A Comprehensive Analysis of Energy Consumption, Demand Forecasting, and Infrastructure Recommendations in Cameroon
# PySpark Jupyter Notebook Project
This project contains PySpark Jupyter notebooks for analyzing energy consumption data. You can run this project in two ways:
1. Using Docker (Recommended): This method is guaranteed to work and ensures a consistent environment.
2. Using requirements.txt (Optional): This method is not guaranteed to work and depends on your local system configuration.
---
### Option 1: Using Docker (Recommended)
#### Prerequisites
- Docker installed on your system. If you don't have Docker, follow the installation guide for your operating system:
- Windows:
docs.docker.com
- macOS:
docs.docker.com
- Linux:
docs.docker.com
#### Steps to Run the Project
1. Extract the files from the folder I sent you to a directory on your computer. For example:
- On Windows: Extract to `C:\Users\ \Documents\pyspark-project`.
- On macOS/Linux: Extract to `/home/ /pyspark-project`.
2. Open a terminal (Command Prompt on Windows, Terminal on macOS/Linux) and navigate to the extracted folder. For example:
- On Windows:
```
cd C:\Users\ \Documents\pyspark-project
```
- On macOS/Linux:
```
cd /home/ /pyspark-project
```
3. Pull the PySpark Jupyter Docker image:
```
docker pull jupyter/pyspark-notebook:latest
```
4. Run the Docker container and mount the current directory:
```
docker run -p 8888:8888 -v "$(pwd)":/home/jovyan/work jupyter/pyspark-notebook
```
5. Access Jupyter Notebook:
- Open your browser and navigate to `
localhost`.
- The token for access will be displayed in the terminal where you ran the `docker run` command.
6. Open and run the notebooks:
- In the Jupyter interface, navigate to the directory.
- Open and run the notebooks.
---
### Option 2: Using requirements.txt (Optional)
#### Prerequisites
- Python 3.8 or higher.
- Java 8 or higher (required for PySpark).
- pip (Python package manager).
#### Steps to Run the Project
1. Extra …