Evals / tables / Analyse

Ask a table with SQL

Using gdp.csv, write the ten countries with the highest Value in 2015 to top.csv with the columns Country Name and Value.

normalsingledata-wranglingdeft sheet query

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 "Country Name", Value from gdp where Year = 2015 order by Value desc limit 10' -o top.csv

Input

gdp.csv 549.6 KB
Country NameCountry CodeYearValue
AfghanistanAFG20003521418059.923445
AfghanistanAFG20012813571753.8725324
AfghanistanAFG20023825701438.9996333
AfghanistanAFG20034520946818.545814
AfghanistanAFG20045224896718.67782
AfghanistanAFG20056203256538.709669
AfghanistanAFG20066971758282.293506
AfghanistanAFG20079747886187.393929
AfghanistanAFG200810109297047.543194
AfghanistanAFG200912416152732.056717
AfghanistanAFG201015856668555.833595
AfghanistanAFG201117805098206.314083
AfghanistanAFG201219907329777.587166
AfghanistanAFG201320146416757.598675
AfghanistanAFG201420497128555.69723
AfghanistanAFG201519134221644.732494
AfghanistanAFG201618116572395.077213
AfghanistanAFG201718753456497.815865
AfghanistanAFG201818053222687.412624
AfghanistanAFG201918799444490.11278
AfghanistanAFG202019955929052.149597
AfghanistanAFG202114266499429.874573
AfghanistanAFG202214502158192.090395

Showing 24 of 4985 rows.

Reference output

top.csv 361 B
Country NameValue
World75359657218242.52
High income49773105280474.15
OECD members47536673280840.75
Post-demographic dividend44669765037594.52
IDA & IBRD total27987288576613.15
IBRD only25838353087075.664
Low & middle income25326526306958.895
Middle income24911694910932.1
East Asia & Pacific21995274219766.668
Europe & Central Asia20481460301210.54
How a result is judged (1 check)
  • csv: file = "top.csv", rows = 11, columns = 2

Runs

CodexWithout deftPassed2026-11-07

Time
12s
New tokens
6.0k
Total input
53.8k
Output tokens
0.3k
Commands
3
Failed
0

Trace

  1. I’ll inspect `gdp.csv`, select the top ten 2015 values, and write just the requested columns to `top.csv` in the current directory.

  2. rg --files -g 'gdp.csv' -g 'AGENTS.md'
    output
    gdp.csv
  3. python3 -c 'import pandas as pd; d=pd.read_csv(\"gdp.csv\"); print(d.columns.tolist()); print(d.head(3).to_string(index=False))'
    output
    ['Country Name', 'Country Code', 'Year', 'Value']
    Country Name Country Code  Year        Value
     Afghanistan          AFG  2000 3.521418e+09
     Afghanistan          AFG  2001 2.813572e+09
     Afghanistan          AFG  2002 3.825701e+09
  4. python3 -c 'import pandas as pd; d=pd.read_csv(\"gdp.csv\"); x=d[d[\"Year\"]==2015].nlargest(10,\"Value\")[ [\"Country Name\",\"Value\"] ]; x.to_csv(\"top.csv\",index=False); print(x.to_string(index=False))'
    output
    Country Name        Value
                        World 7.535966e+13
                  High income 4.977311e+13
                 OECD members 4.753667e+13
    Post-demographic dividend 4.466977e+13
             IDA & IBRD total 2.798729e+13
                    IBRD only 2.583835e+13
          Low & middle income 2.532653e+13
                Middle income 2.491169e+13
          East Asia & Pacific 2.199527e+13
        Europe & Central Asia 2.048146e+13
  5. Created [top.csv](top.csv) with the ten highest 2015 `Value` rows and the requested columns. The source’s top rows include aggregates such as “World” and “High income.”

Output

top.csv 361 B
Country NameValue
World75359657218242.52
High income49773105280474.15
OECD members47536673280840.75
Post-demographic dividend44669765037594.52
IDA & IBRD total27987288576613.15
IBRD only25838353087075.664
Low & middle income25326526306958.895
Middle income24911694910932.1
East Asia & Pacific21995274219766.668
Europe & Central Asia20481460301210.54

CodexWith deft, skill installedPassedRead the skillUsed deft2026-11-07

Time
21s
New tokens
9.9k
Total input
102.9k
Output tokens
0.7k
Commands
9
Failed
0

Trace

  1. I’ll inspect `gdp.csv`, identify the 2015 values, and write the ten highest rows to `top.csv` in the current directory.

