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Pandas Data Manipulation Rules

Listed
oimiragieo·vlatest·data

Applies complex data cleaning, transformation, and analysis rules using pandas for structured datasets.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add oimiragieo/agent-studio --skill pandas-data-manipulation-rules -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

oimiragieo

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

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scanned

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Not scanned. none of the 73 skills in the repository match this slug — it was most likely renamed or removed upstream after the registry indexed it Source recorded as oimiragieo/agent-studio.
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About this skill

What it does

This skill allows AI agents to manipulate and analyze data using the pandas library in Python. It can perform operations like filtering rows based on conditions, calculating new columns derived from existing ones, grouping data for aggregation, and applying custom functions to datasets. The agent can also handle missing values and reformat data structures.

When to use it

  • Analyzing sales data to identify top-performing products or regions.
  • Cleaning and preparing customer data for marketing campaigns by removing duplicates and correcting errors.
  • Calculating summary statistics (mean, median, standard deviation) from a dataset of experimental results.
  • Transforming raw log files into structured tables for easier analysis.

Key capabilities

  • Data filtering based on conditions
  • Column creation and modification
  • Grouping and aggregation
  • Custom function application
  • Handling missing values

Example prompts

  • "Filter this CSV file to show only rows where the 'price' column is greater than $50."
  • "Create a new column called 'total_cost' by multiplying the 'quantity' and 'unit_price' columns."
  • "Group this data by 'category' and calculate the average 'rating'."

Tips & gotchas

  • Requires Python and the pandas library to be installed in the agent’s environment.
  • The skill relies on well-structured data, typically in CSV or tabular format. Incorrectly formatted input may lead to errors.