Reading population before trusting it in world-indicators

Profiling population on world-indicators before anyone builds anything on top of it.

720 rows, no nulls, 720 distinct values. Mid-year population.

The five-number version: min 4,154,889, p10 39,662,954, median 144,290,872, p90 195,716,782, max 260,257,217. The mean is 130,641,222.

The p10 to p90 band — 39,662,954 to 195,716,782 — 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(population)            as present,
  count(*) - count(population) as nulls,
  count(distinct population)   as distinct_values
from world_indicators;

Nothing dramatic: the mean and median are within 9.5% of each other, so an average is a fair summary. That is worth confirming rather than assuming — it is not true of most money columns.

Where this matters: a symmetric column is one you can average, threshold and chart without hedging, which makes it unusually cheap to work with. Knowing which of your columns are like this and which are not is most of knowing when to be careful.

The grain is one row per country per year, 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.