csv-tools

name	csv-tools
description	Inspect, filter, aggregate, and clean CSV/TSV data with Python. Use when users hand over a .csv/.tsv file or paste tabular data and want a quick look, column stats, filtering, sorting, deduping, group-by sums/counts, or cleanup — without needing a full spreadsheet. Triggers on mentions of csv, tsv, columns, rows, filter, group by, aggregate, dedupe, clean data, 表格, 逗号分隔, 去重, 分组统计, 筛选.
license	Proprietary. LICENSE.txt has complete terms
compatibility	Requires python3. Works on macOS, Linux, and Windows.

CSV Tools

Use Python's stdlib csv (always available). Reach for pandas only if it's installed and the task is heavy (python3 -c "import pandas" to check first).

Peek: headers, row count, first rows

python3 - <<'PY'
import csv
with open('data.csv', newline='') as f:
    r = list(csv.reader(f))
print('cols:', r[0])
print('rows:', len(r)-1)
for row in r[1:4]: print(row)
PY

Filter rows by a column

python3 - <<'PY'
import csv
with open('data.csv', newline='') as f:
    for row in csv.DictReader(f):
        if row['status'] == 'active':
            print(row['id'], row['name'])
PY

Group-by aggregate (sum / count)

python3 - <<'PY'
import csv, collections
sums = collections.Counter()
with open('sales.csv', newline='') as f:
    for row in csv.DictReader(f):
        sums[row['region']] += float(row['amount'])
for k,v in sums.most_common():
    print(f'{k}: {v:.2f}')
PY

Dedupe / clean

python3 - <<'PY'
import csv
seen=set(); out=[]
with open('data.csv', newline='') as f:
    rd=csv.reader(f); header=next(rd)
    for row in rd:
        key=tuple(c.strip() for c in row)
        if key not in seen:
            seen.add(key); out.append(row)
with open('clean.csv','w',newline='') as f:
    w=csv.writer(f); w.writerow(header); w.writerows(out)
print('wrote', len(out), 'unique rows')
PY

Guidance

• Always check the delimiter (, vs \t vs ;) and whether there's a header row.
• Watch for quoted fields containing commas/newlines — csv handles them; manual splitting won't.
• Report a short summary (rows in/out, columns, key numbers), not the whole file.
• If the deliverable is a polished spreadsheet with formatting/charts, use the xlsx skill instead.