Maven Commuter Challenge

Goal

The project involved stepping into the role of a Data Visualization Specialist for the Data & Analytics Team at the Metropolitan Transportation Authority (MTA), North America's largest transportation network. The objective was to create an interactive visual or dashboard that illustrates post-pandemic ridership recovery trends across the MTA's services.

The dataset is a single table containing estimated daily passenger numbers for each of the seven MTA services, spanning from March 1, 2020, to October 31, 2024. For the Access-A-Ride service, which used daily scheduled trips, the data was treated the same as the other six services. Each day's ridership is compared to the 2019 monthly average for the same day type (non-holiday weekday, Saturday, or Sunday/holiday) in the equivalent month. This information served as the pre-pandemic baseline.

I decided to provide a macro-level overview of the MTA’s services and their ridership trends during the pandemic. For me, this means showing all relevant information on a one-pager. Based on the task, I decided to use an explanatory dashboard to guide the users through specific insights.

Data Cleaning

No data cleaning was required for this challenge, as it focused mainly on data visualization. For clarity, I renamed the MTA service "Bridges and Tunnels" to "Traffic". Additionally, since I decided to present the data grouped by calendar week, I removed the final incomplete calendar week to maintain consistency.

Report Structure

The one-pager is structured into three sections.

1. The first section introduces the user to the topic by displaying the average daily passenger numbers for each of the seven MTA services. This immediately highlights that nearly all passengers use three of the seven services: the Subway, the Bus, or vehicles crossing the seven bridges and two tunnels operated by the MTA, the ladder renamed into Traffic. These three services set the narrative for the report, as their significance in overall ridership shapes the focus of the entire one-pager.

2. The second and main section shows a line chart of the recovery rates (in percentage) for each service throughout the pandemic up to October 2024, aggregated at the calendar week level. The main focus is on the three main services. This visualization is enriched with info-windows highlighting key events affecting the transportation system, both pandemic-related and otherwise. Events such as the overnight subway shutdown in May 2020 and MTA’s campaign in October 2020 to increase passengers were excluded, as they did not show a noticeable impact on the trends at this level of granularity. I thought a lot about whether to show the data at the monthly level to smooth out weekly fluctuations and reinforce a macro-level perspective. This approach, however, decreased the storytelling potential, as the info-windows became too condensed to convey meaningful context. In the chart tooltips are included, offering additional details about the events, because even on a weekly level there were significant space limitations. To further engage users and introduce interactivity, I created an animated line chart to let the user fly through the pandemic, observing the progression of recovery rates over time. The animation was achieved by creating a measure that evaluates as TRUE for all dates in the past and FALSE for future dates relative to the current date. The visual is filtered to display only TRUE values.

3. The final section zooms out from the calendar week view to present a 3-month rolling average for each of the seven services, along with a comparison to the previous 3-month rolling average. This concluding section provides a high-level snapshot of the latest usage numbers and trends, giving users a clear understanding before exiting the report.

Design

To ensure a continous and visually engaging design, I used a color palette tool to select three distinctive colors for the primary transportation services in focus while all other services were grayed out. Taking advantage of the Gestalt Principle of Similarity, I applied consistent coloring for each service across all charts to enhance clarity and intuitive understanding.