  2. cat .agents/skills/deft/SKILL.md
    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, 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, downlo
    … 849 more characters
  3. pwd && rg --files -g 'gdp.csv'
    output
    gdp.csv
  4. deft find "sort CSV rows by a column and select top 10 columns"
    output
    sheet sort     sheet -> sheet  Sort rows: --columns age,name --descending
    sheet select   sheet -> sheet  Keep, reorder or --drop columns
    sheet extract  sheet -> sheet  Take a sheet or range: --sheet, --range A1:D20
  5. head -n 4 gdp.csv
    output
    Country Name,Country Code,Year,Value
    Afghanistan,AFG,2000,3521418059.923445
    Afghanistan,AFG,2001,2813571753.8725324
    Afghanistan,AFG,2002,3825701438.9996333
  6. deft sheet select --help
    output
    deft sheet select - Keep, reorder or --drop columns
    
    Usage: deft sheet select <sheet>... [-o <sheet|dir>] [options]
    In: sheet (each handled separately)   Out: sheet (default <name>.selected.<ext>)
    
    Options:
      --columns <text>             Columns to keep, in this order
      --drop <text>                Columns to remove
      --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 select people.csv --columns age,name -o swapped.csv
      deft sheet select people.csv --drop age -o names.csv
    
    Result fields: rows, columns
  7. deft sheet sort --help
    output
    deft sheet sort - Sort rows: --columns age,name --descending
    
    Usage: deft sheet sort <sheet>... [-o <sheet|dir>] [options]
    In: sheet (each handled separately)   Out: sheet (default <name>.sorted.<ext>)
    Numbers sort as numbers; empty cells go last.
    
    Options:
      --columns <text>             Column names or numbers, comma-separated (required)
      --descending                 Largest 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 sort people.csv --columns age --descending -o ranked.csv
    
    Result fields: rows, columns
  8. deft find "filter CSV rows where a column equals a value"
    output
    sheet filter  sheet -> sheet  Keep matching rows: --where "age > 30 and city = 'Oslo'"
  9. The file has a `Year` column and numeric `Value` data. I’m filtering to 2015, sorting by `Value` descending, then selecting the requested two columns for the output.

  10. deft sheet filter gdp.csv --where "Year = 2015" -o <tmp> && deft sheet sort <tmp> --columns Value --descending -o <tmp> && deft sheet extract <tmp> --range A1:D11 -o <tmp> && deft sheet select <tmp> --columns "Country Name,Value" -o top.csv
    output
    ok sheet.filter gdp.csv -> <tmp>  258 rows x 4 columns  0.01s
    ok sheet.sort <tmp> -> <tmp>  258 rows x 4 columns  0.00s
    ok sheet.extract <tmp> -> <tmp>  11 rows x 4 columns  0.00s
    ok sheet.select <tmp> -> top.csv  10 rows x 2 columns  0.00s
  11. cat top.csv
    output
    Country Name,Value
    World,75359657218242.52
    High income,49773105280474.15
    OECD members,47536673280840.75
    Post-demographic dividend,44669765037594.52
    IDA & IBRD total,27987288576613.15
    IBRD only,25838353087075.664
    Low & middle income,25326526306958.895
    Middle income,24911694910932.1
    East Asia & Pacific,21995274219766.668
    Europe & Central Asia,20481460301210.54
  12. Created [top.csv](top.csv) with the ten highest 2015 `Value` rows and the requested columns.

Output

top.csv 361 B
Country NameValue
World75359657218242.52
High income49773105280474.15
OECD members47536673280840.75
Post-demographic dividend44669765037594.52
IDA & IBRD total27987288576613.15
IBRD only25838353087075.664
Low & middle income25326526306958.895
Middle income24911694910932.1
East Asia & Pacific21995274219766.668
Europe & Central Asia20481460301210.54

Claude Opus 5.5Without deftPassed2026-11-07

Time
15s
New tokens
12.0k
Total input
62.1k
Output tokens
1.1k
Commands
0
Failed
0

Trace

    Output

    top.csv 297 B
    Country NameValue
    United States18295019000000.0
    China11061572618578.693
    Japan4444930651964.18
    Germany3357585719351.5605
    United Kingdom2927911140916.7314
    France2439188643162.4985
    India2103588360044.3894
    Italy1836637711060.546
    Brazil1802212206904.6777
    Canada1556508816217.1401

    Claude Opus 5.5With deft, skill installedPassedRead the skillUsed deft2026-11-07

    Time
    16s
    New tokens
    13.3k
    Total input
    79.7k
    Output tokens
    1.3k
    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
      
      top.csv 286 B
      Country NameValue
      United States18295019000000.0
      China11061572618578.693
      Japan4444930651964.18
      Germany3357585719351.5605
      United Kingdom2927911140916.7314
      France2439188643162.4985
      India2103588360044.3894
      Italy1836637711060.546
      Brazil1802212206904.6777
      Canada1556508816217.1401

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