electricsheepafrica/africa-rwanda-eicv5-vup-large-crops-7fe5c429

EICV5 (VUP): Large crops | Africa (Rwanda Data Sharing Platform - NISR)

4,613 rows - 1 Africa country/area - 2016-10-13-2017-10-22 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 4,613 rows from Rwanda Data Sharing Platform - NISR, covering EICV5 (VUP): Large crops. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Agriculture datasets help analysts examine production, prices, inputs, land use, food systems, and rural economic activity.

Source-provided context: Summary: This microdata table contains information on large scale crops collected in the fifth Integrated Household Living Conditions Survey, known as EICV5 (Enquête Intégrale sur les Conditions de Vie des ménages). A main cross-sectional sample survey, a panel survey and a VUP (Vision Umurenge Programme) sample survey were conducted simultaneously; this microdata table relates to the VUP sample survey. Geographic Coverage: National coverage (Rwanda), including rural and urban households and allowing province- and district-level estimation of key indicators. Data are disaggregated up to the district level. Time Period: The EICV5 survey was conducted over a 12-month cycle from October 2016 to October 2017. Data collection was divided into 10 cycles in order to represent seasonality in the income and consumption data.

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: not detected.
• Time coverage basis: source metadata period.
• Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

Dimension	Value
Rows	4,613
Countries/areas	1
First period	2016-10-13
Last period	2017-10-22
Indicators	0
Columns	29
Source format	CSV

Geographic Coverage

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

Area	Rows	First year	Last year	Name
RWA	4,613	2016-10-13	2017-10-22	Rwanda

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.	51c654b0-a6fa-43ed-9ad7-aa23055fc072:0
country_iso3	string	ISO3 country or area code.	RWA
country_name	string	Country or area name.	Rwanda
id	int64	Row ID	1
key_17	double	EICV5 Household unique ID	11000100.0
hhid	double	Household ID in EICV4	110001.0
clust	double	Cluster	11231.0
province	string	Province	Kigali City
district	string	District Name	Nyarugenge
ur	string	Urban/Rural	Rural
weight	double	Household weight	28.083334
s7dq1	bool	Engaged in any larger scale agricultural production over the last 12 months	False
s7d_crops	double	Number of Crops lines S7 Part D	``
s7dq2	string	Name of the crops	``
s7dq3	double	harvested in the last 12 months	``
s7dq5	double	Sold havest in kg over the last 12 months	``
s7dq6	double	average price per kg sold	``
s7dq7	double	Amount received	``
s0q18m	int64	Month of interview	4
s0q18y	int64	Year of interview	2017
s7dq4	string	Sold crops over the course of the last 12 months	``
source_provider	string	Publishing organization.	NISR
source_dataset	string	Source dataset or package title.	EICV5 (VUP): Large crops
source_resource	string	Source resource title, table name, or file name.	eicv5_vup_s7d_large_crop
source_package_id	string	Source package identifier.	51c654b0-a6fa-43ed-9ad7-aa23055fc072
source_resource_id	string	Source resource identifier.	51c654b0-a6fa-43ed-9ad7-aa23055fc072
source_url	string	Original source URL or download URL.	https://api.data.gov.rw/api/v1/datasets/public/51c654b0-a6fa-43ed-9ad...
license_id	string	Source license identifier.	cc-by-4.0
retrieved_at	string	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-07-18T16:36:19Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-rwanda-eicv5-vup-large-crops-7fe5c429")
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"] == "RWA"]

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

• No canonical year/date column was detected in the packaged table; use source metadata and domain context for temporal interpretation.
• 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: Rwanda Data Sharing Platform - NISR
• Publisher: NISR
• Portal: https://data.gov.rw/
• Resource: eicv5_vup_s7d_large_crop
• License: CC BY 4.0
• Retrieved/generated: 2026-07-18T16:37:06Z
• Hugging Face repo: electricsheepafrica/africa-rwanda-eicv5-vup-large-crops-7fe5c429

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

• Track production or price movements
• Compare regions or commodities
• Join with climate and trade data
• Check missingness before modeling
• Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_rwanda_eicv5_vup_large_crops_7fe5c429_2017,
  title        = {EICV5 (VUP): Large crops | Africa (Rwanda Data Sharing Platform - NISR)},
  author       = {NISR},
  year         = {2017},
  url          = {https://api.data.gov.rw/api/v1/datasets/public/51c654b0-a6fa-43ed-9ad7-aa23055fc072},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-rwanda-eicv5-vup-large-crops-7fe5c429}}
}

License

Released under CC BY 4.0.

Original data is published by NISR. 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.

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Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://api.data.gov.rw/api/v1/datasets/public/51c654b0-a6fa-43ed-9ad7-aa23055fc072