DTS-Assignment

This repository contains code and resources for the DTS Assignment, which includes data analysis of a dataset (zomato_df_final_data.csv) and implementation files (assignment1.py, Assignment1.ipynb) to explore and manipulate the data. The repository also includes configuration files necessary for setting up a Docker container environment.

Repository Structure

• data/zomato_df_final_data.csv: The primary dataset used in this project, containing information about restaurant data.
• .dockerignore: Lists files and directories that should be ignored by Docker.
• .gitignore: Specifies files and directories that Git should ignore in the version control process.
• Ansa_PDF.pdf: A supporting document, potentially containing instructions, notes, or assignment details.
• assignment1.py: A Python script that processes or analyzes the zomato_df_final_data.csv file.
• Assignment1.ipynb: A Jupyter notebook that may contain code, analysis, and visualizations related to the dataset.
• Dockerfile: The configuration file to set up a Docker container for running the code in a controlled environment.
• requirements.txt: Lists the Python dependencies required to run the code.

Getting Started

Prerequisites

To run this code, ensure you have the following installed:

• Python 3.x
• Docker (if you prefer running the code in a Docker container)

Installation

1. Clone the repository:

   git clone https://github.com/your-username/DTS-Assignment.git
   cd DTS-Assignment

2. (Optional) Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate   # On Windows, use `venv\Scripts\activate`

3. Install the required dependencies:

   pip install -r requirements.txt

Running the Code

Running the Python Script

You can run the assignment1.py script directly using Python:

python assignment1.py

The script is expected to read the zomato_df_final_data.csv file and perform data analysis or transformation, producing outputs such as summaries, visualizations, or reports.

Running the Jupyter Notebook

To explore or modify the code in the notebook (Assignment1.ipynb), follow these steps:

1. Launch Jupyter Notebook:

   jupyter notebook

2. Open Assignment1.ipynb from the Jupyter Notebook dashboard and execute the cells to explore the analysis step-by-step.

Running with Docker

To run the project using Docker, follow these steps:

1. Build the Docker image:

   docker build -t dts-assignment .

2. Run the Docker container:

   docker run -it dts-assignment

This will set up the environment according to the Dockerfile and run the specified code within the container.

Expected Output

When the code is executed, you can expect:

• Analysis results on the zomato_df_final_data.csv dataset, possibly including:

  • Data cleaning and processing steps.
  • Visualizations of trends or insights.
  • Statistical summaries or models, depending on the assignment requirements.

• If using the Jupyter notebook, you'll be able to interact with the data, execute cells individually, and view the step-by-step results of the analysis.

License

This project is licensed under the MIT License - see the LICENSE file for details.