Evals / tables / Filter and clean
Remove duplicate rows
Keep one row per Country Name in gdp.csv and save it as countries-once.csv.
The task
The reference answer shows the job can be done with deft. It is not an agent run.
deft sheet query gdp.csv --sql "select * from gdp group by [Country Name]" -o countries-once.csv
Input
| Country Name | Country Code | Year | Value |
| Afghanistan | AFG | 2000 | 3521418059.923445 |
| Afghanistan | AFG | 2001 | 2813571753.8725324 |
| Afghanistan | AFG | 2002 | 3825701438.9996333 |
| Afghanistan | AFG | 2003 | 4520946818.545814 |
| Afghanistan | AFG | 2004 | 5224896718.67782 |
| Afghanistan | AFG | 2005 | 6203256538.709669 |
| Afghanistan | AFG | 2006 | 6971758282.293506 |
| Afghanistan | AFG | 2007 | 9747886187.393929 |
| Afghanistan | AFG | 2008 | 10109297047.543194 |
| Afghanistan | AFG | 2009 | 12416152732.056717 |
| Afghanistan | AFG | 2010 | 15856668555.833595 |
| Afghanistan | AFG | 2011 | 17805098206.314083 |
| Afghanistan | AFG | 2012 | 19907329777.587166 |
| Afghanistan | AFG | 2013 | 20146416757.598675 |
| Afghanistan | AFG | 2014 | 20497128555.69723 |
| Afghanistan | AFG | 2015 | 19134221644.732494 |
| Afghanistan | AFG | 2016 | 18116572395.077213 |
| Afghanistan | AFG | 2017 | 18753456497.815865 |
| Afghanistan | AFG | 2018 | 18053222687.412624 |
| Afghanistan | AFG | 2019 | 18799444490.11278 |
| Afghanistan | AFG | 2020 | 19955929052.149597 |
| Afghanistan | AFG | 2021 | 14266499429.874573 |
| Afghanistan | AFG | 2022 | 14502158192.090395 |
Showing 24 of 4985 rows.
Reference output
| Country Name | Country Code | Year | Value |
| Afghanistan | AFG | 2000 | 3521418059.923445 |
| Africa Eastern and Southern | AFE | 1960 | 21216962289.557568 |
| Africa Western and Central | AFW | 1960 | 11884128412.35638 |
| Albania | ALB | 1984 | 1857337995.3379953 |
| Algeria | DZA | 1960 | 2723615451.3009768 |
| American Samoa | ASM | 2002 | 512000000.0 |
| Andorra | AND | 1970 | 78617711.09653251 |
| Angola | AGO | 1993 | 5879999999.999999 |
| Antigua and Barbuda | ATG | 1977 | 77496296.2962963 |
| Arab World | ARB | 1965 | 26772088212.098404 |
| Argentina | ARG | 1983 | 109490000000.0 |
| Armenia | ARM | 1990 | 2256863448.7708597 |
| Aruba | ABW | 1986 | 405586592.17877096 |
| Australia | AUS | 1960 | 18606562977.050076 |
| Austria | AUT | 1960 | 6650133914.547951 |
| Azerbaijan | AZE | 1990 | 8884848484.848484 |
| Bahamas, The | BHS | 1960 | 169803921.56862745 |
| Bahrain | BHR | 1970 | 391577364.829337 |
| Bangladesh | BGD | 1960 | 4274894083.3333335 |
| Barbados | BRB | 1960 | 80021380.2934078 |
| Belarus | BLR | 1992 | 9200000000.0 |
| Belgium | BEL | 1960 | 11810619368.387356 |
| Belize | BLZ | 1960 | 28072478.072478075 |
Showing 24 of 263 rows.
