ariffazil/skills/csv-analyzer

CSV Analyzer

Analyze CSV/TSV files: statistics, data profiling, and visualizations.

Instructions

1. Read and detect: Identify delimiter (comma, tab, pipe), encoding, row count

2. Preview: Show first 5 rows as a formatted table

3. Profile each column:

   Numeric columns: count, mean, median, min, max, std dev, null count String columns: count, unique values, top 5 most frequent, avg length Date columns: min date, max date, range

4. Summary report:

   📊 CSV Analysis — data.csv
   Rows: 10,432 | Columns: 8 | Size: 2.1 MB
   
   | Column    | Type    | Non-null | Unique | Summary            |
   |-----------|---------|----------|--------|--------------------|
   | name      | string  | 10,432   | 8,721  | top: "John" (42)   |
   | age       | numeric | 10,210   | 82     | mean=34.2, σ=12.1  |
   | signup    | date    | 10,432   | 1,203  | 2020-01 to 2025-01 |
   

5. Visualizations (ASCII):

   # Histogram
   awk -F',' 'NR>1{print int($3/10)*10}' data.csv | sort -n | uniq -c | awk '{printf "%3d-%3d: %s (%d)\n", $2, $2+9, substr("████████████████████",1,$1/5), $1}'
   
   # Top values bar chart
   awk -F',' 'NR>1{print $2}' data.csv | sort | uniq -c | sort -rn | head -10
   

Edge Cases

• Large files (>100MB): Sample first 10,000 rows; report that sampling was used
• Quoted fields: Handle "field, with comma" correctly — use proper CSV parsing
• Mixed types: If a column has mixed numeric/string, classify as string
• Empty file: Report immediately; don't error out
• Encoding issues: Try UTF-8 first, fall back to Latin-1; report if issues detected

Requirements

• Standard Unix tools: awk, sort, uniq, wc, head
• No API keys or external dependencies