Statistical Data Analysis App

Overview

This enhanced Streamlit application offers a sophisticated platform for statistical data analysis. With a focus on sensor data, it provides interactive and detailed analyses, catering to both advanced users and those new to data analysis. The app now supports multi-page navigation, allowing users to focus on specific types of analyses separately, enhancing the user experience.

Features

• Advanced File Upload: Supports TAR files containing CSVs, allowing for bulk data processing.
• Multi-Page Navigation: Each analysis type is hosted on a separate page, improving navigation and user focus.
• Comprehensive Data Analysis Techniques: The application includes several sophisticated data analysis methods:
  • Setting Acceptance Upper and Lower Limits: Analyzes data within specified boundaries.
  • Reporting Out of Boundary Data: Identifies and reports data points that fall outside predefined limits.
  • Trending Historical Data Analysis: Investigates trends and patterns over time.
  • Curve Fitting and R² Calculation: Performs curve fitting (linear, polynomial, exponential) and calculates the coefficient of determination.
  • Step-Shift Adjustments: Detects and adjusts for sudden changes or shifts in the data.
  • Comparative Linear Regression Analysis: Compares linear relationships between variables across different groups.
  • 3-Sigma Envelope Analysis: Implements the 3-sigma rule for outlier detection in data.
  • Cook's Distance Analysis: Identifies influential points in regression analysis.
• Enhanced Data Visualization: Integrates Plotly for dynamic, interactive charts and graphs.
• User-Friendly Interface: Easy-to-navigate interface with clear options and interactive elements for a smooth user experience.
• Streamlined Code Structure: Code for each analysis is modularized and organized within the utils and for Pages in page directory, following best practices.

Installation

Ensure you have Python(3.11.6) installed on your system. The application relies on various Python libraries listed in requirements.txt.

1. Clone the Repository

git clone https://github.com/Kheem-Dh/CSV-Excel-File-Analyzer-App.git
cd statistical-analysic-streamlit-local

2. Create and Activate a Virtual Environment (Recommended)

• For Windows:

  python -m venv venv
  .\venv\Scripts\activate

• For macOS and Linux:

 python3 -m venv venv
source venv/bin/activate

3. Install Dependencies

pip install -r requirements.txt

4. Running the App To start the Streamlit server:

streamlit run Upload_File.py

Access the app in your web browser at http://localhost:8501.

5. Usage

• File Upload: Click "Choose a CSV or Excel file" to upload.
• Analysis Selection: Navigate to different pages for each type of analysis.
• Column Selection: Choose appropriate columns for the selected analysis.
• View Results: Explore the interactive visualizations and data tables.