Five minutes with surge_multiplier in ride-hail-trips

Someone asked what is in surge_multiplier on ride-hail-trips, and the honest answer took one query.

8,000 rows, no nulls, 24 distinct values. 1.0 when demand is normal, up to 3.4 at peak.

The five-number version: min 1.00, p10 1.00, median 1.00, p90 2.60, max 3.40. The mean is 1.35.

The p10 to p90 band — 1.00 to 2.60 — is where ordinary rows live, and it is the pair worth quoting when somebody asks what to expect. Min and max describe the two strangest rows in the table and nothing else; they are useful for spotting impossible values and misleading for everything else.

select
  count(*)                           as rows,
  count(surge_multiplier)            as present,
  count(*) - count(surge_multiplier) as nulls,
  count(distinct surge_multiplier)   as distinct_values
from ride_hail_trips;

The mean sits 35% above the median, which is the whole story: anything that reports the average of surge_multiplier is reporting a number most rows are below. Put the median next to it or drop the mean.

Where this bites: a filter like surge_multiplier > 1.35 reads as "above average" and selects a minority of rows — a smaller minority than the phrase suggests to whoever asked for it. If the request was "the typical ones", the threshold they meant was 1.00.

The grain is one row per completed trip, which is the context every one of those numbers depends on. None of them survive a change of grain, which is why "profile the column" and "profile the table" are the same job. Full schema, and the CSV, on the dataset page.