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BytesAgain β€Ί Skills β€Ί Data Analyzer
πŸ¦€ ClawHub

Data Analyzer

by @yinanping-cpu

Data analysis and visualization skill for CSV, Excel, and JSON data. Use when analyzing sales data, creating reports, generating charts, or processing e-comm...

Versionv1.0.1
Downloads858
Installs4
#data#legal
TERMINAL
clawhub install yinan-data-analyzer

πŸ“– About This Skill

name: data-analyzer description: Data analysis and visualization skill for CSV, Excel, and JSON data. Use when analyzing sales data, creating reports, generating charts, or processing e-commerce analytics. Supports pivot tables, statistical analysis, and automated reporting.

Data Analyzer

Overview

Professional data analysis skill for OpenClaw. Analyze CSV, Excel, and JSON data with statistical functions, visualizations, and automated report generation.

Features

  • CSV/Excel/JSON data processing
  • Basic statistical analysis
  • HTML report generation
  • Group-by analysis
  • E-commerce data support

    • Quick Start

    Analyze Data

    python scripts/analyze_data.py \
  --input sales.csv \
  --output report.html \
  --group-by date

    Generate JSON Summary

    python scripts/analyze_data.py \
  --input orders.json \
  --output summary.json

    Scripts

    analyze_data.py

    Analyze CSV/Excel/JSON data and generate reports.

    Arguments:

  • --input - Input data file
  • --output - Output report file
  • --group-by - Group data by field
  • --metrics - Metrics to calculate (comma-separated)
  • --format - Output format (html, json)

    • E-commerce Analytics

    Taobao/Douyin Sales Analysis

    # Daily sales report
python scripts/analyze_sales.py \
  --input taobao_orders.csv \
  --output daily_report.html \
  --group-by product \
  --metrics revenue,quantity,profit
    Monthly trend analysis
    
python scripts/generate_charts.py \
  --input monthly_sales.json \
  --charts line \
  --x-axis month \
  --y-axis revenue

    Inventory Analysis

    python scripts/inventory_analysis.py \
  --input stock_levels.csv \
  --output inventory_report.xlsx \
  --alert-low-stock 10

    Customer Analytics

    python scripts/customer_analysis.py \
  --input customers.csv \
  --output customer_segments.html \
  --segment-by purchase_frequency

    Output Formats

    HTML Report

    Interactive report with charts and tables.

    Excel Workbook

    Multiple sheets with raw data, analysis, and charts.

    CSV Export

    Clean data for further processing.

    Templates

    Daily Sales Report

  • Total revenue
  • Order count
  • Top products
  • Hourly breakdown

    • Weekly Summary

  • Week-over-week comparison
  • Trend analysis
  • Top categories
  • Customer insights

    • Monthly Executive Report

  • KPI dashboard
  • Revenue breakdown
  • Growth metrics
  • Recommendations

    • Best Practices

    1. Clean data first - Remove duplicates, handle missing values 2. Validate inputs - Check data types and ranges 3. Use appropriate charts - Match chart type to data 4. Label clearly - Add titles, axis labels, legends 5. Export in multiple formats - HTML for viewing, CSV for further analysis

    Troubleshooting

  • Import errors: Install required packages (pandas, matplotlib)
  • Memory issues: Process large files in chunks
  • Chart rendering: Check output directory permissions
  • Date parsing: Ensure consistent date formats

    • πŸ’‘ Examples

    Analyze Data

    python scripts/analyze_data.py \
  --input sales.csv \
  --output report.html \
  --group-by date

    Generate JSON Summary

    python scripts/analyze_data.py \
  --input orders.json \
  --output summary.json

    πŸ“‹ Tips & Best Practices

    1. Clean data first - Remove duplicates, handle missing values 2. Validate inputs - Check data types and ranges 3. Use appropriate charts - Match chart type to data 4. Label clearly - Add titles, axis labels, legends 5. Export in multiple formats - HTML for viewing, CSV for further analysis