Totals per group
Add up Value for each Year in gdp.csv and save the totals as per-year.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 Year, sum(Value) as Value from gdp group by Year order by Year" -o per-year.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
| Year | Value |
| 1960 | 9940146901453.5 |
| 1961 | 10431373800760.1 |
| 1962 | 11107920701138.8 |
| 1963 | 12024266177274.1 |
| 1964 | 13270687512845.4 |
| 1965 | 14556657260112.7 |
| 1966 | 15645181746578.9 |
| 1967 | 16580380159389.3 |
| 1968 | 17839694577457.9 |
| 1969 | 19728317147812 |
| 1970 | 21715158708429 |
| 1971 | 23903916492376.3 |
| 1972 | 27600409301028.3 |
| 1973 | 33850699517320.9 |
| 1974 | 39371484221204.9 |
| 1975 | 44176959007771.4 |
| 1976 | 47749276390027.4 |
| 1977 | 53958696974536.7 |
| 1978 | 63061369954035.3 |
| 1979 | 73955359933978.9 |
| 1980 | 84377400197205.5 |
| 1981 | 87317977608829.9 |
| 1982 | 85943726521367.9 |
Showing 24 of 65 rows.
How a result is judged (1 check)
- csv: file = "per-year.csv", columns = 2
Runs
CodexWithout deftPassed2026-11-07
- Time
- 13s
- New tokens
- 3.9k
- Total input
- 54.0k
- Output tokens
- 0.4k
- Commands
- 3
- Failed
- 0
Trace
I’ll inspect the CSV headers and rows, then sum `Value` by `Year` and write `per-year.csv` in the current directory.
pwd && rg --files -g 'gdp.csv' -g 'per-year.csv'output
gdp.csv
head -n 8 gdp.csv && wc -l gdp.csvoutput
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 13979 gdp.csv
python3 - <<'PY' import csv from collections import defaultdict from decimal import Decimal sums = defaultdict(Decimal) with open('gdp.csv', newline='', encoding='utf-8-sig') as f: reader = csv.DictReader(f) for row in reader: sums[row['Year']] += Decimal(row['Value']) with open('per-year.csv', 'w', newline='', encoding='utf-8') as f: writer = csv.writer(f) writer.writerow(['Year', 'Value']) for year in sorted(sums, key=int): writer.writerow([year, format(sums[year], 'f')]) print(f'Wrote {len(sums)} yearly totals to per-year.csv') PY head -n 5 per-year.csv && tail -n 3 per-year.csvoutput
Wrote 64 yearly totals to per-year.csv Year,Value 1960,9940146901453.497643636 1961,10431373800760.141361371 1962,11107920701138.818373020 1963,12024266177274.141863954 2021,804682961797170.21171958 2022,836222292702314.19790341 2023,869835019902455.581596936
Summed `Value` for each year and saved 64 yearly totals to [per-year.csv](per-year.csv).
Output
| Year | Value |
| 1960 | 9940146901453.497643636 |
| 1961 | 10431373800760.141361371 |
| 1962 | 11107920701138.818373020 |
| 1963 | 12024266177274.141863954 |
| 1964 | 13270687512845.441672564 |
| 1965 | 14556657260112.655892625 |
| 1966 | 15645181746578.892010217 |
| 1967 | 16580380159389.291262233 |
| 1968 | 17839694577457.922919765 |
| 1969 | 19728317147811.993456441 |
| 1970 | 21715158708428.957462811 |
| 1971 | 23903916492376.269630717 |
| 1972 | 27600409301028.3479189906 |
| 1973 | 33850699517320.9319518957 |
| 1974 | 39371484221204.889989758 |
| 1975 | 44176959007771.4258441205 |
| 1976 | 47749276390027.364261043 |
| 1977 | 53958696974536.7413766226 |
| 1978 | 63061369954035.330914486 |
| 1979 | 73955359933978.872732812 |
| 1980 | 84377400197205.496644574 |
| 1981 | 87317977608829.859647907 |
| 1982 | 85943726521367.918899881 |
Showing 24 of 65 rows.
