Campus takeaway trend insight and future prediction system

Project Overview

This project aims to build a campus takeaway trend insight and future prediction system based on Flask and Echarts. Through in-depth analysis of simulated campus takeout data sets and combined with machine learning algorithms, we are committed to providing a deep understanding of students' takeout ordering patterns and predicting future trends to help the campus catering industry make informed decisions.

data set

The simulated campus takeout data set contains information such as students' ordering records, delivery time, dish types, etc., providing a rich data basis for the system.

technology stack

• Flask : Build web applications to process and display data.
• Echarts : Data visualization library for creating interactive charts and presenting data analysis results.

Features

1. Data processing and analysis

   • Clean and process takeaway data to ensure data accuracy.
   • Use statistical methods to analyze the frequency, time, and dish preferences of students ordering takeout.

2. Visual display

   • Use Echarts to create interactive charts to show the trends and distribution of takeaway data.
   • Presents students’ takeout behavior at different times and locations.

3. regular prediction

   • Based on historical data, use machine learning algorithms or time series analysis to predict the pattern of students ordering takeout in the future.
   • Provides visual display of prediction results to help the catering industry make decisions.

Innovation

The innovation of this project is that it can predict future ordering patterns through in-depth analysis of student takeout data. This not only helps the campus catering industry better prepare and adjust services, but also provides them with more basis for business decisions. In this way, the catering industry can be more flexible to meet the needs of students and improve service quality.

Implementation steps

1. Data cleaning and processing : Clean the simulated campus takeout data set to ensure the accuracy and completeness of the data.
2. Data analysis and modeling : Use statistical methods or machine learning algorithms to analyze and model data to discover the patterns of students ordering takeout.
3. Flask application development : Use Flask to build web applications to achieve data processing, analysis and visual display.
4. Echarts visualization : Use Echarts to create interactive charts to display the analysis results of takeaway data.
5. Rule prediction and display : Make rule predictions based on historical data and present the prediction results in a visual way.
6. System optimization and deployment : Optimize the system to ensure stability and performance, and deploy it.

Through this project, we hope to provide a data-based decision support for the campus catering industry so that it can better meet the needs of students and improve service quality. At the same time, everyone is welcome to leave a message to discuss more innovations and application scenarios in the predictive analysis and visualization of campus takeaway data.