benitchriss2015-cmd/malawi-stock-exchange-data-stock-analysis

This is a data analysis project of the stock data of the listed companies on malawi stock exchange Data-Driven Development Framework 📌 Project Overview This project establishes a standardized, scalable framework for Economic and Development Data Science. Built upon international best practices for transparency and reproducibility, it integrates financial analysis with community impact metrics. As a professional at the intersection of Finance and Data Science, I developed this repository to demonstrate how rigorous version control, structured folder hierarchies, and collaborative documentation can drive sustainable development initiatives. 🚀 Key Features Reproducible Analysis: Automated environment setup using Mamba/Conda. Bilingual Documentation: Framework support for multicultural project environments. Professional Standards: Integrated Contributor Covenant Code of Conduct. Data Governance: Strict protocols for handling sensitive financial and geographical datasets. 📂 Repository Structure Following the standardized Data Lab philosophy, the project is organized as follows: Plaintext ├── data/ # Local only: raw-data and derived-datasets ├── docs/ # Jupyter Book documentation and methodology ├── notebooks/ # Thematic analysis (Agriculture, Finance, etc.) ├── src/ # Production-ready Python processing scripts ├── .env.example # Template for API keys and credentials └── environment.yml # Conda environment configuration Getting Started 1. Clone & Setup Bash git clone github.com cd development-framework 2. Environment Configuration I utilize Mamba for high-speed dependency management. Create the environment using: Bash mamba env create -f notebooks/environment.yml conda activate [env_name] 3. Running the Analysis Launch the Jupyter ecosystem to explore the notebooks: Bash jupyterlab Methodology & Standards This project adheres to a "Results-Oriented" analytical structure: Data Sourcing: Integration of alternative data and official statistics. Processin …