sobitd/Maji-Ndogo-Agricultural-Analysis

Using Pandas and Matplotlib to Analyse Maji Ndogo farm database # Integrated Agricultural Analysis in Maji Ndogo 1 ### Introduction **Project Overview:** The project aims to automate farming practices in Maji Ndogo by leveraging data-driven insights. It focuses on optimizing crop selection and cultivation practices based on geographic, weather, soil, and management data. **Personal Motivation:** I chose this project due to its potential impact on sustainable agriculture in challenging environments. My background in data science and passion for solving real-world problems align perfectly with the project's objectives. This project serves as a practical application of my skills and interests in machine learning, data analysis, and agriculture. ### Data Collection and Preparation **Data Sources:** The project utilizes data from an SQLite database, including tables for geographic features, weather conditions, soil and crop details, and farm management metrics. The data was collected through field surveys and digital sensors, ensuring comprehensive coverage of agricultural variables. **Data Cleaning and Preprocessing:** - **Data Integration:** Combined multiple tables using SQL queries to create a unified dataset. - **Cleaning:** Addressed issues like swapped column names, corrected spelling errors in crop types, and adjusted negative elevation values. - **Normalization:** Ensured consistency in data formats and units across all variables to facilitate accurate analysis. ### Exploratory Data Analysis (EDA) **Descriptive Statistics:** - **Summary Statistics:** Calculated measures of central tendency and dispersion for key variables like rainfall, elevation, and soil fertility. - **Data Distribution:** Analyzed the distribution of crop types across different soil types and geographic locations. ### Analysis #### Challenge 1: Uncovering Crop Preferences - **Tea Plantations:** Explored optimal conditions for tea cultivation, focusing on mean rainfall and elevation. #### Challenge 2: Finding Fertile Grounds - **Soil Fertility A …