electricsheepafrica/africa-zambia-crop-forecast-survey-2021-2022-30d64709

Crop Forecast Survey 2021 2022 | Africa (Zambia Statistics Agency)

3,939 rows - 1 Africa country/area - 2021-2024 - source table - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

TL;DR

This dataset contains 3,939 rows from Zambia Statistics Agency, covering Crop Forecast Survey 2021 2022. 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: Crop Forecast Survey 2021-2022

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.
• —Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

Geographic Coverage

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

Indicators, Variables, Or Resource Contents

• —This repo preserves one source tabular resource with its usable columns kept together.

Schema

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-zambia-crop-forecast-survey-2021-2022-30d64709")
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"] == "ZMB"]

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: Zambia Statistics Agency
• —Publisher: Zambia Statistics Agency
• —Portal: https://www.zamstats.gov.zm
• —Resource: Crop Forecast Survey 2021-2022
• —License: other-open
• —Retrieved/generated: 2026-07-22T09:46:45Z
• —Hugging Face repo: electricsheepafrica/africa-zambia-crop-forecast-survey-2021-2022-30d64709

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_zambia_crop_forecast_survey_2021_2022_30d64709_2024,
  title        = {Crop Forecast Survey 2021 2022 | Africa (Zambia Statistics Agency)},
  author       = {Zambia Statistics Agency},
  year         = {2024},
  url          = {https://www.zamstats.gov.zm/cfs-2021-2022/},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-zambia-crop-forecast-survey-2021-2022-30d64709}}
}

License

Released under other-open.

Original data is published by Zambia Statistics Agency. 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.

Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://www.zamstats.gov.zm/cfs-2021-2022/