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Writer's pictureMona Swarnakar

The Metropolitan Transportation Authority (MTA) WebApp with Plotly Dash

Before diving into the details of the project, I want to share something exciting—I worked with Dash Plotly for the very first time! 😊 Despite not having prior knowledge of Python, I managed to successfully complete the project. To make this happen, I relied heavily on resources like the Dash Plotly website, their YouTube channel, and, of course, the invaluable help from Adam, who was incredibly supportive and quick to respond whenever I needed assistance.


How did I discover this tool?

I came across it through @Maven Analytics. They host a monthly data challenge, and for November 2024, they partnered with Dash Plotly, offering participants the opportunity to showcase their projects using this tool.

As someone from a non-technical background, I must admit, building a web app was no easy feat. I faced several challenges and spent over 15 days completing this project. Believe it or not, just deploying the app took me three days because I couldn’t figure out what was going wrong! 😅 But in the end, all the effort was worth it. I’m thrilled with the outcome and hope you enjoy the web app! 😊



About this project


The project focuses on the Metropolitan Transportation Authority (MTA) and consists of a three-page website that provides key insights and data analysis on ridership trends:

  1. About: This section offers an overview of the Metropolitan Transportation Authority, highlighting the organization's role and significance. Additionally, it includes a comparison of ridership percentages across segments between 2020 and 2024.

  2. Overview: The overview page presents a detailed trend analysis of total ridership by year. It showcases year-over-year changes in ridership, evaluates the percentage of pre-pandemic ridership recovery, and provides comparisons with the previous year's data.

  3. Segment: This page delves into segment-specific trends. It provides a breakdown of ridership changes by segment over the years, including year-over-year comparisons and pre-pandemic ridership recovery percentages.


This project marked my first foray into building a data-driven web application, and while it required significant effort and time, I’m proud to have completed it successfully within the deadline. The experience was both challenging and rewarding, pushing me to learn new tools and techniques.


I’d like to express my gratitude to Dash Plotly for providing such a powerful framework, which made it possible for me to develop and deploy the app.


The final application has been successfully deployed on PythonAnywhere, enabling web-based accessibility to the insights.


The weblink of the project is here:


The GitHub link is here:




Thank You :-)

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