Five quiet mistakes with the wrong kind
Nothing here throws an error. Every line gives an answer that looks reasonable and is wrong.
Data comes in four kinds: quantitative (amounts), ordinal (ordered labels), categorical (unordered labels) and time. The kind decides what you may do with a column: sort it, average it, compare it, or only count it.
Change the code and press Run (Ctrl+Enter). Predict what will happen first, then break it on purpose and read what changes. Your edits are saved and match the lesson page.
Ready for more? This phase has 4 hands-on exercises with automatic checks.
Practice questions
Write the code in the editor, run it, then open the model answer to compare.
Write isNumberColumn(values) that returns true only if every non-empty value converts to a finite number and none starts with a zero followed by another digit (like "07790"). Test with ["12", "20"], ["07790", "09250"], ["S01", "S02"].
Write meanOf(values) for an array of strings that returns the mean of the numeric ones, skips empty strings and "n/a", and returns null when nothing numeric is left. Test with ["1539", "1519", "1950", "", "1915"] and ["", "n/a"].
Explain it without notes
Name the four kinds of data and one Lumen column for each.
Why is a station ID such as S01 not a number even though it contains digits?
Why is a missing value not the same as zero? Give a Lumen example.
Console
(nothing was printed)Expected console output
1. dates sorted as text: [ '13/03/2025', '2025-03-02', '2025-03-09', '2025-03-10' ]
2. weekdays sorted as text: [ 'Fri', 'Mon', 'Sat', 'Sun', 'Thu', 'Tue', 'Wed' ]
weekdays in their real order: [ 'Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun' ]
3. empty cell read as a number: 0 -> mean 1384.6
empty cell left out: mean 1730.75
4. an ID as a number: 7790 - and back to text: 7790
5. numbers sorted without a compare function: [ 2979, 3742, 439 ]
numbers sorted properly: [ 439, 2979, 3742 ]