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Data-Visualization-CurryPasta

Data Visualization Repository For Team "CurryPasta"

Table of Contents

  1. Introduction
  2. Prerequisites
  3. Installation
  4. Usage

Introduction

In this project we develop steps from 1 to 7 from the Data Visualization course.


Prerequisites

Before diving in, ensure you have the following installed:


Installation

Follow these steps to get your environment up and running.

1. Clone the Repository

Start by cloning the repository to your local machine:

https://github.com/Prat2420/Data-Visualization-CurryPasta.git
cd Data-Visualization-CurryPasta/

2. Create and Activate the Virtual Environment

Option A: Using requirements.txt

  1. Create the virtual environment:

    python3.11 -m venv my_env
  2. Activate the virtual environment:

    • On Windows:

      my_env\Scripts\activate
    • On macOS and Linux:

      source my_env/bin/activate
  3. Install dependencies:

    pip install -r requirements.txt

3. Updating Packages in the Environment

As the project evolves, we might need to add new packages to our environment. Below is the process to update the list of packages, ensuring everyone stays in sync.

Example: Adding a New Package

Suppose you need to add the package pydot to your environment.

Steps:

  1. Activate the Environment

    source my_env/bin/activate
  2. Add the Package to requirements.txt

    Open the requirements.txt file and add:

    pydot
    
  3. Install the New Package

    Run:

    pip install -r requirements.txt
  4. Verify the Package is Installed

    Check that pydot is now available in your environment:

    pip list | grep pydot

    You should see pydot listed among the installed packages.

  5. Commit the New Version of the Requirements File

    Ensure the updated requirements.txt file is committed to the repository:

    git add requirements.txt
    git commit -m "Updated requirements.txt with new package pydot"
    git push

Usage

To use the implemented steps of the project, go to the Notebooks folder and run either individual step notebooks (step_1.ipynb, step_2.ipynb, etc.) or the comprehensive all_in_one_final.ipynb that contains the most up-to-date implementation of all visualization techniques.

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Data Visualization (UU) Repository For Team Curry Pasta

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  • Jupyter Notebook 100.0%