Field note · December 26, 2025
Five minutes with duration_min in ride-hail-trips
8,000 rows, 792 distinct values, and the one fact about duration_min that changes how you query it.
Someone asked what is in duration_min on ride-hail-trips, and the honest answer took one query.
8,000 rows, no nulls, 792 distinct values. Wheels-moving duration in minutes.
The five-number version: min 1.30, p10 7.50, median 14.40, p90 40.30, max 130.00. The mean is 20.11.
The p10 to p90 band — 7.50 to 40.30 — 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(duration_min) as present,
count(*) - count(duration_min) as nulls,
count(distinct duration_min) as distinct_values
from ride_hail_trips;The mean sits 40% above the median, which is the whole story: anything that reports the average of duration_min is reporting a number most rows are below. Put the median next to it or drop the mean.
Where this bites: a filter like duration_min > 20.11 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 14.40.
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.