Before you clip the outliers

A tail worth looking at rather than removing. wind_kph on city-air-quality tops out at 45.90 against a median of 9.90.

The max is 1.6× the 99th percentile and 6.8 standard deviations above the mean. The median is 9.90, so the top of this column lives in a different regime from the middle of it.

select *
from city_air_quality
order by wind_kph desc
limit 20;

Run that before deciding anything. There are three things an extreme value can be, and they need opposite treatment: a data error, a real but rare event, or a different population that got mixed into the same table. Only the first is safe to drop, and you cannot tell them apart from the summary statistics — you have to look at the rows.

A ratio this modest is consistent with an ordinary heavy tail — nothing anomalous, just a distribution that is not symmetric.

Clipping at the 99th percentile is a decision to discard your most interesting rows. Sometimes right. Never automatic, and never silent — if a number in a report was computed on clipped data, the report has to say so.