Dishing Out Data with Mai Shan Yun

Intro to Our Dashboard
Graph: Ingredients Used per Month
Graph: Ingredient Usage for Next 3 Months
Graph: Top Dishes Per Month

Inspiration

We wanted to support local business and also learn the process of how we can use different datasets to create a working, interactive dashboard.

What it does

Given the datasheets of Mai Shan Yun inventory, our goal was to create a functional dashboard that can give key insights into information like ingredients stock, sales notifications, and seasonal and monthly trends. Our dashboard specifically focuses on ingredients usage over the months, predicting future use, and top dishes. This aims to help the restaurant with understanding which ingredients get used the most and least and also be able to visually see general trends.

How we built it

We used Streamlit through VSCode to get the dashboard to run. By using libraries like pandas, mathplotlib, and plotly, we were able to format graphs to reflect different trends and information from the datasets given. We also used OpenAI, to understand the syntax of how to use to many features in Streamlit.

Challenges we ran into

Since we were cleaning and formatting databases, we were getting a lot of errors on missing columns and syntax. By using Open AI, we were able able to understand what we were doing wrong. It also helped us learn the syntax for Streamlit.

Accomplishments that we're proud of

Since this was our first time using these platforms, it was a learning curve in understanding where to start in analyzing the data. However, by trying out different resources, we were able to create a functioning dashboard that we are proud of.

What we learned

We learned how to use Streamlit and different python libraries to analyze and visualize the data. Since the datasheets collected different types of data, we also learned how to combine different categories to answer the questions given.

What's next for Mai Shan Yun Dashboard

We would probably focus on how to get the dashboard to be more interactive for the people using it. This would be done learning all the other features Streamlit has to make a dashboard more usable.

Built With

openai
python
streamlit
vscode

Submitted to

TAMU Datathon 25: A Code Case!

Created by

I worked on ordering datasets based on certain categories. I also learned how to use different libraries in Streamlit.

Rishika Mudundi
For our Mai Shan Yun project, my contributions focused on integrating creative, structured components that elevated the overall look of the dashboard to be visually professional and aesthetic. The sidebar feature that Streamlit uses was also a integral component of the dashboard that I worked on mainly to utilize as an informative alert system that lets staff know when to next restock based on prior trends in 2025. Furthermore, I worked on team management by engaging my teammates and incorporating our best skillsets in active communication.

Aparna Sathya Narayanan
I worked on compiling and incorporating all my teammates' code into one file. I worked on debugging and aesthetics, as well as creating a "Top Dishes" graph and creating an Excel sheet with all the Restaurant data together using Power Query.

ranibhakta
I worked on combining the data files and analyzing the ingredient usage across months. I also created the outline of the overall dashboard and got it to first start working. It was my first time working with Streamlit, but I learned a lot.

Chaitra Shenoy

Updates

Rishika Mudundi started this project — Nov 09, 2025 12:56 PM EST

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