https://github.com/dylan-stewart/capstone

Cloud-Based Analytics Application: CSV Check ~ Data Visualization for Inexperienced Users
https://github.com/dylan-stewart/capstone

automation cloud css csv data-visualization exploratory-data-analysis file-processing flask gcp gcs html javascript machine-learning python visualization web-app

Last synced: 7 months ago
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Cloud-Based Analytics Application: CSV Check ~ Data Visualization for Inexperienced Users

• Host: GitHub
• URL: https://github.com/dylan-stewart/capstone
• Owner: Dylan-Stewart
• License: mit
• Created: 2025-05-20T09:12:05.000Z (7 months ago)
• Default Branch: main
• Last Pushed: 2025-06-03T10:15:50.000Z (7 months ago)
• Last Synced: 2025-06-03T21:17:57.079Z (7 months ago)
• Topics: automation, cloud, css, csv, data-visualization, exploratory-data-analysis, file-processing, flask, gcp, gcs, html, javascript, machine-learning, python, visualization, web-app
• Language: HTML
• Homepage:
• Size: 3.54 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# CSV Check

**Cloud-Based Analytics Application**  

**CSV Check – Data Visualization for Inexperienced Users**

CSV Check is a lightweight, cloud-powered tool designed to help everyday users explore and understand their data. By simply uploading a CSV file, users receive cleaned data, automatically generated visualizations, and simplified AI-generated summaries — no technical knowledge required.

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## 🚀 What It Does

- Upload a CSV file

- Automatically clean and process the data

- Generate visual summaries with plots

- Get plain-English explanations of insights

- View basic machine learning predictions (if applicable)

CSV Check aims to **bridge the gap between complex data tools and non-technical users**, providing insights through automation and clarity.

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## 🌐 About This Repository

> **Important Note**  

> This repository only contains the **frontend and application-facing code** (Flask app, routing, HTML/CSS templates).  

> The cloud infrastructure (Google Cloud Functions, API calls, and backend logic) is **not included here**.

This means you're seeing the interface and local structure that connects to the cloud, not the full cloud processing logic itself.

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## 🖼️ Screenshots & Previews

Below are some example screenshots of the application in use.

### 📊 Upload and Analysis Interface

![Upload Screenshot](images/upload_interface.png)

### 📈 Sample Visualization Page Output

![Visualization Page Screenshot](images/visualization_output.png)

### 🤖 Sample Machine Learning Page Output

![Machine Learning Page Screenshot](images/machine_learning_output.png)

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## 🧠 Tech Stack

- **Python** (Flask)

- **HTML/CSS** for basic UI

- **Google Cloud Storage** – For uploading and retrieving user files

- **Google Cloud Functions** – For processing CSV files serverlessly

- **OpenAI API** – For generating human-friendly summaries and insights

- **Pandas / Matplotlib / Seaborn / Scikit-learn** – For data processing and visualizations

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## 📁 File Structure (Partial)

csvCheck/

├── static/

│ └── css/

│ └── style.css

├── templates/

│ ├── index.html

│ ├── result.html

├── app.py

└── README.md

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## ✍️ Author

**Dylan Stewart**  

Master's in Computer Science  

Hofstra University

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## 📌 Possible Future Plans

- Add user-specified visualization options

- Processing speed enhancements

- Offer increased handling for dealing with very large file sizes

- Include more interactive plots

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## 📬 Feedback

Have suggestions or want to contribute? Feel free to open an issue or reach out via email.

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