skills/claude-scientific-skills
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Improve thinking skills descriptions

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Timothy Kassis
2025-10-20 16:05:31 -07:00
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scientific-thinking/exploratory-data-analysis/SKILL.md
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name: exploratory-data-analysis
description: Comprehensive exploratory data analysis toolkit for data scientists. Use when users request data exploration, analysis of datasets, statistical summaries, data visualizations, or insights from data files. Handles multiple file formats (CSV, Excel, JSON, Parquet, etc.) and generates detailed markdown reports with statistics, visualizations, and automated insights. This skill should be used when analyzing any tabular data to understand patterns, distributions, correlations, outliers, and data quality issues.
description: Comprehensive exploratory data analysis (EDA) toolkit for analyzing datasets and generating actionable insights. Use this skill when users provide data files and request analysis, exploration, insights, or understanding of their data. Handles CSV, Excel (.xlsx/.xls), JSON, Parquet, TSV, Feather, HDF5, and Pickle files. Automatically performs statistical analysis including distributions, correlations, outlier detection, missing data patterns, and data quality assessment. Generates professional visualizations (histograms, box plots, correlation heatmaps, scatter matrices) and comprehensive markdown reports with automated insights. Key triggers: "analyze this data", "explore this dataset", "what's in this file", "data insights", "statistical summary", "data visualization", "EDA", "exploratory analysis", "data profiling", "understand my data", "find patterns", "data quality", "missing data", "outliers", "correlations", "distributions". Always outputs structured markdown reports with embedded visualizations and actionable recommendations.
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# Exploratory Data Analysis