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Time Series Analysis (TSA) Dashboard 📈

Streamlit App

Welcome to the TSA Dashboard! This interactive web application is built with Streamlit to provide deep insights, dynamic visualizations, and forecasting for Time Series data.

Academic Context: This project and dashboard were developed as part of a Time Series Analysis project completed at the Indian Institute of Technology (IIT) Guwahati. You can view the formal certification in the repository: TSA_IITg_CertificateOfExcellence.pdf.

🗂️ Repository Structure

  • dashb.py: The main Streamlit application file containing the dashboard layout and UI logic.
  • task1_3.py: Python script covering the implementation of Tasks 1 through 3 of the IIT project (e.g., data preprocessing, exploratory data analysis, and initial modeling).
  • task4_final.py: Python script covering Task 4, which includes the final forecasting models and advanced time series analytics.
  • requirements.txt: The list of Python dependencies required to run the project.

🌟 Features

  • Interactive Visualizations: Dynamically filter and explore time-dependent data trends.
  • Statistical Analysis: Quickly surface key metrics, rolling averages, and seasonal patterns.
  • Modular Codebase: Analysis is cleanly separated into task-specific scripts for easy review.

About

An interactive Streamlit dashboard for Time Series Analysis (TSA) and forecasting, originally developed for a project at IIT Guwahati.

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