CodexWith deft, skill installedPassedRead the skillUsed deft2026-11-07
- Time
- 15s
- New tokens
- 9.3k
- Total input
- 72.1k
- Output tokens
- 0.4k
- Commands
- 6
- Failed
- 0
Trace
I’ll inspect the CSV headers and rows, then write one summed total per year to `per-year.csv` in the current directory.
cat .agents/skills/deft/SKILL.mdoutput
--- 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 … 728 more characters
I’m applying the `deft` skill for this CSV task. I’ll check its table aggregation options and the input structure, then create the output.
head -5 gdp.csvoutput
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
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
rg --files -g 'gdp.csv' -g 'per-year.csv'output
gdp.csv
deft sheet group --helpoutput
deft sheet group - Group and total: --columns city --values sales --agg sum Usage: deft sheet group <sheet>... [-o <sheet|dir>] [options] In: sheet (each handled separately) Out: sheet (default <name>.grouped.<ext>) Without --values, counts the rows of each group. Options: --columns <text> Columns to group by (required) --values <text> Columns to aggregate --agg <sum|mean|count|min|max> How to combine values (default sum) --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 group sales.csv --columns city --values amount --agg mean -o totals.csv deft sheet group sales.csv --columns city,year -o counts.csv Result fields: rows, columnsdeft sheet group gdp.csv --columns Year --values Value --agg sum -o per-year.csvoutput
ok sheet.group gdp.csv -> per-year.csv 64 rows x 2 columns 0.02s
Created [per-year.csv](per-year.csv) with the sum of `Value` for each `Year` (64 years).
Output
| Year | Value_sum |
| 2000 | 248410805726630.47 |
| 2001 | 247580096430191.34 |
| 2002 | 257377252033461.8 |
| 2003 | 290307395862932.75 |
| 2004 | 329624586123499.4 |
| 2005 | 360547919545506.8 |
| 2006 | 395423460251844.8 |
| 2007 | 452558909234250.9 |
| 2008 | 504827157828119 |
| 2009 | 479835946119308.5 |
| 2010 | 532356740877791.56 |
| 2011 | 597862594560925.5 |
| 2012 | 613339581738808.1 |
| 2013 | 635449664774803.5 |
| 2014 | 654673772501479.9 |
| 2015 | 615964124156973 |
| 2016 | 624446095851665.4 |
| 2017 | 668487989564750.1 |
| 2018 | 711534474317183.9 |
| 2019 | 722421672807313.5 |
| 2020 | 701682453087538.1 |
| 2021 | 804682961797170.3 |
| 2022 | 836222292702314.5 |
Showing 24 of 65 rows.
Claude Opus 5.5Without deftPassed2026-11-07
- Time
- 16s
- New tokens
- 10.3k
- Total input
- 57.4k
- Output tokens
- 1.1k
- Commands
- 0
- Failed
- 0
Trace
Output
| Year | Value |
| 1960 | 9940146901453.496 |
| 1961 | 10431373800760.14 |
| 1962 | 11107920701138.814 |
| 1963 | 12024266177274.145 |
| 1964 | 13270687512845.441 |
| 1965 | 14556657260112.648 |
| 1966 | 15645181746578.889 |
| 1967 | 16580380159389.299 |
| 1968 | 17839694577457.918 |
| 1969 | 19728317147811.996 |
| 1970 | 21715158708428.97 |
| 1971 | 23903916492376.26 |
| 1972 | 27600409301028.36 |
| 1973 | 33850699517320.938 |
| 1974 | 39371484221204.89 |
| 1975 | 44176959007771.43 |
| 1976 | 47749276390027.38 |
| 1977 | 53958696974536.76 |
| 1978 | 63061369954035.336 |
| 1979 | 73955359933978.89 |
| 1980 | 84377400197205.53 |
| 1981 | 87317977608829.88 |
| 1982 | 85943726521367.94 |
Showing 24 of 65 rows.
Claude Opus 5.5With deft, skill installedPassedRead the skillUsed deft2026-11-07
- Time
- 16s
- New tokens
- 12.2k
- Total input
- 94.4k
- Output tokens
- 1.1k
- Commands
- 0
- Failed
- 0
Trace
Output
--- name: deft description: "Use deft first for any simple, direct operation on local files, whatever the type: convert, read, 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
| Year | Value |
| 1960 | 9940146901453.5 |
| 1961 | 10431373800760.1 |
| 1962 | 11107920701138.8 |
| 1963 | 12024266177274.1 |
| 1964 | 13270687512845.4 |
| 1965 | 14556657260112.7 |
| 1966 | 15645181746578.9 |
| 1967 | 16580380159389.3 |
| 1968 | 17839694577457.9 |
| 1969 | 19728317147812 |
| 1970 | 21715158708429 |
| 1971 | 23903916492376.3 |
| 1972 | 27600409301028.3 |
| 1973 | 33850699517320.9 |
| 1974 | 39371484221204.9 |
| 1975 | 44176959007771.4 |
| 1976 | 47749276390027.4 |
| 1977 | 53958696974536.7 |
| 1978 | 63061369954035.3 |
| 1979 | 73955359933978.9 |
| 1980 | 84377400197205.5 |
| 1981 | 87317977608829.9 |
| 1982 | 85943726521367.9 |
Showing 24 of 65 rows.
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