On the final day of Dashboard Week, we embarked on a unique journey, beginning by examining the impact on mobility. However, at the stroke of 10:00, a surprising twist altered our course, presenting us with a new challenge involving a dataset. This time, we worked in pairs, focusing our analytical lens on New York taxis.
To obtain the dataset, we had to grapple with a Parquet file, a term that had been unfamiliar to me until that moment. Converting this Parquet file into usable tabular data required some Python wizardry. Once we successfully extracted our data, it was time to roll up our sleeves and start sketching out our project.
Our specific focus was on the green taxis, the electric or hybrid cabs of New York City. Our goal was to create a dashboard tailored for a New York City transportation department employee who sought to comprehend the usage patterns of these eco-friendly taxis over time and assess their economic feasibility.
We made charts to compare the current year with the previous one, revealing a decline in usage but a simultaneous increase in overall costs. This intriguing discovery prompted us to delve deeper into the factors contributing to this rise in cost per trip.
Additionally, we wanted to provide a visual representation of when and on which days green taxi trips predominantly occurred. Our findings unveiled a fascinating trend: most trips took place during weekday evenings, with Fridays and Saturdays surprisingly registering lower activity.
In hindsight, despite the unexpected shift at 10:00 that demanded quick thinking and adaptation, I thoroughly enjoyed my last day of Dashboard Week. It was a whirlwind of rapid problem-solving, making it a memorable and rewarding experience.