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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta content="width=device-width, initial-scale=1.0" name="viewport">
<title>Datavista: GUI</title>
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<h1>DataVista: Graphic User Interface</h1>
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<div class="swiper-wrapper align-items-center">
<figure>
<img src="assets/img/data-engineering/datavista.png" alt="" style="max-width: 50%; max-height: auto;">
<figcaption style="text-align: center;"></figcaption>
</figure>
</div>
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<div class="section-title">
<h3>Table of Contents</h3>
<ol>
<li><a href="#introduction">Introduction</a></li>
<ul>
<li><a href="#why">Why IV&V is Important?</a></li>
<li><a href="#key">Key benefits of IV&V include</a></li>
<li><a href="#component">Components of IV&V</a></li>
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<li><a href="#method">IV&V in Different Software Development Methodologies</a></li>
<li><a href="#tools">Tools and Techniques Used in IV&V</a></li>
<li><a href="#challanges">Challenges in Implementing IV&V</a></li>
<li><a href="#best">Best Practices for IV&V</a></li>
</ul>
<li><a href="#reference">Reference</a></li>
</ol>
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<div class="container">
<hr>
<h1>Objective</h1>
<p><strong>DataVista</strong> is a modern Tkinter application designed for complex data analytics, providing a user-friendly interface to visualize, manipulate, and analyze datasets.</p>
<div class="grey-box">
For more details, please find the open source project details on: <a href="https://github.com/arunp77/datavista" target="_blank">github repository</a> (currently a private but very soon make it open source).
</div>
<h2>Features</h2>
<ul>
<li>Modern UI design with customizable themes</li>
<li>Reusable components for quick development</li>
<li>Responsive layout adaptable to various screen sizes</li>
</ul>
<h2>Requirements</h2>
<ul>
<li>Python 3.x</li>
<li>Tkinter (included with standard Python installation)</li>
</ul>
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# Bash example: List all files in the current directory
for file in *; do
echo "Found file: $file"
done
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-- SQL example: Select all rows from a table
SELECT * FROM users WHERE status = 'active';
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<h2>Steps</h2>
<ol>
<li>Clone the repository:
<pre><code>git clone https://github.com/arunp77/datavista.git</code></pre>
Next, go to the Tkinter project directory:
<pre><code>cd datavista/</code></pre>
</li>
<li>Install Poetry if you haven't already. Follow the instructions on the <a href="https://python-poetry.org/docs/#installation" target="_blank">Poetry website</a>.</li>
<li>Create a virtual environment and install dependencies:
<ul>
<li>Create and activate a virtual environment:
<pre class="language-python"><code>
#!/bin/bash
$ python -m venv venv
$ source venv/bin/activate # On linux
$ venv\Scripts\activate # on windows
</code></pre>
</li>
<li>Install required packages:
<pre><code>poetry install</code></pre>
or just install <code>tkinter</code> using (for more details on the tkinter library, please check the <a href="https://docs.python.org/3/library/tkinter.html" target="_blank">official documentation</a>):
<pre><code>pip install tk</code></pre>
</li>
</ul>
</li>
<li><strong>Docker image:</strong> The docker image of the complete application can be found at: <a href="https://hub.docker.com/repository/docker/arunp77/datavista-tkinter-app/general" target="_blank">datavista-application</a></li>
</ol>
<h2>Usage</h2>
<p>To run the application, execute the following command in your terminal:</p>
<pre><code>python src/main.py</code></pre>
<p>or</p>
<pre><code>poetry run python src/main.py</code></pre>
<h2>The Planned Interface</h2>
<p>Our current plan is to create an interface with:</p>
<ul>
<li>Data load option</li>
<li>View the first 5 lines after loading the data</li>
<li>Create a few plots such as scatter, line, bar, etc.</li>
</ul>
<figure>
<img src="assets/img/data-engineering/interface.png" alt="" style="max-width: 90%; max-height: auto;">
<figcaption style="text-align: center;"></figcaption>
</figure>
<h2>Future Plan</h2>
<p>I will be modifying the interface more in the future. I will try to make it look more advanced and enable more advanced-level data analytics, including machine learning analysis.</p>
<h2>Project Structure</h2>
<pre class="language-python"><code>
datavista/
├── src/
│ ├── __init__.py
│ ├── main.py # Main application file
│ └── ui/
│ ├── main_window.py # Main window class
│ └── custom_widgets.py # Custom widgets
├── tests/
├── pyproject.toml
└── README.md</code></pre>
<h2>Contributing</h2>
<p>Feel free to contribute to this project! Please follow these steps:</p>
<ol>
<li>Fork the repository.</li>
<li>Create a new branch:
<pre><code>git checkout -b feature/your-feature</code></pre>
</li>
<li>Commit your changes:
<pre><code>git commit -m "Add your new feature"</code></pre>
</li>
<li>Push to the branch:
<pre><code>git push origin feature/your-feature</code></pre>
</li>
<li>Open a pull request.</li>
</ol>
<h2>License</h2>
<p>This project is licensed under the MIT License. See the <a href="LICENSE" target="_blank">LICENSE: Creative Commons Legal Code CC0 1.0 Universal</a> file for details.</p>
<h2>Contact</h2>
<p>For any inquiries, feel free to reach out to <a href="mailto:[email protected]">[email protected]</a>.</p>
</div>
<!-------Reference ------->
<!-- <section id="reference">
<h3>References</h3>
<ol>
<li><a href="https://www.youtube.com/watch?v=dq-ZACSt_gA&t=28s" target="_blank">Youtube Kafka tutorial videos (I specially followed this one. Great playlist).</a></li>
<li><a href="https://kafka.apache.org/documentation/" target="_blank">Apache</a></li>
<li><a href="https://spark.apache.org/documentation.html" target="_blank"> Official Documentation</a></li>
<li><a href="https://www.databricks.com/learn/training/login" target="_blank">Databricks Learning Academy</a></li>
<li><a href="https://sparkbyexamples.com/" target="_blank">Spark by Examples</a></li>
<li><a href="https://www.datacamp.com/tutorial/pyspark-tutorial-getting-started-with-pyspark" target="_blank">Datacamp tutorial</a>.</li>
<li>For databricks, you can look at tutorial videos on youtube at <a href="https://www.youtube.com/watch?v=ChISx0-cMpU" target="_blank">youtube video by Bryan Cafferky</a>,
writer of the book "Master Azure Databricks". A great playlist for someone who just want to learn about the big data analytics at Databricks Azure cloud platform.</li>
<li>See the video for <a href="https://www.youtube.com/watch?v=_C8kWso4ne4" target="_blank">pyspark basics by Krish Naik</a>. Great video for starter.</li>
<li><a href="https://www.youtube.com/watch?v=QLGrLFOzMRw" target="_blank">Great youtube on Apache spark</a> one premise working.</li>
</ol>
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<hr>
<div style="background-color: #f0f0f0; padding: 15px; border-radius: 5px;">
<h3>Some other interesting things to know:</h3>
<ul style="list-style-type: disc; margin-left: 30px;">
<li>Visit my website on <a href="sql-project.html">For Data, Big Data, Data-modeling, Datawarehouse, SQL, cloud-compute.</a></li>
<li>Visit my website on <a href="Data-engineering.html">Data engineering</a></li>
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