Python Idle
A local real-estate agency just handed you their sales database — and it's a mess. Rows with missing prices, duplicate listings that were entered twice, and columns stored as the wrong type. Before any analysis can begin, the data needs to be cleaned. Your job: turn this raw spreadsheet into a reliable, analysis-ready DataFrame. Welcome to the reality of data science.
~15 minscenario510 rows
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Goals: 5 tests
should create a cleaned DataFrame
should have no missing values
should have no duplicate rows
should have between 460 and 480 rows after cleaning
SalePrice should be numeric
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