Sn Da Excel Workflow

Excel Data Analysis Workflow

End-to-end workflow for structured Excel analysis. Each step maps to a capability sub-skill that can be loaded for detailed patterns.

Workflow

Step 1 — Count rows across all sheets (lightweight, no full load)

Count rows per sheet without loading data into memory. Use openpyxl read_only mode — this works for any file size.

import openpyxl, gc

wb = openpyxl.load_workbook(file_path, read_only=True, data_only=True)
total_rows = 0
sheet_info = {}
for name in wb.sheetnames:
    ws = wb[name]
    row_count = sum(1 for _ in ws.iter_rows(min_row=2, values_only=True))
    total_rows += row_count
    sheet_info[name] = row_count
    print(f"Sheet '{name}': {row_count} rows")
wb.close()
print(f"总行数={total_rows}")

⚠️ Do NOT use pd.read_excel() to count rows — it loads all data into memory, which will OOM on large files.

→ capability: excel-reading/multi-sheet-reading

Step 2 — Large file gate (CRITICAL — choose strategy by row count)