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anitaadjei200-tech/HarvestGuard-Africa

Domaine:

agricultureclimatesocioeconomic

Type de record:

dataset
Créateur:
ani
Hôte:
HarvestGuard Africa is a predictive analytics project analyzing climate, crop yield, and food security data across five African countries (2013–2024, with projections to 2027). It delivers insights via a Power BI dashboard to help decision-makers identify and act on climate-driven food security risks. # HarvestGuard-Africa HarvestGuard Africa is a predictive analytics project analyzing climate, crop yield, and food security data across five African countries (2013–2024, with projections to 2027). It delivers insights via a Power BI dashboard to help decision-makers identify and act on climate-driven food security risks. **The Five Datasets** Five publicly available datasets were sourced, downloaded as CSV files, and consolidated into a single Microsoft Excel workbook: **Dataset Source What It Contributed** Staple Crop Yield (Maize, Rice, Cassava, Millet, Wheat) FAOSTAT fao.org Annual yield in kg/ha per country per crop 2013–2024. Baseline for Yield_Decline_% and FORECAST.LINEAR predictions Rainfall & Temperature World Bank Climate Portal climateknowledgeportal.worldbank.org Annual rainfall (mm) and mean temperature (°C) per country. Used for Rainfall_Deficit_% and Temp_Deficit_% Vegetation Health Index (VHI) FAO GIEWS fao.org Dekadal (10-day) VHI score per country. Averaged to annual VHI_Score for Climate_Stress_Score formula Food Security (Undernourishment) FAO Food Security Data fao.org Number of people undernourished (millions) per country per year. Used as Food_Security_Score in risk formula Malnutrition (Stunting Prevalence) UNICEF data.unicef.org Stunting prevalence % per country per year. Used as Malnutrition_Rate_% in risk formula **The Excel COMBINE MASTER** All five datasets were cleaned and merged into a single COMBINE MASTER sheet in Microsoft Excel using the following step-by-step process: Data Cleaning • Removed all redundant metadata columns from each CSV file (database codes, footnote flags, API reference fields) • Standardised country name spellings across all five sheets to enable consistent XLOOKUP and SUMPRODUCT matching • Filtered crop yield data to five target crops only: Maize, Rice, Cassava, Millet, Wheat • Filtered all datasets to the 2013–2024-time range for consistency …

Visit

github.com

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