electricsheepafrica/africa-tanzania-national-bureau-of-statistics-bb9f2bb2

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

250 rows - 1 Africa country/area - 2021 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 250 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: 16 August, 2021 High Frequency Data July 2021.xls

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	250
Countries/areas	1
First period	2021
Last period	2021
Indicators	0
Columns	41
Source format	XLS

Geographic Coverage

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

Area	Rows	First year	Last year	Name
TZA	250	2021	2021	Tanzania

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.	nbs-stat-200ec485802a58:tourist-arrivals:0
country_iso3	string	ISO3 country or area code.	TZA
country_name	string	Country or area name.	Tanzania
source_sheet	string	Source column from the original resource.	Tourist Arrivals
year	double	Observation year.	2021.0
january	string	Source column from the original resource.	February
d_98710	double	Source column from the original resource.	88939.0
d_99815	double	Source column from the original resource.	91485.0
d_121280	double	Source column from the original resource.	101168.0
d_133795	double	Source column from the original resource.	107835.0
d_108027	double	Source column from the original resource.	122929.0
d_132684	double	Source column from the original resource.	137204.0
d_79116	double	Source column from the original resource.	79730.0
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.	High Frequency Data July 2021.xls
source_package_id	string	Source package identifier.	high-frequency-data
source_resource_id	string	Source resource identifier.	nbs-stat-200ec485802a58
source_url	string	Original source URL or download URL.	https://www.nbs.go.tz/uploads/statistics/documents/en-1705429386-High...
license_id	string	Source license identifier.	other-open
retrieved_at	string	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-07-21T20:05:22Z
quarter	string	Source column from the original resource.	``
2015	double	Source column from the original resource.	``
2016	double	Source column from the original resource.	``
2017	double	Source column from the original resource.	``
2018	double	Source column from the original resource.	``
2019	double	Source column from the original resource.	``
2020	double	Source column from the original resource.	``
2021	double	Source column from the original resource.	``
total	string	Source column from the original resource.	``
isic_rev_4	string	Source column from the original resource.	``
industry_activity	string	Source column from the original resource.	``
2019_2	double	Source column from the original resource.	``
2019_3	double	Source column from the original resource.	``
2019_4	double	Source column from the original resource.	``
2020_2	double	Source column from the original resource.	``
2020_3	double	Source column from the original resource.	``
2020_4	double	Source column from the original resource.	``

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-tanzania-national-bureau-of-statistics-bb9f2bb2")
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: High Frequency Data July 2021.xls
• License: other-open
• Retrieved/generated: 2026-07-21T20:15:36Z
• Hugging Face repo: electricsheepafrica/africa-tanzania-national-bureau-of-statistics-bb9f2bb2

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
• 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_bb9f2bb2_2021,
  title        = {National Bureau of Statistics | Africa (National Bureau of Statistics, Tanzania)},
  author       = {National Bureau of Statistics, Tanzania},
  year         = {2021},
  url          = {https://www.nbs.go.tz/statistics/topic/high-frequency-data},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-tanzania-national-bureau-of-statistics-bb9f2bb2}}
}

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.

---

Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://www.nbs.go.tz/statistics/topic/high-frequency-data