How a result is judged (1 check)
- python: code = "import csv; r = [x['Country Name'] for x in csv.DictReader(open('countries-once.csv'))]; assert len(r) == len(set(r)) and len(r) > 100"
Runs
CodexWithout deftPassed2026-11-07
- Time
- 14s
- New tokens
- 3.7k
- Total input
- 53.7k
- Output tokens
- 0.4k
- Commands
- 3
- Failed
- 0
Trace
I’ll check the CSV headers and duplicate country names, then write the deduplicated rows to `countries-once.csv` in the current directory.
pwd && rg --files -g 'gdp.csv' -g 'countries-once.csv'output
gdp.csv
python3 -c 'import csv; f=open(\"gdp.csv\",newline=\"\",encoding=\"utf-8-sig\"); r=csv.reader(f); print(next(r))'output
['Country Name', 'Country Code', 'Year', 'Value']
python3 -c 'import csv; from collections import Counter; src=\"gdp.csv\"; dst=\"countries-once.csv\"; f=open(src,newline=\"\",encoding=\"utf-8-sig\"); reader=csv.DictReader(f); rows=list(reader); seen=set(); unique=[] for row in rows: k=row[\"Country Name\"] if k not in seen: seen.add(k); unique.append(row) with open(dst,\"w\",newline=\"\",encoding=\"utf-8\") as out: w=csv.DictWriter(out,fieldnames=reader.fieldnames); w.writeheader(); w.writerows(unique) print(f\"rows={len(rows)} unique_countries={len(unique)} output={dst}\")'output
rows=13979 unique_countries=262 output=countries-once.csv
Saved [countries-once.csv](countries-once.csv) with one row per `Country Name` (262 rows). When a country appeared multiple times, I kept its first row in `gdp.csv`.
Output
| Country Name | Country Code | Year | Value |
| Afghanistan | AFG | 2000 | 3521418059.923445 |
| Africa Eastern and Southern | AFE | 1960 | 21216962289.557568 |
| Africa Western and Central | AFW | 1960 | 11884128412.35638 |
| Albania | ALB | 1984 | 1857337995.3379953 |
| Algeria | DZA | 1960 | 2723615451.3009768 |
| American Samoa | ASM | 2002 | 512000000.0 |
| Andorra | AND | 1970 | 78617711.09653251 |
| Angola | AGO | 1993 | 5879999999.999999 |
| Antigua and Barbuda | ATG | 1977 | 77496296.2962963 |
| Arab World | ARB | 1965 | 26772088212.098404 |
| Argentina | ARG | 1983 | 109490000000.0 |
| Armenia | ARM | 1990 | 2256863448.7708597 |
| Aruba | ABW | 1986 | 405586592.17877096 |
| Australia | AUS | 1960 | 18606562977.050076 |
| Austria | AUT | 1960 | 6650133914.547951 |
| Azerbaijan | AZE | 1990 | 8884848484.848484 |
| Bahamas, The | BHS | 1960 | 169803921.56862745 |
| Bahrain | BHR | 1970 | 391577364.829337 |
| Bangladesh | BGD | 1960 | 4274894083.3333335 |
| Barbados | BRB | 1960 | 80021380.2934078 |
| Belarus | BLR | 1992 | 9200000000.0 |
| Belgium | BEL | 1960 | 11810619368.387356 |
| Belize | BLZ | 1960 | 28072478.072478075 |
Showing 24 of 263 rows.
CodexWith deft, skill installedPassedRead the skillUsed deft2026-11-07
- Time
- 17s
- New tokens
- 9.3k
- Total input
- 86.2k
- Output tokens
- 0.5k
- Commands
- 5
- Failed
- 0
Trace
I’ll inspect the CSV header and duplicate counts, then write `countries-once.csv` with the first row kept for each Country Name.
pwd && rg --files -g 'gdp.csv' -g 'AGENTS.md' -g 'SKILL.md'output
gdp.csv
This is a CSV cleanup task, so I’m following the available `deft` file workflow while preserving the original row order.
