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…egation in Excel Co-authored-by: muumuu8181 <87556753+muumuu8181@users.noreply.github.com>
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| # Format | ||
| summary['average_salary'] = summary['average_salary'].astype(int) |
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Keep average_salary as a true average
Casting average_salary to int truncates fractional values from the group mean, which systematically underreports department averages whenever totals are not evenly divisible by employee count. This silently corrupts the aggregation result the script is meant to produce; keep the float or round explicitly instead of truncating.
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| output_file = 'employee_data.xlsx' | ||
| print(f"Saving to {output_file}...") | ||
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| with pd.ExcelWriter(output_file, engine='openpyxl') as writer: |
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Avoid hard-coding the Excel writer engine
Forcing engine='openpyxl' makes the script fail in environments where openpyxl is not installed, even if pandas could otherwise write .xlsx using another available engine. Since this commit adds no dependency declaration for openpyxl, this choice introduces an avoidable runtime failure mode for users running the script.
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Added a Python script
generate_employee_data.pythat generates 1000 records of synthetic employee data across 3 tables (Departments, Employees, Salaries) and performs aggregation (count, average, sum by department). The output is saved toemployee_data.xlsx.PR created automatically by Jules for task 7361334929024047645 started by @muumuu8181