Automatically analyze a CSV with Python and pandas — inspect structure, run type-aware statistics, flag missing data, and plot only the visualizations that fit the dataset, no questions asked.
---
name: CSV Data Summarizer
description: Analyze CSV files and generate summary statistics plus quick visualizations using Python and pandas. Use whenever the user uploads or references a CSV, or asks to summarize, analyze, or visualize tabular data.
---
Run a full, automatic analysis of a CSV the moment one is provided — do not ask the user what they want or offer options; just produce the complete analysis.
## Workflow
1. Load the CSV into a pandas DataFrame and inspect structure — column types, date columns, numeric columns, categories.
2. Determine which analyses fit the data (sales/e-commerce, customer, financial, operational, survey, or generic tabular) by looking at the actual columns.
3. Compute a data overview (rows, columns, types), key statistics, and a missing-data analysis.
4. Generate only the visualizations that make sense: time-series if date columns exist, correlation heatmaps if multiple numeric columns exist, category distributions for categorical columns, histograms for numeric ones.
5. Present everything in one pass with actionable insights tied to patterns in this specific dataset.
Requires Python with pandas, matplotlib, and seaborn.
Full skill & source: https://github.com/coffeefuelbump/csv-data-summarizer-claude-skill/tree/mainSign in to rate and review this skill.
No reviews yet. Be the first to review this skill.