Csv Workbench

CSV Workbench

Use this skill when the user asks for quick analysis of tabular data.

Workflow

1. Inspect the CSV schema first (head, python csv.DictReader, or both). 2. Compute requested aggregates with a short Python script. 3. Return concise results with concrete numbers and units when available.

Constraints

• Prefer Python stdlib for portability.
• If data is missing or malformed, state assumptions clearly.
• Keep the final answer short and actionable.

CSV Playbook

Quick checks

• Preview rows: head -n 10 /mnt/data/your-file.csv.
• Count rows:

python - <<'PY'
import csv

with open('/mnt/data/your-file.csv', newline='') as f:
    print(sum(1 for _ in csv.DictReader(f)))
PY

Grouped totals template

python - <<'PY'
import csv
from collections import defaultdict

totals = defaultdict(float)
with open('/mnt/data/your-file.csv', newline='') as f:
    for row in csv.DictReader(f):
        totals[row['region']] += float(row['amount'])

for region in sorted(totals):
    print(region, round(totals[region], 2))
PY