QuickLook CSV Uploader & Analyzer

A FastAPI application for uploading, analyzing, and visualizing CSV files with machine learning capabilities.

Features

• Upload CSV files through a modern web interface
• View file statistics (rows, columns)
• Preview the first 5 rows of the uploaded CSV
• Responsive UI with drag-and-drop support
• Machine learning analysis:
  • Descriptive statistics for numeric columns
  • Principal Component Analysis (PCA) with visualization
  • K-Means clustering with cluster information

Installation

1. Clone this repository:

git clone https://github.com/yourusername/quicklook.git
cd quicklook

2. Install the required dependencies:

pip install -r requirements.txt

Usage

1. Start the FastAPI server:

python run.py

2. Open your browser and navigate to:

http://localhost:8000

3. Upload a CSV file using the web interface.
4. Explore the different tabs to see data preview, statistics, and ML analysis.

Machine Learning Capabilities

The application automatically performs the following analysis on CSV files with numeric data:

• Descriptive Statistics: Mean, standard deviation, min/max values, etc.
• Principal Component Analysis (PCA): Dimensionality reduction to identify the most important features.
• K-Means Clustering: Automatically groups similar data points together.

Requirements

• Python 3.7+
• FastAPI
• pandas
• scikit-learn
• numpy
• uvicorn