wasemi/TACKLING-CLIMATE-CHANGE-IMPACT-ON-AGRICULTURE

To analyze how rising temperatures and unpredictable weather patterns affect crop yields and agricultural productivity across African countries. # CLIMATE CHANGE ANALYSIS ## Project Overview Climate change significantly affects agricultural productivity at both local and regional scales. In Africa, it remains a critical issue, hindering progress towards achieving the United Nations Sustainable Development Goals (SDGs), particularly: SDG 13 (Climate Action) - Addressing climate-related challenges in agriculture. SDG 2 (Zero Hunger) - Improving food security and sustainable agriculture. By leveraging data-driven approaches, this Datathon aims to identify actionable insights, develop innovative solutions, and contribute to global efforts to mitigate the negative impacts of climate change on agriculture for a more sustainable future. ### Table of Contents Data source Tools Project Structure Analysis Recommendations ### Dataset The data was gotten from FAO Crop Production and Livestock Download here and NASA Climate data Download here ### Data Exploration and Preprocessing The crop production and livestock dataset consisted of 16 columns and 14,596 rows. The temperature dataset contained 3 columns and 144 rows. ### Data Cleaning and Transformation Understanding & Selecting Relevant Columns Data exploratory analysis the data, to understand the trend, look at what is important for the analysis. Checked for duplicates Mean imputation method in replacing null values Unpivot columns to have all the values for different years just in two columns, the year and then the value for that year. Finally column selection Crop Production dataset, columns used for analysis: Area, Item, Element, Value, Year. Global temperature anomalies data, not much cleaning was done there, I just explored the data and selected the years that corresponded to the year I had in the crop production and livestock data to enable a connection. Temperature dataset, columns selected: Derived Temperature, Smoothed Temperature, Year. ### Data Standardization & Cleaning Renamed columns for better readability (Area → Countries, Item → Crops). Stan …