64	Source column from the original resource.	2020
period_length	string	Source column from the original resource.	year
financial_period	int64	Source column from the original resource.	2020
amount_type_code	string	Source column from the original resource.	IBY1
source_period_start_year	int64	Start year inferred from source metadata.	2020
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.	2020-2023
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.	Income and Expenditure - 2020
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	Income and Expenditure - 2020
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	income-and-expenditure-2020-municipal-money-0e2a7a7b1d7490
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	municipal-money-0e2a7a7b1d7490
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.	2026-07-22T20:13:23Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-south-africa-income-and-expenditure-2020-47301f2e")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns

print(df.info())
print(df.head())

Filter By Geography

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

Time-Series Pattern

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

Pivot For Analysis

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
• Publisher: National Treasury, South Africa
• Portal: https://municipaldata.treasury.gov.za
• Resource: Income and Expenditure - 2020
• License: other-open
• Retrieved/generated: 2026-07-22T20:37:52Z
• Hugging Face repo: electricsheepafrica/africa-south-africa-income-and-expenditure-2020-47301f2e

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

@misc{electric_sheep_africa_africa_south_africa_income_and_expenditure_2020_47301f2e_2023,
  title        = {Income and Expenditure 2020 | Africa (National Treasury, South Africa)},
  author       = {National Treasury, South Africa},
  year         = {2023},
  url          = {https://municipaldata.treasury.gov.za/docs#cube-incexp},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-south-africa-income-and-expenditure-2020-47301f2e}}
}

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.

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