Clean a dataset into a report

CodexWithout deftPassed2026-11-07

Time

58s

New tokens

15.7k

Total input

115.2k

Output tokens

2.7k

Commands

7

Failed

2

Trace

1. I’ll inspect the two CSVs, match GDP rows against the country list, then write the sorted 2015 workbook in the current directory.

2. ls -la && rg --files
   output

   total 1112
   drwxr-xr-x@    4 user  staff     128 Nov  6 16:41 .
   drwx------@ 1698 user  staff   54336 Nov  6 16:41 ..
   -rw-r--r--@    1 user  staff    3835 Nov  5 21:11 countries.csv
   -rw-r--r--@    1 user  staff  562767 Nov  5 21:11 gdp.csv
   gdp.csv
   countries.csv

3. python3 -c 'import csv; from pathlib import Path;\\nfor f in [\"countries.csv\",\"gdp.csv\"]:\\n with open(f, newline=\"\", encoding=\"utf-8-sig\") as x:\\n rd=csv.reader(x); print(f, next(rd)); print(next(rd))' (exit 1)
   output

   File "<string>", line 1
       import csv; from pathlib import Path;\nfor f in ["countries.csv","gdp.csv"]:\n with open(f, newline="", encoding="utf-8-sig") as x:\n  rd=csv.reader(x); print(f, next(rd)); print(next(rd))
                                             ^
   SyntaxError: unexpected character after line continuation character

4. python3 - <<'PY' import csv for f in ['countries.csv','gdp.csv']: with open(f, newline='', encoding='utf-8-sig') as x: rd=csv.reader(x) print(f, next(rd)) print(next(rd)) PY
   output

   countries.csv ['Name', 'Code']
   ['Afghanistan', 'AF']
   gdp.csv ['Country Name', 'Country Code', 'Year', 'Value']
   ['Afghanistan', 'AFG', '2000', '3521418059.923445']

5. python3 - <<'PY' import csv for f in ['countries.csv','gdp.csv']: with open(f,newline='',encoding='utf-8-sig') as fp: rows=list(csv.DictReader(fp)) print(f,len(rows),rows[:3]) if f=='gdp.csv': print([x for x in rows if x['Year']=='2015'][:4]) PY
   output

   countries.csv 249 [{'Name': 'Afghanistan', 'Code': 'AF'}, {'Name': 'Albania', 'Code': 'AL'}, {'Name': 'Algeria', 'Code': 'DZ'}]
   gdp.csv 13979 [{'Country Name': 'Afghanistan', 'Country Code': 'AFG', 'Year': '2000', 'Value': '3521418059.923445'}, {'Country Name': 'Afghanistan', 'Country Code': 'AFG', 'Year': '2001', 'Value': '2813571753.8725324'}, {'Country Name': 'Afghanistan', 'Country Code': 'AFG', 'Year': '2002', 'Value': '3825701438.9996333'}]
   [{'Country Name': 'Afghanistan', 'Country Code': 'AFG', 'Year': '2015', 'Value': '19134221644.732494'}, {'Country Name': 'Africa Eastern and Southern', 'Country Code': 'AFE', 'Year': '2015', 'Value': '899295676086.8356'}, {'Country Name': 'Africa Western and Central', 'Country Code': 'AFW', 'Year': '2015', 'Value': '769367317617.821'}, {'Country Name': 'Albania', 'Country Code': 'ALB', 'Year': '2015', 'Value': '11386853113.0189'}]

6. The files use country names plus two-letter codes in `countries.csv`, while GDP uses three-letter codes. I’ll use exact country-name matches to exclude regional aggregates, and preserve the GDP three-letter code in the output.

7. python3 - <<'PY' import csv from pathlib import Path from openpyxl import Workbook with open('countries.csv', newline='', encoding='utf-8-sig') as f: country_names = {row['Name'].strip() for row in csv.DictReader(f)} rows = [] with open('gdp.csv', newline='', encoding='utf-8-sig') as f: for row in csv.DictReader(f): if row['Year'].strip() "'!= '"'2015' or row['Country Name'].strip() not in country_names: continue try: value = float(row['Value']) except (TypeError, ValueError): continue rows.append((row['Country Name'].strip(), row['Country Code'].strip(), value)) rows.sort(key=lambda row: row[2], reverse=True) wb = Workbook() ws = wb.active ws.title = 'GDP 2015' ws.append(['Country Name', 'Code', 'Value']) for row in rows: ws.append(row) ws.freeze_panes = 'A2' ws.auto_filter.ref = ws.dimensions ws.column_dimensions['A'].width = 34 ws.column_dimensions['B'].width = 12 ws.column_dimensions['C'].width = 20 for cell in ws['C'][1:]: cell.number_format = '#,##0.00' wb.save('gdp-2015.xlsx') print(f'Wrote {len(rows)} countries to {Path(\"gdp-2015.xlsx\").resolve()}') if rows: print('Largest:', rows[0]) print('Smallest:', rows[-1]) PY (exit 1)
   output

   Traceback (most recent call last):
     File "<stdin>", line 3, in <module>
   ModuleNotFoundError: No module named 'openpyxl'

