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Found 6 Skills
This skill should be used when working with CSV files to create interactive data visualizations, generate statistical plots, analyze data distributions, create dashboards, or perform automatic data profiling. It provides comprehensive tools for exploratory data analysis using Plotly for interactive visualizations.
Profile and explore datasets to understand their shape, quality, and patterns before analysis. Use when encountering a new dataset, assessing data quality, discovering column distributions, identifying nulls and outliers, or deciding which dimensions to analyze.
Comprehensive CSV data analysis and visualization tool. Use this skill when analyzing CSV files, generating data summaries, creating visualizations from data, detecting outliers, finding correlations, assessing data quality, or creating data reports. Triggers on CSV analysis, data exploration, data visualization, data profiling, statistical analysis, or data quality assessment requests.
Comprehensive data quality patterns using Great Expectations, DLT expectations, and custom validators for ensuring data reliability and trust.
EDA toolkit. Analyze CSV/Excel/JSON/Parquet files, statistical summaries, distributions, correlations, outliers, missing data, visualizations, markdown reports, for data profiling and insights.
Exploratory Data Analysis (EDA): profiling, visualization, correlation analysis, and data quality checks. Use when understanding dataset structure, distributions, relationships, or preparing for feature engineering and modeling.