spreadsheet

name	spreadsheet
description	Read, write, and transform CSV and XLSX files. Use for Excel, tabular data, bulk row edits, and column transforms.

Spreadsheet skill

When to use

• User mentions CSV, Excel, XLSX, or tabular/spreadsheet data
• User wants to filter, transform, aggregate, or reformat rows/columns
• User wants to convert between CSV and XLSX
• User wants to inspect, summarize, or fix a data file

When NOT to use

• The file is a database (SQLite, PostgreSQL) — use data-analysis skill or execute_shell with sqlite3
• The file is a JSON/log — use data-analysis skill
• The user wants to edit a Word document — use docx skill

Procedure

1. Identify the file path and format (CSV or XLSX). Run scripts/csv_inspect.py or scripts/xlsx_to_csv.py first to understand structure.
2. For CSV: use Python stdlib csv module via run_code.
3. For XLSX: check if openpyxl is available. If not, install via execute_shell: pip install --user openpyxl. Then use run_code.
4. Read the header row first before writing any transforms.
5. Write output to a new file (don't overwrite the original unless the user asks).
6. Report row count and first few rows to confirm correctness.

Recipes

Inspect CSV (dialect, header, first 5 rows):

import csv, sys
path = "/path/to/file.csv"
with open(path, newline="", encoding="utf-8-sig") as f:
    dialect = csv.Sniffer().sniff(f.read(4096))
    f.seek(0)
    reader = csv.DictReader(f, dialect=dialect)
    rows = []
    for i, row in enumerate(reader):
        if i >= 5:
            break
        rows.append(row)
print("Header:", reader.fieldnames)
print("Rows:", rows)

Filter CSV rows where column equals value:

import csv
with open("in.csv", newline="") as fin, open("out.csv", "w", newline="") as fout:
    reader = csv.DictReader(fin)
    writer = csv.DictWriter(fout, fieldnames=reader.fieldnames)
    writer.writeheader()
    for row in reader:
        if row["status"] == "active":
            writer.writerow(row)

Read XLSX sheet:

import openpyxl
wb = openpyxl.load_workbook("/path/to/file.xlsx", read_only=True, data_only=True)
ws = wb.active
for row in ws.iter_rows(values_only=True):
    print(row)
wb.close()

Write XLSX:

import openpyxl
wb = openpyxl.Workbook()
ws = wb.active
ws.append(["Name", "Score"])
ws.append(["Alice", 95])
wb.save("/path/to/output.xlsx")

Convert CSV to XLSX: Use the bundled scripts/xlsx_to_csv.py (in reverse) or write directly:

import csv, openpyxl
wb = openpyxl.Workbook()
ws = wb.active
with open("data.csv", newline="") as f:
    for row in csv.reader(f):
        ws.append(row)
wb.save("data.xlsx")

Pitfalls

• XLSX files with formulas: data_only=True reads the cached value (may be stale if never opened in Excel). Never modify formulas by editing cell values — use openpyxl formula strings.
• CSV encoding: use utf-8-sig to handle BOM from Excel exports.
• Large files (>100k rows): prefer read_only=True in openpyxl; use csv.DictReader (streaming) not readlines().
• run_code Python is stdlib-only. openpyxl is a third-party package — install via execute_shell first.
• Newlines inside CSV cells require the csv module — never parse CSV by hand with split(",").
• Do not overwrite the original file without explicit user consent.

References

• scripts/csv_inspect.py — inspect CSV dialect, header, row count, first 5 rows
• scripts/xlsx_to_csv.py — convert XLSX to CSV