electricsheepafrica/africa-tanzania-national-bureau-of-statistics-63b37a26

National Bureau of Statistics | Africa (National Bureau of Statistics, Tanzania)

1,441 rows - 1 Africa country/area - 2012-2020 - 48 indicators - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 1,441 rows from National Bureau of Statistics, Tanzania, covering National Bureau of Statistics. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Official statistics datasets help analysts inspect public data as published by governments, national statistical systems, and regional data portals.

Source-provided context: 25 June, 2021 Summary QNA Second Quarter 2021.zip

How To Read This Dataset

• One row means: one indicator observation for one geography, time period, and optional source dimensions.
• Primary geography column: country_iso3.
• Best time column: year.
• Time coverage basis: year.
• Recommended join keys: country_iso3, year, indicator_id.

Coverage

Dimension	Value
Rows	1,441
Countries/areas	1
First period	2012
Last period	2020
Indicators	48
Columns	19
Source format	ZIP

Geographic Coverage

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

Area	Rows	First year	Last year	Name
TZA	1,441	2012	2020	Tanzania

Indicators, Variables, Or Resource Contents

• national-bureau-of-statistics-mwaka-4cd0fd60 - National Bureau of Statistics - mwaka(source_units_unspecified)
• national-bureau-of-statistics-robo-mwaka-f05c0697 - National Bureau of Statistics - robo mwaka(source_units_unspecified)
• national-bureau-of-statistics-kilimo-c5518fa5 - National Bureau of Statistics - kilimo(source_units_unspecified)
• national-bureau-of-statistics-madini-na-mawe-617e4fbd - National Bureau of Statistics - madini na mawe(source_units_unspecified)
• national-bureau-of-statistics-viwanda-bf4c0cd7 - National Bureau of Statistics - viwanda(source_units_unspecified)
• national-bureau-of-statistics-umeme-d7451d61 - National Bureau of Statistics - umeme(source_units_unspecified)
• national-bureau-of-statistics-maji-safi-na-maji-taka-1c3bc567 - National Bureau of Statistics - maji safi na maji taka(source_units_unspecified)
• national-bureau-of-statistics-ujenzi-4cdb127b - National Bureau of Statistics - ujenzi(source_units_unspecified)
• national-bureau-of-statistics-biashara-na-matengenezo-2893b4d8 - National Bureau of Statistics - biashara na matengenezo(source_units_unspecified)
• national-bureau-of-statistics-malazi-na-huduma-ya-chakula-034ad3ce - National Bureau of Statistics - malazi na huduma ya chakula(source_units_unspecified)
• national-bureau-of-statistics-uchukuzi-na-uhifadhi-mizigo-d5727b17 - National Bureau of Statistics - uchukuzi na uhifadhi mizigo(source_units_unspecified)
• national-bureau-of-statistics-habari-na-mawasiliano-aba15602 - National Bureau of Statistics - habari na mawasiliano(source_units_unspecified)
• national-bureau-of-statistics-fedha-na-bima-35114db0 - National Bureau of Statistics - fedha na bima(source_units_unspecified)
• national-bureau-of-statistics-robo-mwaka-2-fd237f80 - National Bureau of Statistics - robo mwaka 2(source_units_unspecified)
• national-bureau-of-statistics-utawala-na-ulinzi-35d8f0e6 - National Bureau of Statistics - utawala na ulinzi(source_units_unspecified)
• national-bureau-of-statistics-sughuli-za-kitaaluma-sayansi-na-ufundi-acbb5f28 - National Bureau of Statistics - sughuli za kitaaluma sayansi na ufundi(source_units_unspecified)
• national-bureau-of-statistics-huduma-zinazohusiana-na-utawala-e9d92a1f - National Bureau of Statistics - huduma zinazohusiana na utawala(source_units_unspecified)
• national-bureau-of-statistics-upangishaji-majengo-5387e2cf - National Bureau of Statistics - upangishaji majengo(source_units_unspecified)
• national-bureau-of-statistics-elimu-4a60ea7d - National Bureau of Statistics - elimu(source_units_unspecified)
• national-bureau-of-statistics-afya-na-huduma-za-jami-3d441b71 - National Bureau of Statistics - afya na huduma za jami(source_units_unspecified)
• ... 28 more indicators

Schema

Column	Type	Description	Example
indicator_id	string	Stable source or Electric Sheep Africa indicator identifier.	national-bureau-of-statistics-mwaka-4cd0fd60
indicator_name	string	Human-readable indicator name.	National Bureau of Statistics - mwaka
country_iso3	string	ISO3 country or area code.	TZA
source_sheet	string	Source column from the original resource.	Summary_QNA_Second _Quarter_2021_17102021.xls::Table KP Tshs
country_name	string	Country or area name.	Tanzania
year	int64	Observation year.	2012
value	double	Numeric observation value.	2012.0
unit	string	Measurement unit, when supplied by the source.	source_units_unspecified
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	string	Source column from the original resource.	2021
source_provider	string	Publishing organization.	National Bureau of Statistics, Tanzania
source_dataset	string	Source dataset or package title.	National Bureau of Statistics
source_resource	string	Source resource title, table name, or file name.	Summary QNA Second Quarter 2021.zip
source_package_id	string	Source package identifier.	gross-domestic-product-gdp
source_resource_id	string	Source resource identifier.	nbs-stat-356fca5878cbf7
source_url	string	Original source URL or download URL.	https://www.nbs.go.tz/uploads/statistics/documents/en-1705429386-Summ...
license_id	string	Source license identifier.	other-open
retrieved_at	string	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-07-21T20:19:26Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-tanzania-national-bureau-of-statistics-63b37a26")
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"] == "TZA"]

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: National Bureau of Statistics, Tanzania
• Publisher: National Bureau of Statistics, Tanzania
• Portal: https://www.nbs.go.tz
• Resource: [Summary QNA Second Quarter 2021.zip](https://www.nbs.go.tz/uploads/statistics/documents/en-1705429386-Summary_QNA_Second _Quarter_2021_17102021.zip)
• License: other-open
• Retrieved/generated: 2026-07-21T20:20:15Z
• Hugging Face repo: electricsheepafrica/africa-tanzania-national-bureau-of-statistics-63b37a26

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

• Profile the distribution of values
• Compare categories or geographies
• Join with complementary public datasets
• Build time-series views and period-over-period comparisons
• Pivot to geography x period or indicator x period matrices
• Check missingness before modeling
• Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_tanzania_national_bureau_of_statistics_63b37a26_2020,
  title        = {National Bureau of Statistics | Africa (National Bureau of Statistics, Tanzania)},
  author       = {National Bureau of Statistics, Tanzania},
  year         = {2020},
  url          = {https://www.nbs.go.tz/statistics/topic/gross-domestic-product-gdp},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-tanzania-national-bureau-of-statistics-63b37a26}}
}

License

Released under other-open.

Original data is published by National Bureau of Statistics, Tanzania. 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://www.nbs.go.tz/statistics/topic/gross-domestic-product-gdp