A mean is a summary, and summaries hide the shape of the data. One huge value can move a mean by ten times while the median does not move. Look at the distribution before you quote an average.
About 1 min of reading
See a mean hide an outlier.
Compute both
Before you run it, say out loud what it will print. Then open the answer.
Percentiles
Before you run it, say out loud what it will print. Then open the answer.
Before you write anything, put these lines back in the right order. Click a line to move it up one step. This support step is easier than writing code from scratch, and it is here to make the last example stick.
Read the first example one line at a time. A line that prints shows what appears on screen; the rest set things up quietly.
A real extreme is a finding; a unit error is a bug. Check the source of the biggest values before deciding. Dismissing a real outlier with an automatic rule throws away the interesting part of the data.
When values span three orders of magnitude, a linear chart puts everything in one bar and one spike. A log scale makes ratios readable, and labelling it as log prevents a reader reading it as a normal bar.
For [1,2,3,4,1000] the mean is 202 and the median is 3. Both are correct and only one is useful. Quote both when they differ, because the difference is the finding.
'p50 is 4, p95 is 90, max is 1200' says more than 'mostly small with a few big ones'. Percentiles are checkable numbers, so two people can agree on the description instead of arguing about a word.
Sort descending and look at the top ten before any statistics. A single input error, a unit mistake, or a duplicate row shows up there, and it changes every summary you were about to publish.
Each one is defined here on this site. Open the entry for the full definition and the other words it points at.