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Table of Contents

• ↓ Anatomy of a major surge pricing event: The Rolling Stones No Filter Tour
• ↓ Bears games show less evidence of post-game surge pricing, but there’s a big caveat
• ↓ Geographically widespread surge pricing events
• ↓ Surge pricing seasonality by location and time of week
• ↓ Robust regression methodology to estimate historical surge prices
• ↓ Why were surge prices so high in Q2 2019?
• ↓ Top Alternatives to toddwschneider.com

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"The City of Chicago now publishes trip-level data for every ride-hail trip taken since November 1, 2018. Chicago isn’t the first major US city to make ride-hailing trip data publicly available—New York has published Uber and Lyft data since 2014—but the Chicago dataset includes additional fields, most notably fare amounts, that provide new insights into the ride-hailing landscape."

"In particular, although the dataset does not explicitly indicate when high-demand “surge” pricing was in effect, I used the available fields to reverse engineer the historical surge pricing map based on a robust regression model. More to come about the methodology, along with challenges and caveats. All code used in this post is available on GitHub. As I write this in March 2020, the dataset includes 129 million trips from November 1, 2018 through December 31, 2019. It is scheduled to update quarterly in the future."

"You can play around with the map below to see estimated surge pricing multipliers by time and neighborhood. I’ve highlighted some notable events with elevated pickup activity and/or surge pricing, for example at the conclusion of The Rolling Stones concert at Soldier Field on June 25, 2019, when fares were 3x more expensive than usual."

"In addition to estimated surge multipliers, the map shows modified z-scores, which represent pickup activity in an area compared to the median for that time of day and day of week. Positive z-scores mean more pickups than normal. For example, the area near Soldier Field saw 154 pickups at midnight after the Stones concert, while a median Wednesday midnight sees 9 pickups with a median absolute deviation of 2.5. Those numbers produce a large modified z-score of 39, meaning way more pickups than normal. (The “modified” part in modified z-score refers to the use of the median and median absolute deviation instead of the mean and standard deviation, which reduces the impact of outliers.)"

Key Topics & Focus Areas for toddwschneider.com:

Anatomy of a major surge pricing event: The Rolling Stones No Filter Tour

Bears games show less evidence of post-game surge pricing, but there’s a big caveat

Geographically widespread surge pricing events

Surge pricing seasonality by location and time of week

Robust regression methodology to estimate historical surge prices

Why were surge prices so high in Q2 2019?