Analyze CSV and XLSX files to generate statistical profiles and visual insights.
npx skills add https://github.com/cheatcode-ai/cheatcode --skill csv-analyst
Please help me install this Agent Skill. Skill: csv-analyst Source: https://github.com/cheatcode-ai/cheatcode/tree/main/skills/csv-analyst Command: npx skills add https://github.com/cheatcode-ai/cheatcode --skill csv-analyst
This Skill eliminates the manual effort required to profile, clean, and visualize tabular data, allowing you to move from raw files to business insights without writing boilerplate code.
Ask the agent to analyze the uploaded sales data file and generate a summary of trends and key findings.
High-intent search queries and answers about installing and using this skill.
Statistical profiling and visual insights for a CSV file are generated by analyzing tabular data to produce row counts, missingness reports, and type distributions. The process creates reproducible charts and statistical summaries saved directly to your workspace.
Cohort analysis on spreadsheet data can be performed without manual Python coding by utilizing automated analysis scripts. You can analyze user retention data or identify outliers in financial datasets by asking the agent to process the uploaded files.
CSV analysis supports both CSV and XLSX file formats. It processes these tabular data files to provide data quality assessments, trend identification, and business intelligence insights.
The best way to assess data quality and missingness in a large dataset is through automated profiling. This process instantly generates missingness reports and type distributions, eliminating manual effort and identifying data gaps.
A sandbox environment with Python data processing tools is required to execute reproducible analysis scripts. This setup ensures that the statistical profiling and visual insights are generated reliably and audited.
Automated tabular data profiling is used instead of manual analysis to eliminate boilerplate code and manual effort. It allows you to move directly from raw files to actionable business insights by automating trend identification and statistical summaries.
Nabil-MabroukExecute Python code in a sandbox and inspect workspace CSV data.
saeed-vayghanAnalyzes raw data using SQL, Python, and BI tools for actionable insights and dashboard development.
cosmicdreamsAnalyze CSV files with pandas and generate statistical summaries and PNG charts.
finsilabsCreate interactive financial KPI dashboards with drill-down analysis and threshold-based alerts.
