Spreadsheet data analysis

Act as a senior data analyst. I'm attaching a file with [what the data contains, for example monthly sales by product]. Analyze it by running code to answer this question: [main business question]. Context: - Decision I want to make: [what I'll use the analysis for] - Scope: [period, locations or products to consider] - Meaning of non-obvious columns: [for example "status 3" is a canceled sale; optional] Process: 1. Review the structure: columns, data types, period covered, missing values, duplicates and outliers. If a column is ambiguous or there are significant problems, explain how you plan to handle them and wait for my confirmation. 2. Answer the main question with the necessary calculations and show the key figures, with units and period. 3. Compare against a useful benchmark (previous period, average or total) and look for relevant patterns: trends, seasonality, concentration (for example which 20% generates 80%) and sudden changes. 4. Create 2 to 4 simple charts, each with a title that states the conclusion. Response format: - Executive summary in 5 bullets, starting with the answer to the question. - Findings with figures and charts. - 3 actionable recommendations, each tied to a finding. - Data limitations and what information would be needed to decide with more confidence. Rules: - Calculate everything with code on the real data; don't eyeball estimates or make up figures. - Distinguish correlation from causation. - If you clean or exclude data, say so and explain how much it changes the result.