Taxi price analysis

Taxi price analysis

Introduction

I’ve always been fascinated by how data can reveal hidden patterns in everyday life. Like many urban dwellers, I often take taxis to save time—working on my laptop in the back seat instead of zoning out on public transport. But I couldn’t help noticing how wildly the prices fluctuated throughout the day!

For my daily commuting needs, I regularly use Yandex.Taxi (internationally known as Yango), one of the largest ride-hailing services in Eastern Europe. While the app is convenient and the service reliable, I noticed significant price fluctuations depending on the time of day, weather conditions, and other factors that weren’t immediately obvious.

New Yandex office walkability analysis

New Yandex office walkability analysis

Turning Commute Frustration into Data-Driven Housing Decisions

When I heard about our company’s plans to relocate to a brand new headquarters, my analytical mind immediately kicked into high gear. As someone who values both sleep and work-life balance, I wasn’t thrilled about potentially extending my daily commute. Could data help me find the sweet spot between affordable housing and a reasonable walk to work?

Rather than browsing endless rental listings or asking around for opinions, I decided to approach this challenge like any good analyst would—by gathering concrete data and visualizing it. This side project would not only help me make a more informed personal decision but also sharpen my geospatial analysis skills.