Spreadsheet Manipulation Skill (xlsx)

Overview

This skill guides agents in manipulating Excel (.xlsx) spreadsheets using Python.

Primary libraries: openpyxl (structure-preserving read/write), pandas (data transformation). Never use any other third-party libraries.

Common Workflow

Explore the input file: list sheets, inspect headers, check dimensions.
Write solution.py with INPUT_PATH and OUTPUT_PATH defined at the top.
Execute python solution.py and verify the output file was created.
Confirm the target cells/range contain the expected values.

Library Selection

Use case	Library
Preserve formulas, formatting, named ranges	`openpyxl`
Bulk data transformation, aggregation, sorting	`pandas` → write back with `openpyxl`
Simple cell read/write	`openpyxl`

Warning: pandas.to_excel() silently destroys existing formulas and named ranges. When writing back to a spreadsheet that contains formulas, always use openpyxl.save().

solution.py Template

import openpyxl
import pandas as pd

INPUT_PATH  = "..."   # set to the actual input path
OUTPUT_PATH = "..."   # set to the actual output path

wb = openpyxl.load_workbook(INPUT_PATH)
ws = wb.active  # or wb["SheetName"]

# --- perform manipulation ---

wb.save(OUTPUT_PATH)

Output Requirements

Save the result to OUTPUT_PATH.
Do not hardcode row counts or column letters — iterate over actual rows in the workbook.
Preserve sheets and cells not mentioned in the instruction.

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