cat .agents/skills/deft/SKILL.md && head -n 5 gdp.csvoutput
--- name: deft description: "Use deft instead of writing a script for file jobs: PDF merge/split/compress/watermark, image resize/convert/compress, video and audio trim/convert/compress, spreadsheets, Markdown to PDF/HTML, and YouTube downloads and subtitles." --- # 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, filters, montage, OCR - `video`: Trim, crop, speed, convert, compress, GIF, frames (ffmpeg) - `audio`: Convert, trim, merge, fade, speed, tag, normalize (ffmpeg) - `doc`: Word/ODT/RTF: to text, Markdown, HTML, PDF; find and replace - `slides`: PowerPoint: extract text, Markdown outline, PDF handout - `data`: JSON/YAML/TOML/XML: convert, query with jq syntax, merge, diff - `sheet`: Excel/CSV/ODS tables: filter, sort, join, pivot, convert - `md`: Markdown to PDF, HTML, Word, EPUB; table of contents - `html`: HTML to Markdown, text, Word, PDF; screenshots - `epub`: E-books: info, to text, Markdown and PDF - `email`: EML files: headers, text, attachments - `contact`: VCF address books: to and from CSV - `calendar`: ICS calendars: to and from CSV - `gps`: GPX and KML tracks: convert, distance and time - `youtube`: Info, download, audio, subtitles, thumbnail (yt-dlp) - `file`: Any file: hash, duplicates, batch rename, base64, encoding - `qr`: Cre … 923 more characters
deft sheetoutput
deft sheet - commands (input -> output) info sheet -> report Sheet names, rows, columns convert sheet -> sheet Change format: --to csv|xlsx|json dedupe sheet -> sheet Drop repeated rows, by whole row or --columns extract sheet -> sheet Take a sheet or range: --sheet, --range A1:D20 filter sheet -> sheet Keep matching rows: --where "age > 30 and city = 'Oslo'" from-pdf pdf -> sheet All text as one table [beta] group sheet -> sheet Group and total: --columns city --values sales --agg sum join sheet... -> sheet Join two tables on a key: --on id --how left merge sheet... -> sheet Stack tables; a shared header is kept once pivot sheet -> sheet Pivot table: --rows city --columns year --values sales query sheet|sqlite... -> sheet Run SQL over tables or a SQLite file: --sql 'select ...' select sheet -> sheet Keep, reorder or --drop columns sort sheet -> sheet Sort rows: --columns age,name --descending split sheet -> sheet... Split up: --sheets, --columns city or --every 1000 stats sheet -> report Per-column counts, empties, min, max, mean, sum to-md sheet -> md Markdown table (first row is the header) transpose sheet -> sheet Swap rows and columns More: deft sheet <command> --help
deft sheet dedupe --helpoutput
deft sheet dedupe - Drop repeated rows, by whole row or --columns Usage: deft sheet dedupe <sheet>... [-o <sheet|dir>] [options] In: sheet (each handled separately) Out: sheet (default <name>.deduped.<ext>) Options: --columns <text> Compare only these columns --keep <first|last> Which repeat stays (default first) --sheet <text> Sheet name or number (default: first) --to <csv|xlsx|json> Output format (default: like the input) Common: -o --force --dry-run --json -j (deft help common) Examples: deft sheet dedupe people.csv -o unique.csv deft sheet dedupe people.csv --columns name --keep last -o latest.csv Result fields: rows, columns, removed
deft sheet dedupe gdp.csv --columns 'Country Name' --keep first -o countries-once.csvoutput
ok sheet.dedupe gdp.csv -> countries-once.csv 13717 removed, 262 rows left 0.01s
Done. I kept the first row for each `Country Name` and saved the 262 remaining rows to [countries-once.csv](countries-once.csv).
Output
| Country Name | Country Code | Year | Value |
| Afghanistan | AFG | 2000 | 3521418059.923445 |
| Africa Eastern and Southern | AFE | 1960 | 21216962289.557568 |
| Africa Western and Central | AFW | 1960 | 11884128412.35638 |
| Albania | ALB | 1984 | 1857337995.3379953 |
| Algeria | DZA | 1960 | 2723615451.3009768 |
| American Samoa | ASM | 2002 | 512000000.0 |
| Andorra | AND | 1970 | 78617711.09653251 |
| Angola | AGO | 1993 | 5879999999.999999 |
| Antigua and Barbuda | ATG | 1977 | 77496296.2962963 |
| Arab World | ARB | 1965 | 26772088212.098404 |
| Argentina | ARG | 1983 | 109490000000.0 |
| Armenia | ARM | 1990 | 2256863448.7708597 |
| Aruba | ABW | 1986 | 405586592.17877096 |
| Australia | AUS | 1960 | 18606562977.050076 |
| Austria | AUT | 1960 | 6650133914.547951 |
| Azerbaijan | AZE | 1990 | 8884848484.848484 |
| Bahamas, The | BHS | 1960 | 169803921.56862745 |
| Bahrain | BHR | 1970 | 391577364.829337 |
| Bangladesh | BGD | 1960 | 4274894083.3333335 |
| Barbados | BRB | 1960 | 80021380.2934078 |
| Belarus | BLR | 1992 | 9200000000.0 |
| Belgium | BEL | 1960 | 11810619368.387356 |
| Belize | BLZ | 1960 | 28072478.072478075 |
Showing 24 of 263 rows.
