electricsheepafrica/africa-chad-small-business-surveys-aggregated-data-e2ac8c3f

Small Business Surveys Aggregated Data | Africa (AI for Good at Meta)

6,483 rows - 1 Africa country/area - 2021 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 6,483 rows from AI for Good at Meta, covering Small Business Surveys Aggregated Data. 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: Weighted country level data for the Global State of Small Business Survey, fielded in July and August 2021.

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: year.
• Time coverage basis: year.
• Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

Dimension	Value
Rows	6,483
Countries/areas	1
First period	2021
Last period	2021
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
TCD	6,483	2021	2021	Chad

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	string	Stable row identifier assigned during Electric Sheep Africa engineering.	2397dac1-21f3-462d-9e84-d232ed4ed73b:0
country_iso3	dictionary<values=string, indices=int8, ordered=0>	ISO3 country or area code.	TCD
country_name	dictionary<values=string, indices=int8, ordered=0>	Country or area name.	Chad
year	int64	Observation year.	2021
unnamed_0	int64	Source column from the original resource.	1
variable	string	Source column from the original resource.	bus_cur_opn
value	string	Numeric observation value.	No
pop	string	Source column from the original resource.	overall_owner_manager
country_iso2	string	Source column from the original resource.	AR
mean_w	double	Source column from the original resource.	0.159750536
se_w	double	Source column from the original resource.	0.020619019
count	int64	Source column from the original resource.	90
question_n	int64	Source column from the original resource.	635
source_period_start_year	int64	Start year inferred from source metadata.	2021
source_period_end_year	int64	End year inferred from source metadata.	2021
source_period_label	dictionary<values=string, indices=int8, ordered=0>	Source column from the original resource.	2021
source_provider	dictionary<values=string, indices=int8, ordered=0>	Publishing organization.	AI for Good at Meta
source_dataset	dictionary<values=string, indices=int8, ordered=0>	Source dataset or package title.	Small Business Surveys - Aggregated Data
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	gsosb_2021julyaugust_data_aggregate_weighted.csv
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	8bd3d109-d33d-4349-90c4-464c9d7ccb66
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	2397dac1-21f3-462d-9e84-d232ed4ed73b
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.humdata.org/dataset/8bd3d109-d33d-4349-90c4-464c9d7ccb66...
license_id	dictionary<values=string, indices=int8, ordered=0>	Source license identifier.	cc-by
retrieved_at	dictionary<values=string, indices=int8, ordered=0>	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-08-10T22:51:43Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-chad-small-business-surveys-aggregated-data-e2ac8c3f")
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"] == "TCD"]

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

• Canonical time field: year.
• 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: AI for Good at Meta
• Publisher: AI for Good at Meta
• Portal: https://data.humdata.org
• Resource: gsosb_2021julyaugust_data_aggregate_weighted.csv
• License: CC BY 4.0
• Retrieved/generated: 2026-08-10T23:36:44Z
• Hugging Face repo: electricsheepafrica/africa-chad-small-business-surveys-aggregated-data-e2ac8c3f

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
• Build time-series views and period-over-period comparisons
• Check missingness before modeling
• Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_chad_small_business_surveys_aggregated_data_e2ac8c3f_2021,
  title        = {Small Business Surveys Aggregated Data | Africa (AI for Good at Meta)},
  author       = {AI for Good at Meta},
  year         = {2021},
  url          = {https://data.humdata.org/dataset/future-of-business-survey-aggregated-data},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-chad-small-business-surveys-aggregated-data-e2ac8c3f}}
}

License

Released under CC BY 4.0.

Original data is published by AI for Good at Meta. 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 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.humdata.org/dataset/future-of-business-survey-aggregated-data