M-Deve/Maji_Ndogo

This repository contains code on identifying best farming practices for Maji Ndogo # 🌾 Maji Ndogo: Farming Automation Data Analysis Welcome to the Maji Ndogo project — an ambitious data analysis initiative supporting the automation of agriculture in a diverse and challenging landscape. This project lays the groundwork for making informed decisions about where and what to farm by analyzing environmental, geographic, and crop-related data. ## 📌 Project Overview Maji Ndogo, a region with varied terrain and climate conditions, is on a mission to revolutionize agriculture using data. Before deploying automation tools, it is crucial to understand: - 🌱 Where to farm - 🌾 What to grow - 🌤️ Which environmental conditions influence yields Our job? Combine and clean data from multiple tables in an SQLite database, explore patterns and correlations, and produce actionable insights. --- ## 🗃️ Data Sources The data is stored in an SQLite database: `Maji_Ndogo_farm_survey.db`. It consists of four tables joined by the common field: `Field_ID`. ### 1. 🌍 Geographic Features | Column | Description | |-----------|-----------------------------------------------------| | Field_ID | Unique field identifier (BigInt) | | Elevation | Elevation in meters (Float) | | Latitude | Latitude in degrees (Float) | | Longitude | Longitude in degrees (Float) | | Location | Province or administrative region (Text) | | Slope | Land slope (Float) | ### 2. 🌦️ Weather Features | Column | Description | |--------------------|----------------------------------------------| | Field_ID | Field identifier (BigInt) | | Rainfall | Annual rainfall in mm (Float) | | Min_temperature_C | Avg. minimum temperature in °C (Float) | | Max_temperature_C | Avg. maximum temperature in °C (Float) | | Ave_temps …