Elish-Ab/KAIM-WEEK0-Solar_Farm_EDA_project

These repo is about EDA of 3 solar farms in africa. # KAIM WEEK0 Project ## Overview This project involves analyzing solar radiation and weather data from three different countries (Benin, Sierra Leone, and Togo). The data analysis includes data cleaning, exploratory data analysis (EDA), and visualization. Additionally, an interactive dashboard is created using **Streamlit** to visualize the insights and interact with the data dynamically. Finally, the dashboard is deployed on **Streamlit Community Cloud** for public access. ## Table of Contents - Project Structure - Installation - Data Analysis - Data Quality Check - Exploratory Data Analysis (EDA) - Time Series Analysis - Correlation Analysis - Outlier Detection and Z-Score Analysis - Wind & Temperature Analysis - Dashboard Development - Deployment - [Usage ## Project Structure ├── .streamlit │ └── config.toml ├── .vscode │ └── settings.json ├── .github │ └── workflows │ ├── unittests.yml ├── .gitignore ├── requirements.txt ├── README.md ├── notebooks │ ├── init.py │ ├── EDA.ipynb │ └── README.md ├── tests │ ├── init.py ├── app │ ├── init.py │ ├── main.py # main Streamlit application script │ ├── utils.py # utility functions for data processing and visualization └── scripts ├── init.py └── README.md --- ## Installation To run the project locally, follow these steps: 1. **Clone the repository**: ```bash git clone github.com cd KAIM-WEEK0 2. **Create a virtual environment (optional but recommended):** ```bash python -m venv .venv source .venv/bin/activate # On Windows, use .venv\Scripts\activate ``` 3. Install the required dependencies: ```bash pip install -r requirements.txt ``` ## Data Analysis Data Quality Check Missing Values: Identified missing values in the datasets (Benin, Sierra Leone, and Togo) and applied imputation or removal strategies. Outliers Detection: Applied Z-score analysis to detect anomalies in columns such as GHI, DNI, DHI, Tamb, WS, WSgust. Incorrect Entries: Filtered out incorrect entries, e.g …