CSV Formatting Skill

When to Use

Use this skill when creating, cleaning, or exporting CSV files from scraped data, database queries, or any structured output.

File Standards

Encoding & Format

• •UTF-8 encoding (no BOM)
• •Unix line endings (LF, not CRLF)
• •.csv extension

Headers

• •First row is always headers
• •Lowercase with underscores: company_name, job_title, date_posted
• •No spaces, no special characters
• •Short but descriptive

Delimiters

• •Use comma , as default delimiter
• •If data contains many commas, consider tab-delimited (.tsv)
• •Never mix delimiters in one file

Data Formatting

Text Fields

• •Wrap in double quotes if contains: comma, newline, or double quote
• •Escape double quotes by doubling: "She said ""hello"""
• •Trim leading/trailing whitespace
• •Empty string for missing values (not "N/A", "null", "None", or "-")

Numbers

• •No currency symbols: 49.99 not $49.99
• •No thousand separators: 1000000 not 1,000,000
• •Use period for decimals: 3.14
• •Empty for missing (not 0 unless zero is meaningful)

Dates

• •ISO 8601 format: 2025-01-13
• •Include time if relevant: 2025-01-13T14:30:00
• •Use UTC when timezone matters
• •Empty for missing dates (not "TBD" or "N/A")

URLs

• •Full URL with protocol: https://example.com
• •No trailing slashes unless meaningful
• •URL-encode special characters if needed

Boolean Values

• •Use lowercase: true, false
• •Or: yes, no
• •Pick one convention per file
• •Empty for unknown (not "maybe")

Lists Within Cells

• •Pipe-delimited: python|javascript|sql
• •Or semicolon: python;javascript;sql
• •Never comma (conflicts with CSV delimiter)
• •Document the convention in the first row or filename

Quality Checks

Before delivering a CSV:

1. •Open in text editor — verify no weird characters or encoding issues
2. •Check row count — matches expected data?
3. •Verify headers — all lowercase, no spaces?
4. •Spot check values — dates formatted? numbers clean?
5. •No trailing empty rows — delete blank lines at end
6. •Consistent columns — every row has same number of fields?

Common Mistakes to Avoid

Python Reference

import csv

# Writing
with open('output.csv', 'w', newline='', encoding='utf-8') as f:
    writer = csv.DictWriter(f, fieldnames=['company_name', 'website', 'price'])
    writer.writeheader()
    writer.writerows(data)

# Reading
with open('input.csv', 'r', encoding='utf-8') as f:
    reader = csv.DictReader(f)
    data = list(reader)

Naming Convention

{topic}_{date}.csv

Examples:
competitor_pricing_2025-01-13.csv
job_listings_2025-01-13.csv
scraped_companies_2025-01-13.csv

Delivery Checklist

• • UTF-8 encoded
• • Headers in first row, lowercase with underscores
• • No empty rows at end
• • Dates in ISO format
• • Numbers without formatting
• • Empty strings for missing values
• • Filename includes topic and date