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csv-profiler

Profiles a CSV file column by column, reporting inferred type, missing values, unique counts and min, max and mean for numeric columns. Use when the user hands over a CSV and asks what is in it, whether the data is clean, or what to check before analysis.

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Lethe044/agentskill-kit48 stars(GitHub 48 + cccskills 0)

Run score Not tested

See how to install

Files included (3)

  • SKILL.md1.6 KB
  • scripts/profile_csv.py2.7 KB
  • tests/cases.json1.3 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

CSV profiler

Gives an agent a reliable picture of a CSV file before it writes any analysis code.

When to use

  • The user uploads or points to a CSV and asks "what is in this file?".
  • Before cleaning, joining or plotting data, to find empty columns and mixed types.
  • When a script fails on a column and the user suspects bad values.

How to run

python scripts/profile_csv.py data.csv
python scripts/profile_csv.py data.tsv --delimiter tab

The delimiter is detected automatically when it is not given. Use --delimiter tab for tab separated files.

Output

JSON with rows, columns and a profile list. Each column has name, type (integer, float, boolean, date, string or empty), missing, unique, sample and, for numeric columns, min, max and mean.

Reading the result

  • A column with a large missing count needs a decision: drop it, fill it, or ask the user.
  • A string column whose unique count is close to rows is probably an identifier.
  • A string column with few unique values is a good candidate for a categorical type.
  • Report surprises first: mixed types, empty columns, duplicated headers.

Errors

A missing file exits with code 2. A file with no rows returns rows: 0.

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