Projects / Intermediate
What you end up with
A query that shows items and payments side by side and still says 9,200 yen. A per-customer table where a customer with no orders stays in with 0. And the query plan from before and after the index.
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Starting from a single orders CSV, you narrow down where sales are falling, working from the whole to the breakdown to one candidate. Using nothing but pandas aggregation, you finish with a one-page report holding a conclusion, its evidence, what the data cannot tell you, and one next step.
You build a pricing table of three plans that holds its shape from a 360px phone up to a wide screen. The aim is to let it wrap because the content is cramped, without writing a single @media rule.
You take a function that does not match its spec and fix it by writing a failing test first rather than diving in. You learn how to pick the boundaries, and what to leave behind once it is fixed.