xlsx

name	xlsx
description	Create or edit spreadsheets (.xlsx) — data tables, financial models, budgets, trackers, cleaned/restructured tabular data. Trigger when a spreadsheet is the primary output, the user references an .xlsx/.csv by name, or asks for a model/budget/table as Excel. Not when the deliverable is a Word doc, PDF, or report.

XLSX — spreadsheets (Python runtime)

Build .xlsx files with openpyxl (formatting + formulas) and pandas (data wrangling) in the interpreter. Save to the workspace; it renders in the side panel. (No LibreOffice to recalc — Excel recalculates formulas when the file is opened.)

Requirements for every workbook

• Professional font (e.g. Calibri, Arial) consistently across the file.
• No known broken formulas — scan formula strings for invalid references and error literals. The sandbox cannot calculate formulas; Excel/Sheets recalculates them when opened.
• Use formulas for derived values, not source facts. Imported data and assumptions are hardcoded inputs; totals, ratios, forecasts, and checks should remain live formulas:
  • ✅ ws["B10"] = "=SUM(B2:B9)" · ✅ ws["C5"] = "=(C4-C2)/C2"
  • ❌ computing the total in Python and writing the number.
• Assumptions in their own cells, referenced by formulas: =B5*(1+$B$6), not =B5*1.05.
• When editing an existing file, match its conventions exactly — don't impose new formatting.

For a new workbook, establish a compact visual system: one structural header treatment tied to the subject or source brand, one input treatment, one accent/status color, clear section bands, deliberate column widths, frozen panes, filters, and number formats. Optimize for scanning and repeated use, not decoration.

Financial-model conventions (when modelling)

Color-code cell text so reviewers can read the model:

• Blue (0,0,255) — hardcoded inputs / assumptions a user changes.
• Black (0,0,0) — formulas and calculations.
• Green (0,128,0) — links to other sheets in the same workbook.
• Red (255,0,0) — links to external files.
• Yellow fill (255,255,0) — key assumptions needing attention.

Number formats:

• Years as text ("2024", not "2,024"); currency $#,##0 with units in the header ("Revenue ($mm)").
• Zeros shown as "-": "$#,##0;($#,##0);-". Percentages 0.0%. Multiples 0.0x. Negatives in parentheses (123).
• Document hardcodes in an adjacent cell: Source: [System], [Date], [Reference].

Build it

from openpyxl import Workbook
from openpyxl.styles import Font, PatternFill, Alignment

wb = Workbook(); ws = wb.active; ws.title = "Model"
BLUE = Font(name="Calibri", color="0000FF")
BLACK = Font(name="Calibri", color="000000")

ws["A1"] = "Revenue ($mm)"; ws["A1"].font = Font(bold=True)
ws["A2"], ws["B2"] = "Base", 100; ws["B2"].font = BLUE                 # input
ws["A3"], ws["B3"] = "Growth", 0.12; ws["B3"].font = BLUE; ws["B3"].number_format = "0.0%"
ws["A4"], ws["B4"] = "Year 2", "=B2*(1+B3)"; ws["B4"].font = BLACK     # formula
for cell in ("B2", "B4"):
    ws[cell].number_format = "$#,##0;($#,##0);-"
ws.column_dimensions["A"].width = 18
ws.freeze_panes = "A2"

wb.save("model.xlsx")
print("wrote model.xlsx")

• Multiple sheets: wb.create_sheet("Assumptions"). Charts: openpyxl BarChart/LineChart from cell ranges, or embed a matplotlib image. From a DataFrame: df.to_excel("out.xlsx", index=False) then reopen with openpyxl to format.
• Sensitivity tables: use an odd grid (5×5, 7×7) so the base case sits dead-center; highlight that center cell yellow.
• Editing an existing file: load_workbook("model.xlsx"), change what's needed, re-save; write cells without re-applying formats to preserve the existing look.

Before you finish

Check formula strings for #REF! / #DIV/0! / #VALUE! / #N/A / #NAME?; confirm ranges after row/column inserts; label every assumption and add a Source: note; confirm charts point at the intended ranges. Do not claim calculated values were verified in the sandbox.

Deliver

Save as <slug>.xlsx; one-line hand-off. To revise, open the saved file and modify it.