Claude Opus 5.5Without deftPassed2026-11-07
- Time
- 29s
- New tokens
- 10.9k
- Total input
- 59.6k
- Output tokens
- 0.8k
- Commands
- 0
- Failed
- 0
Trace
Output
| Country Name | Country Code | Year | Value |
| Afghanistan | AFG | 2000 | 3521418059.923445 |
| Africa Eastern and Southern | AFE | 1960 | 21216962289.557568 |
| Africa Western and Central | AFW | 1960 | 11884128412.35638 |
| Albania | ALB | 1984 | 1857337995.3379955 |
| Algeria | DZA | 1960 | 2723615451.3009768 |
| American Samoa | ASM | 2002 | 512000000.0 |
| Andorra | AND | 1970 | 78617711.09653251 |
| Angola | AGO | 1993 | 5879999999.999999 |
| Antigua and Barbuda | ATG | 1977 | 77496296.2962963 |
| Arab World | ARB | 1965 | 26772088212.098404 |
| Argentina | ARG | 1983 | 109490000000.0 |
| Armenia | ARM | 1990 | 2256863448.77086 |
| Aruba | ABW | 1986 | 405586592.17877096 |
| Australia | AUS | 1960 | 18606562977.05008 |
| Austria | AUT | 1960 | 6650133914.547951 |
| Azerbaijan | AZE | 1990 | 8884848484.848484 |
| Bahamas, The | BHS | 1960 | 169803921.56862745 |
| Bahrain | BHR | 1970 | 391577364.829337 |
| Bangladesh | BGD | 1960 | 4274894083.3333335 |
| Barbados | BRB | 1960 | 80021380.2934078 |
| Belarus | BLR | 1992 | 9200000000.0 |
| Belgium | BEL | 1960 | 11810619368.387356 |
| Belize | BLZ | 1960 | 28072478.072478075 |
Showing 24 of 263 rows.
Claude Opus 5.5With deft, skill installedPassedRead the skillUsed deft2026-11-07
- Time
- 25s
- New tokens
- 12.4k
- Total input
- 109.5k
- Output tokens
- 1.4k
- 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
| Country Name | Country Code | Year | Value |
| Afghanistan | AFG | 2000 | 3521418059.923445 |
| Africa Eastern and Southern | AFE | 1960 | 21216962289.557568 |
| Africa Western and Central | AFW | 1960 | 11884128412.35638 |
| Albania | ALB | 1984 | 1857337995.3379953 |
| Algeria | DZA | 1960 | 2723615451.3009768 |
| American Samoa | ASM | 2002 | 512000000.0 |
| Andorra | AND | 1970 | 78617711.09653251 |
| Angola | AGO | 1993 | 5879999999.999999 |
| Antigua and Barbuda | ATG | 1977 | 77496296.2962963 |
| Arab World | ARB | 1965 | 26772088212.098404 |
| Argentina | ARG | 1983 | 109490000000.0 |
| Armenia | ARM | 1990 | 2256863448.7708597 |
| Aruba | ABW | 1986 | 405586592.17877096 |
| Australia | AUS | 1960 | 18606562977.050076 |
| Austria | AUT | 1960 | 6650133914.547951 |
| Azerbaijan | AZE | 1990 | 8884848484.848484 |
| Bahamas, The | BHS | 1960 | 169803921.56862745 |
| Bahrain | BHR | 1970 | 391577364.829337 |
| Bangladesh | BGD | 1960 | 4274894083.3333335 |
| Barbados | BRB | 1960 | 80021380.2934078 |
| Belarus | BLR | 1992 | 9200000000.0 |
| Belgium | BEL | 1960 | 11810619368.387356 |
| Belize | BLZ | 1960 | 28072478.072478075 |
Showing 24 of 263 rows.
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