electricsheepafrica/africa-rwanda-season-b-screening-agroforestry-5e74ad1f

Season B: Screening Agroforestry | Africa (Rwanda Data Sharing Platform - NISR)

33,192 rows - 1 Africa country - 2022-03-01-2022-06-30 - Repackaged by Electric Sheep Africa

TL;DR

This dataset packages one public table from Rwanda's official Data Sharing Platform as ML-ready Parquet. The source package is the provenance boundary: all usable source columns from this table stay together in this repo.

About the source

• Source: Season B: Screening Agroforestry
• Publisher: NISR
• Portal: Rwanda Data Sharing Platform
• Dataset ID: 79563b2c-d39b-49b4-9a4f-679f892ce9d9
• Schema: sas_2022
• Table: rwa_sas_seasonb_screening_agroforestry
• Sectors: National Statistics, Agriculture
• Source tags: Microdata
• Period: 2022-03-01-2022-06-30
• Resource: CSV package
• License: CC BY 4.0
• Packaging mode: tabular_resource

Source description

Summary: This table presents plot-level agroforestry screening data collected during Season B (March – June 2022) of the 2021/2022 Seasonal Agricultural Survey conducted by the National Institute of Statistics of Rwanda (NISR). Each record corresponds to an agricultural plot and captures information on land use and the presence of agroforestry practices during the reference season. The dataset includes plot identification, land use type, and whether agroforestry practices are present, as well as the types of trees grown on the plot, including species such as Calliandra, Leucaena, Grevillea, fruit trees, and other tree types. Geographic Coverage: National coverage across Rwanda, including all provinces and districts, covering both rural and peri-urban agricultural areas. Time Period: Season B of the 2021/2022 agricultural year (March – June 2022). Frequency: Seasonal (Season B of three agricultural seasons per year). Population/Units: Agricultural plots managed by small-scale and large-scale farming households in Rwanda. Key Variables: Plot identification, land use type, presence of agroforestry practices, tree species (Calliandra, Leucaena, Grevillea, fruit trees, and others). Purpose: To support analysis of agroforestry adoption, tree integration in farming systems, and sustainable land management practices. Data Quality Notes: Data are collected through structured field screening at plot level and reflect reported and observed conditions from sampled agricultural holdings. Estimates are based on sampled units and may vary across regions.

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
RWA	33,192	n/a	n/a	Rwanda

Indicators or Resource Contents

• This source package is published as a normalized tabular resource.

Schema

Column	Type	Description	Example
source_record_id	string	Stable row identifier assigned during Electric Sheep Africa packaging.	79563b2c-d39b-49b4-9a4f-679f892ce9d9:0
country_iso3	string	ISO3 country code.	RWA
country_name	string	Country name.	Rwanda
id	int64	Row ID	1
segment_id	float64	Segment identifier	12001.0
s1q1	int64	Numeric code (1–5) representing the administrative province of Rwanda where the survey respondent is located. 1 = Kigali City, 2 = Southern...	1
s1q2	int64	Numeric code (11–57) representing the respondent's district in Rwanda. The first digit corresponds to the province (1-5), and the second di...	12
s1q3	int64	Numeric code (0–40) representing the stratum classification of the surveyed area: 0 = NA, 10 = Hillside cropland, 20 = Marshland cropland,...	0
s1q4	float64	Numeric identifier representing the survey segment	0.0
s2q1	int64	Plot number	33
s2q4	float64	Plot size (m2)	1487.001220703125
s2q5_2	float64	Farmer ID	1.0
s2q6	int64	Plot land use: 96=Agricultural, 97=Pasture, 98=Fallow, 99=Non agricultural	99
s2q7	float64	Non agricultural Land Type: 1=Buildings, 2=Road or Path, 3=Forest or Bush, 4=Bare or Rocky soil, 5=Unmanaged marshland, 6=Water body, 7=Oth...	1.0
s2q7_other	string	Other non agricultural Land Type	``
s2q10	float64	Is there any agroforestry practices on this plot? 1=Yes, 2=No	``
s2q11	float64	Types of agroforestry trees planted in this plot? 1=Calliandra, 2=Leucaena, 3=Sesbania, 4=Acacia, 5=Erythrina, 6=Casuarina, 7=Maesopsis, 8=...	``
s2q11_o	string	Other types of agroforestry trees existing in this plot	``
plot_weight	float64	Plot weight	1.0
source_provider	string	Publishing organization.	NISR
source_dataset	string	Source dataset title.	Season B: Screening Agroforestry
source_resource	string	Source table name.	rwa_sas_seasonb_screening_agroforestry
source_package_id	string	Rwanda Data Sharing Platform dataset UUID.	79563b2c-d39b-49b4-9a4f-679f892ce9d9
source_resource_id	string	Rwanda Data Sharing Platform dataset UUID.	79563b2c-d39b-49b4-9a4f-679f892ce9d9
source_url	string	Original source download URL.	https://api.data.gov.rw/api/v1/datasets/public/79563b2c-d39b-49b4-9a4f-...
license_id	string	Source license identifier.	cc-by-4.0
retrieved_at	string	UTC retrieval timestamp.	2026-07-18T11:48:51Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-rwanda-season-b-screening-agroforestry-5e74ad1f")
df = ds["train"].to_pandas()
print(df.head())

Filter to Rwanda

rwanda = df[df["country_iso3"] == "RWA"]

Work with indicators

if "indicator_id" in df.columns:
    print(df["indicator_id"].value_counts().head())
    sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])

Citation

@misc{electric_sheep_africa_africa_rwanda_season_b_screening_agroforestry_5e74ad1f_2026,
  title        = {Season B: Screening Agroforestry | Africa (Rwanda Data Sharing Platform - NISR)},
  author       = {NISR},
  year         = {2026},
  url          = {https://api.data.gov.rw/api/v1/datasets/public/79563b2c-d39b-49b4-9a4f-679f892ce9d9},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-rwanda-season-b-screening-agroforestry-5e74ad1f}}
}

License

Released under CC BY 4.0.

Original data (c) NISR. When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.

About Electric Sheep

Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa on Hugging Face. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use load_dataset() to start working in seconds.

Browse the full collection: huggingface.co/electricsheepafrica

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Provenance: ingested 2026-07-18 via the Electric Sheep pipeline. Source URL: https://api.data.gov.rw/api/v1/datasets/public/79563b2c-d39b-49b4-9a4f-679f892ce9d9/download?format=csv