README.md

metadata

annotations_creators:
  - no-annotation
language_creators:
  - found
language:
  - en
license: cc-by-4.0
multilinguality:
  - monolingual
size_categories:
  - 10K<n<100K
source_datasets:
  - original
task_categories:
  - tabular-classification
  - tabular-regression
task_ids: []
tags:
  - africa
  - humanitarian
  - hdx
  - electric-sheep-africa
  - eastern-africa
  - trade
  - ssd
pretty_name: South Sudan Daily FEWS NET Cross Border Trade Data
dataset_info:
  splits:
    - name: train
      num_examples: 21709
    - name: test
      num_examples: 5427

South Sudan Daily FEWS NET Cross Border Trade Data

Publisher: FEWS NET · Source: HDX · License: cc-by · Updated: 2026-04-07

---

Abstract

South Sudan 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: SSD.

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

---

Dataset Characteristics

Domain	Humanitarian and development data
Unit of observation	First-level administrative unit observations
Rows (total)	27,137
Columns	38 (5 numeric, 31 categorical, 2 datetime)
Train split	21,709 rows
Test split	5,427 rows
Geographic scope	SSD
Publisher	FEWS NET
HDX last updated	2026-04-07

---

Variables

Geographic — reporting_country (South Sudan, Ethiopia, Sudan), reporting_country_code (SS, ET, SD), source_country_code (ET, SD, UG), destination_country_code (SS, SD, ET), flow_type and 8 others.

Temporal — start_date, period_date, value_one_month_ago (range 0.5–244536280.5), pct_change_from_one_month_ago (range -99.988–339609.1105).

Outcome / Measurement — value (range 0.0–978145122.0).

Identifier / Metadata — source (Ethiopia, Sudan, Uganda), indicator_name (TradeFlowQuantity), source_organization, source_document, dataseries_name and 4 others.

Other — border_point (Gambella, War War, Goc Machar), destination (South Sudan, Sudan, Ethiopia), cpcv2 (P23520AA, P23110AA, P21549AA), product (Refined sugar, Wheat Flour, Refined Vegetable Oil), collection_status and 6 others.

---

Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-daily-cross-border-trade-for-south-sudan-6824")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

---

Schema

Column	Type	Null %	Range / Sample Values
reporting_country	object	0.0%	South Sudan, Ethiopia, Sudan
reporting_country_code	object	0.0%	SS, ET, SD
border_point	object	0.0%	Gambella, War War, Goc Machar
source	object	0.0%	Ethiopia, Sudan, Uganda
source_country_code	object	0.0%	ET, SD, UG
destination	object	0.0%	South Sudan, Sudan, Ethiopia
destination_country_code	object	0.0%	SS, SD, ET
cpcv2	object	0.0%	P23520AA, P23110AA, P21549AA
product	object	0.0%	Refined sugar, Wheat Flour, Refined Vegetable Oil
indicator_name	object	0.0%	TradeFlowQuantity
start_date	datetime64[ns]	0.0%
period_date	datetime64[ns]	0.0%
value	float64	0.0%	0.0 – 978145122.0 (mean 1030589.5011)
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%	6544221.0 – 7402467.0 (mean 6681220.24)
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 – 10399759600.0 (mean 3119770.3643)
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	67.1%	0.5 – 244536280.5 (mean 763606.4849)
pct_change_from_one_month_ago	float64	67.1%	-99.988 – 339609.1105 (mean 612.9642)
collection_schedule	object	0.0%
data_usage_policy	object	0.0%
esa_source	object	0.0%
esa_processed	object	0.0%

---

Numeric Summary

Column	Min	Max	Mean	Median
value	0.0	978145122.0	1030589.5011	0.0
dataseries	6544221.0	7402467.0	6681220.24	6615877.0
common_unit_quantity	0.0	10399759600.0	3119770.3643	0.0
value_one_month_ago	0.5	244536280.5	763606.4849	394.6667
pct_change_from_one_month_ago	-99.988	339609.1105	612.9642	198.2516

---

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.

---

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.

---

Citation

@dataset{hdx_africa_daily_cross_border_trade_for_south_sudan_6824,
  title     = {South Sudan Daily FEWS NET Cross Border Trade Data},
  author    = {FEWS NET},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/daily_cross_border_trade_for_south_sudan_6824},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

---

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