Bytesagain Data Analytics
by @loutai0307-prog
Analyze CSV files with statistical summaries, correlations, and pivot tables. Use when exploring new datasets, checking data quality, finding column correlat...
clawhub install bytesagain-data-analyticsπ About This Skill
description: "Analyze CSV files with statistical summaries, correlations, and pivot tables. Use when exploring new datasets, checking data quality, finding column correlations, ranking top values, or charting trends." author: BytesAgain homepage: https://bytesagain.com source: https://github.com/bytesagain/ai-skills
bytesagain-data-analytics
Terminal data analysis toolkit for CSV files. Compute statistical summaries, correlation matrices, top value rankings, trend charts, data quality reports, and pivot tables β no Python data science libraries required.
Usage
bytesagain-data-analytics describe
bytesagain-data-analytics correlate
bytesagain-data-analytics top
bytesagain-data-analytics trend
bytesagain-data-analytics clean
bytesagain-data-analytics pivot
Commands
describe β Per-column statistics: count, mean, std, percentiles, top categoriescorrelate β Pearson correlation matrix across all numeric columnstop β Rank top 15 values in any column with percentage and bar charttrend β ASCII line chart showing value trend over rows with direction indicatorclean β Data quality report: null counts, low cardinality, coverage per columnpivot β Group by a category column and aggregate a numeric columnExamples
bytesagain-data-analytics describe sales.csv
bytesagain-data-analytics correlate metrics.csv
bytesagain-data-analytics top customers.csv country
bytesagain-data-analytics trend revenue.csv amount
bytesagain-data-analytics clean user-data.csv
bytesagain-data-analytics pivot orders.csv category revenue
Requirements
When to Use
Use when exploring a new dataset, checking data quality before analysis, finding correlations between metrics, or generating quick visual summaries from CSV exports without opening a spreadsheet.
β‘ When to Use
Use when exploring a new dataset, checking data quality before analysis, finding correlations between metrics, or generating quick visual summaries from CSV exports without opening a spreadsheet.
π‘ Examples
bytesagain-data-analytics describe sales.csv
bytesagain-data-analytics correlate metrics.csv
bytesagain-data-analytics top customers.csv country
bytesagain-data-analytics trend revenue.csv amount
bytesagain-data-analytics clean user-data.csv
bytesagain-data-analytics pivot orders.csv category revenue