8. python3 - <<'PY' for m in ['xlsxwriter','pandas','odf']: try: mod=__import__(m); print(m,'available') except Exception as e: print(m,'unavailable') PY command -v libreoffice || command -v soffice || true command -v R || true
   output

   xlsxwriter unavailable
   pandas available
   odf unavailable

9. python3 - <<'PY' import csv, zipfile from pathlib import Path from xml.sax.saxutils import escape with open('countries.csv', newline='', encoding='utf-8-sig') as f: countries = {r['Name'].strip() for r in csv.DictReader(f)} rows=[] with open('gdp.csv', newline='', encoding='utf-8-sig') as f: for r in csv.DictReader(f): if r['Year'].strip() == '2015' and r['Country Name'].strip() in countries: try: value=float(r['Value']) except (ValueError, TypeError): continue rows.append((r['Country Name'].strip(), r['Country Code'].strip(), value)) rows.sort(key=lambda r:r[2], reverse=True) def col(n): return chr(64+n) def inline_cell(ref, value): return f'<c r=\"{ref}\" t=\"inlineStr\"><is><t>{escape(str(value))}</t></is></c>' def num_cell(ref, value): return f'<c r=\"{ref}\" s=\"1\"><v>{value:.15g}</v></c>' xml_rows=[] xml_rows.append('<row r=\"1\">'+''.join(inline_cell(f'{col(i)}1',v) for i,v in enumerate(['Country Name','Code','Value'],1))+'</row>') for ri,(name,code,value) in enumerate(rows,2): xml_rows.append(f'<row r=\"{ri}\">{inline_cell(f\"A{ri}\",name)}{inline_cell(f\"B{ri}\",code)}{num_cell(f\"C{ri}\",value)}</row>') sheet='''<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"yes\"?> <worksheet xmlns=\"http://schemas.openxmlformats.org/spreadsheetml/2006/main\"><sheetViews><sheetView workbookViewId=\"0\"><pane ySplit=\"1\" topLeftCell=\"A2\" activePane=\"bottomLeft\" state=\"frozen\"/></sheetView></sheetViews><cols><col min=\"1\" max=\"1\" width=\"34\" customWidth=\"1\"/><col min=\"2\" max=\"2\" width=\"12\" customWidth=\"1\"/><col min=\"3\" max=\"3\" width=\"20\" customWidth=\"1\"/></cols><sheetData>'''+''.join(xml_rows)+'''</sheetData><autoFilter ref=\"A1:C'''+str(len(rows)+1)+'''\"/></worksheet>''' … 3193 more characters
   output

   Wrote 184 countries. Largest: United States (18295019000000.00)
   -rw-r--r--@ 1 user  staff  8257 Nov  6 16:42 gdp-2015.xlsx

10. Created [gdp-2015.xlsx](gdp-2015.xlsx) with 184 countries, matched by name against `countries.csv`, and sorted by 2015 GDP from largest to smallest. The `Code` column uses the three-letter codes from `gdp.csv`.

Output

Claude Opus 5.5Without deftPassed2026-11-07

Time

29s

New tokens

15.9k

Total input

67.1k

Output tokens

2.2k

Commands

0

Failed

0

Trace

Output

---
name: deft
description: "Use deft first for any simple, direct operation on local files, whatever the type: create, convert, read, query, extract, edit, compress, merge, split, compare or inspect. Try it before writing a script or one-liner. If unsure, run deft find; if it says no command does this, use another tool. Not for programming work: to read, write or change source code, skip it."
---

# deft

One local command for file jobs. Prefer it over writing Python or shell scripts.

Syntax: `deft <group> <command> [inputs] [-o output] [--options]`

Groups:
- `pdf`: Merge, split, compress, encrypt, forms, OCR, compare, convert
- `image`: Resize, crop, convert, compress, adjust, montage, OCR
- `video`: Trim, merge, convert, compress, subtitles, GIF, frames (ffmpeg)
- `audio`: Convert, trim, normalize, denoise, cut silence (ffmpeg)
- `doc`: Word/ODT/RTF: to text, Markdown, HTML, PDF; find and replace
- `slides`: PowerPoint: extract text, Markdown outline
- `sheet`: Excel/CSV/ODS tables: SQL query, pivot, merge, split, convert
- `json`: JSON: convert, format, merge, diff, validate
- `toml`: TOML: convert, format, merge, diff, validate
- `xml`: XML: convert, format, merge, diff, validate
- `yaml`: YAML: convert, format, merge, diff, validate
- `md`: Markdown to PDF, HTML, Word, EPUB; table of contents
- `html`: HTML to Markdown, text, Word and PDF
- `epub`: E-books: info, to text, Markdown and PDF
- `gps`: GPX and KML tracks: convert, distance and time
- `qr`: Create QR codes and barcodes; read QR codes

How to use it:
1. Run `deft <group>` to list commands, or `deft find "<what you want>"` to search. If it says `no command does this`, use another tool.
2. Run `deft <group> <command> --help` for options and examples.
3. `deft convert <in> -o <out.ext>` converts between formats by extension.
4. Results are one line starting with `ok`, `partial` or `error`; add `--json` to parse them. Errors include a `hint:` with the fix.

Inputs are never overwritten; pass `--force` or `--in-place` to allow it. Globs and directories work as inputs; several inputs run in parallel.

If `deft` is not installed, ask the user, then follow https://github.com/firstprayer/deft/blob/main/docs/INSTALL.md