Group totals: maximum revenue is a different question

A group count adds 1 per record. A group total adds an amount from the record. A shop can have fewer bills yet more revenue if those bills are larger.

Replace increments with additions #

Totals = empty table
MaxRevenue = 0
For each bill X {
    store = X.Store
    If store has no total: Totals[store] = 0
    Totals[store] = Totals[store] + X.BillAmount
    if (Totals[store] > MaxRevenue) {
        MaxRevenue = Totals[store]
    }
}

Only the current store total changes. For nonnegative bill amounts, its total can only increase, so comparing that total against MaxRevenue maintains the best value in one pass. If negative refunds are allowed, a former leader can decrease; this shortcut needs rethinking rather than being applied blindly.

Distinguish four amounts #

Worked example with small bills #

A has more bills and final revenue 105; B has one bill with amount 100. Average bills are 105/3 = 35 for A and 100 for B. “Best store” must be defined by a chosen metric.

Apply the pattern to words #

Tutorial 2.4 sums LetterCount separately for every part of speech. This asks which category contributes the most letters, not simply the most word cards. From the supplied Words table, noun letters total 145, adjective letters 65, verb letters 35, preposition letters 27, article letters 18, pronoun letters 17, adverb letters 13 and conjunction letters 9.

Those category letter totals sum to 329, matching the whole paragraph. Nouns contribute the most letters. A category can be common but contain short words, so occurrence frequency and total letter contribution are distinct summaries.

Source: Lecture 2.5; Tutorial 2.4. Small teaching datasets and diagrams are prepared for these notes; lecture and tutorial totals are identified explicitly.