ForecastFlow: Time Series Forecasting App Using Flask and Prophet

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 🔍 Project Overview

ForecastFlow is a simple and interactive time series forecasting app that I built using Flask and Facebook Prophet. It allows users to upload their own CSV files and generate future predictions with just a few clicks after uploading data  —no coding more analysis based !

This was a self-driven project to explore time series forecasting and learn how to deploy ML models with a user-friendly interface.

🎯 What Problem It Solves

Forecasting sales, demand, stock levels, or customer trends is critical in business. But many non-technical users struggle with coding-heavy tools. ForecastFlow simplifies that process — anyone can generate insights from their own data.

🛠️ Tools and Technologies Used

  • Python 

  • Pandas & NumPy – Data preprocessing

  • Facebook Prophet – Time series modeling

  • Flask – App deployment and UI

  • Matplotlib & Plotly – Visualizing forecast results

⚙️ Features of ForecastFlow

  • 📁 Upload CSV files with date & value columns

  • ⏳ Select the forecast period (e.g., 30, 60, 90 days)

  • 📊 View interactive line charts for actual vs. predicted values

  • ⬇️ Download forecasted data as CSV

📷 Screenshots of WebApp



Example graph output

{Click on image for broad clear view}

{Any one can upload the data file in csv or excel format to get end result graph with forecast sheet will be provided to download , they are not bind to write codes so its is suitable for non coders}

💡 Key Learnings

  • Hands-on experience with Prophet for decomposing time series

  • Building a full data-to-app workflow using Streamlit

  • Creating tools that are usable by non-coders

  • Deploying ML solutions that solve real business use cases

🔗 GitHub Link

👉 View ForecastFlow Project on GitHub

🧠 Final Thoughts

ForecastFlow was a great learning experience in building something both technical and user-friendly. I plan to extend it in the future with features like automatic seasonality detection and support for multiple time series columns.

If you're into forecasting or want to build apps for business users — this is a great project to try!

Hi, I’m Heena Shaikh — a Data enthusiast with a passion for analytics, storytelling, and machine learning. I enjoy exploring data to uncover patterns, solve problems, and make meaningful decisions. With skills in Python, MySQL, R, Data Visualization , Machine Learning and automation tools, I'm constantly learning and building towards a career in data science.

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