electricsheepafrica/africa-monthly-cross-border-trade-for-south-africa-299

South Africa Monthly FEWS NET Cross Border Trade Data

Publisher: FEWS NET · Source: HDX · License: cc-by · Updated: 2026-04-01

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Abstract

South Africa Monthly cross border trade data collected by FEWS NET since 2005.

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: ZAF.

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)	2,111
Columns	42 (9 numeric, 31 categorical, 2 datetime)
Train split	1,688 rows
Test split	422 rows
Geographic scope	ZAF
Publisher	FEWS NET
HDX last updated	2026-04-01

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Variables

Geographic — reporting_country (Zimbabwe, South Africa, Malawi), reporting_country_code (ZW, ZA, MW), source_country_code (ZA, MW), destination_country_code (ZW, ZA), flow_type and 11 others.

Temporal — start_date, period_date, value_one_month_ago (range 0.1–1167.3), pct_change_from_one_month_ago (range -100.0–14683.44).

Outcome / Measurement — value (range 0.0–6663.0).

Identifier / Metadata — source (South Africa, Malawi), indicator_name (TradeFlowQuantity), source_organization, source_document, dataseries_name and 5 others.

Other — border_point (Beitbridge), destination (Zimbabwe, South Africa), cpcv2 (P23130AB, R01701AA, P23161AA), product (Roller Maize Meal, Beans (mixed), Rice (Milled)), collection_status and 6 others.

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-monthly-cross-border-trade-for-south-africa-299")
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%	Zimbabwe, South Africa, Malawi
reporting_country_code	object	0.0%	ZW, ZA, MW
border_point	object	36.7%	Beitbridge
source	object	0.0%	South Africa, Malawi
source_country_code	object	0.0%	ZA, MW
destination	object	0.0%	Zimbabwe, South Africa
destination_country_code	object	0.0%	ZW, ZA
cpcv2	object	0.0%	P23130AB, R01701AA, P23161AA
product	object	0.0%	Roller Maize Meal, Beans (mixed), Rice (Milled)
indicator_name	object	0.0%	TradeFlowQuantity
start_date	datetime64[ns]	0.0%
period_date	datetime64[ns]	0.0%
value	float64	0.0%	0.0 – 6663.0 (mean 302.7034)
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%	27995.0 – 6960794.0 (mean 4175612.612)
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 – 1167300.0 (mean 27349.9426)
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%
id	float64	76.0%	1159200.0 – 37980943.0 (mean 3754657.7233)
value_one_month_ago	float64	54.6%	0.1 – 1167.3 (mean 78.5218)
value_one_year_ago	float64	68.5%	0.1 – 1167.3 (mean 87.3247)
value_four_years_ago	float64	79.0%	0.1 – 1167.3 (mean 78.8364)
pct_change_from_one_month_ago	float64	54.6%	-100.0 – 14683.44 (mean 1166.5131)
pct_change_from_one_year_ago	float64	68.5%	-100.0 – 27692.8571 (mean 1292.8031)
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	6663.0	302.7034	0.7
dataseries	27995.0	6960794.0	4175612.612	6554429.0
common_unit_quantity	0.0	1167300.0	27349.9426	90.0
id	1159200.0	37980943.0	3754657.7233	1161806.5
value_one_month_ago	0.1	1167.3	78.5218	29.4105
value_one_year_ago	0.1	1167.3	87.3247	29.0
value_four_years_ago	0.1	1167.3	78.8364	16.025
pct_change_from_one_month_ago	-100.0	14683.44	1166.5131	831.404
pct_change_from_one_year_ago	-100.0	27692.8571	1292.8031	204.2789

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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. 6 column(s) with >80% missing values were removed: value_two_years_ago, value_three_years_ago, value_five_years_ago, two_year_average, five_year_average, pct_change_from_five_year_average. 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: border_point, id, value_one_month_ago, value_one_year_ago, value_four_years_ago, pct_change_from_one_month_ago, pct_change_from_one_year_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_monthly_cross_border_trade_for_south_africa_299,
  title     = {South Africa Monthly FEWS NET Cross Border Trade Data},
  author    = {FEWS NET},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/monthly_cross_border_trade_for_south_africa_299},
  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.