Analyze messy datasets to produce insights, charts, and data-driven reports.
npx skills add https://github.com/CellCog/cellcog_python --skill data-cog
Please help me install this Agent Skill. Skill: data-cog Source: https://github.com/CellCog/cellcog_python/tree/main/skills/data-cog Command: npx skills add https://github.com/CellCog/cellcog_python --skill data-cog
CellCog's Data Cog helps you transform messy or under-specified datasets into actionable insights by automating data cleaning, exploration, and reporting, so you can derive meaningful conclusions faster.
Analyze a provided dataset to generate an interactive dashboard and a concise summary report.
High-intent search queries and answers about installing and using this skill.
To clean messy CSV data and generate exploratory data analysis charts, this Skill automates data cleaning, handles missing values, and creates visualizations like distributions and correlations to produce actionable insights.
Yes, you can analyze JSON and SQL exports to create interactive dashboards. The workflow supports these common formats to generate charts, summarize stats, and build stakeholder review interfaces.
The best way to profile dataset quality and readiness for machine learning is to run dataset profiling and simple ML evaluations, assessing data completeness and distributions directly within an automated workflow.
Yes, this data analysis workflow supports Python-based hypothesis testing. It leverages Python workflows to perform cleaning, statistical testing, and model evaluation across your datasets.
To transform Excel columns and fix data formats for reporting, the Skill cleans under-specified XLSX files, normalizes columns, and generates concise summary reports for data-driven conclusions.
cmetechIngest CSV, Excel, or JSON files and analyze them with SQL to produce dashboards, reports, or datasets.
zivtechAudit charts, dashboards, and infographics for statistical honesty and accessibility.
koki3141Automate statistical analysis and visualization of experimental results in Python.
JayRHaClean messy tabular datasets with pandas using auditable transformation steps.
