surajokanyae/Maji-Ndogo-Agricultural-Analysis

An end-to-end data pipeline using SQL and Python to optimize agricultural yields in Maji Ndogo. # Integrated Project: Understanding Maji Ndogo's Agriculture ## 📌 Project Overview This project focuses on the intersection of data science and agriculture. Using Python and SQL, I analyzed agricultural data from Maji Ndogo to identify patterns in soil fertility, climate conditions, and crop yields. ## 🛠️ Tech Stack - **Language:** Python - **Libraries:** Pandas, SQLAlchemy, Matplotlib - **Database:** SQLite ## 📊 Key Highlights - **Data Integration:** Unified multiple SQL tables (Weather, Soil, Farm Management) into a single analytical dataset. - **Data Cleaning:** Handled inconsistent crop naming, standardized elevation data, and addressed missing values. - **Exploratory Data Analysis:** Analyzed the relationship between rainfall, elevation, and the success of different crop types. - ## 🏃 How to Run 1. Clone this repository. 2. Ensure you have the `.db` file in the root directory. 3. Install dependencies: `pip install -r requirements.txt` 4. Open the Jupyter Notebook to view the analysis.