csv-profiler
Skill48 starsChanged 17 days agoMITView on GitHub
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.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- berriosb/data-analytics-agentstheir own version, first seen Oct 20, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- berriosb/data-analytics-agents★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository15 other files it gives its agents.
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The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 18
Before cleaning, joining or plotting data, to find empty columns and mixed types.
- Distinctive: line 19
When a script fails on a column and the user suspects bad values.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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 tabThe 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
missingcount needs a decision: drop it, fill it, or ask the user. - A
stringcolumn whoseuniquecount is close torowsis probably an identifier. - A
stringcolumn 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.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.