Field note · August 3, 2025
Five minutes with passengers in ride-hail-trips
8,000 rows, 6 distinct values, and the one fact about passengers that changes how you query it.
Someone asked what is in passengers on ride-hail-trips, and the honest answer took one query.
8,000 rows, no nulls, 6 distinct values. Riders in the vehicle, 1–6.
The five-number version: min 1, p10 1, median 1, p90 4, max 6. The mean is 2.
The p10 to p90 band — 1 to 4 — 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(passengers) as present,
count(*) - count(passengers) as nulls,
count(distinct passengers) as distinct_values
from ride_hail_trips;The mean sits 77% above the median, which is the whole story: anything that reports the average of passengers is reporting a number most rows are below. Put the median next to it or drop the mean.
Where this bites: a filter like passengers > 2 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.
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.