electricsheepafrica/africa-daily-cross-border-trade-for-united-republic-of-tanzania-6824

United Republic of Tanzania Daily FEWS NET Cross Border Trade Data

Publisher: FEWS NET · Source: HDX · License: cc-by · Updated: 2026-03-28

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Abstract

United Republic of Tanzania Daily cross border trade data collected by FEWS NET since 2010.

Each row in this dataset represents first-level administrative unit observations. Temporal coverage is indicated by the start_date, period_date column(s). Geographic scope: TZA.

Curated into ML-ready Parquet format by Electric Sheep Africa.

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Dataset Characteristics

Domain	Humanitarian and development data
Unit of observation	First-level administrative unit observations
Rows (total)	42,680
Columns	38 (5 numeric, 31 categorical, 2 datetime)
Train split	34,144 rows
Test split	8,536 rows
Geographic scope	TZA
Publisher	FEWS NET
HDX last updated	2026-03-28

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Variables

Geographic — reporting_country (Tanzania, United Republic of, Kenya, Malawi), reporting_country_code (TZ, KE, MW), source_country_code (TZ, KE, BI), destination_country_code (KE, BI, TZ), flow_type and 8 others.

Temporal — start_date, period_date, value_one_month_ago (range 0.2–83640500.0), pct_change_from_one_month_ago (range -100.0–40188788.8889).

Outcome / Measurement — value (range 0.0–334562000.0).

Identifier / Metadata — source (Tanzania, United Republic of, Kenya, Burundi), indicator_name (TradeFlowQuantity), source_organization, source_document, dataseries_name and 4 others.

Other — border_point (Kibande, Taveta, Manyovu), destination (Kenya, Burundi, Tanzania, United Republic of), cpcv2 (P23161AA, R01122AC, R01701AA), product (Rice (Milled), Maize Grain (White), Beans (mixed)), collection_status and 6 others.

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-daily-cross-border-trade-for-united-republic-of-tanzania-6824")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

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Schema

Column	Type	Null %	Range / Sample Values
reporting_country	object	0.0%	Tanzania, United Republic of, Kenya, Malawi
reporting_country_code	object	0.0%	TZ, KE, MW
border_point	object	4.8%	Kibande, Taveta, Manyovu
source	object	0.0%	Tanzania, United Republic of, Kenya, Burundi
source_country_code	object	0.0%	TZ, KE, BI
destination	object	0.0%	Kenya, Burundi, Tanzania, United Republic of
destination_country_code	object	0.0%	KE, BI, TZ
cpcv2	object	0.0%	P23161AA, R01122AC, R01701AA
product	object	0.0%	Rice (Milled), Maize Grain (White), Beans (mixed)
indicator_name	object	0.0%	TradeFlowQuantity
start_date	datetime64[ns]	0.0%
period_date	datetime64[ns]	0.0%
value	float64	0.0%	0.0 – 334562000.0 (mean 64106.3632)
flow_type	object	0.0%
trade_type	object	0.0%
collection_status	object	0.0%
source_organization	object	0.0%
source_document	object	0.0%
dataseries_name	object	0.0%
dataseries	int64	0.0%	27989.0 – 7051434.0 (mean 6290835.0721)
unit	object	0.0%
unit_type	object	0.0%
unit_name	object	0.0%
status	object	0.0%
common_unit	object	0.0%
common_unit_quantity	float64	0.0%	0.0 – 334562000.0 (mean 279649.6762)
reporting_country_geographic_group	object	0.0%
reporting_country_fewsnet_region	object	0.0%
source_geographic_group	object	0.0%
source_fewsnet_region	object	0.0%
destination_geographic_group	object	0.0%
destination_fewsnet_region	object	0.0%
value_one_month_ago	float64	76.7%	0.2 – 83640500.0 (mean 63837.2234)
pct_change_from_one_month_ago	float64	76.7%	-100.0 – 40188788.8889 (mean 5965.1906)
collection_schedule	object	0.0%
data_usage_policy	object	0.0%
esa_source	object	0.0%
esa_processed	object	0.0%

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Numeric Summary

Column	Min	Max	Mean	Median
value	0.0	334562000.0	64106.3632	0.0
dataseries	27989.0	7051434.0	6290835.0721	6606785.0
common_unit_quantity	0.0	334562000.0	279649.6762	0.0
value_one_month_ago	0.2	83640500.0	63837.2234	274.25
pct_change_from_one_month_ago	-100.0	40188788.8889	5965.1906	215.6977

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Curation

Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (N/A, null, none, -, unknown, no data, #N/A) were unified to NaN. 10 column(s) with >80% missing values were removed: id, value_one_year_ago, value_two_years_ago, value_three_years_ago, value_four_years_ago, value_five_years_ago.... 2 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.

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Limitations

• Data originates from FEWS NET and has not been independently validated by ESA.
• Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
• The following columns have >20% missing values and should be treated with caution in modelling: value_one_month_ago, pct_change_from_one_month_ago.
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{hdx_africa_daily_cross_border_trade_for_united_republic_of_tanzania_6824,
  title     = {United Republic of Tanzania Daily FEWS NET Cross Border Trade Data},
  author    = {FEWS NET},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/daily_cross_border_trade_for_united_republic_of_tanzania_6824},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

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Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.