Skill: zaosusu/autoplot-skill (version 0.1.0)

--- name: autoplot-skill description: | Automatically visualize any data file (CSV/Excel/JSON) with one command. No coding required. Keywords: data visualization, chart generator, CSV plot, CSV visualization, Excel chart, JSON visualization, automatic graph, no-code visualization, data analysis, plot generator, 数据可视化, 图表生成, CSV画图, Excel转图表 Use this skill when: - "Visualize this CSV file" - "Visualize CSV data" - "Create a chart from this data" - "Create chart from Excel" - "Plot these sales numbers" - "Plot my data without coding" - "Show me trends in this dataset" - "Make a bar chart from this Excel file" - "Generate an infographic from this JSON" - "Make a graph from JSON" - "Analyze and visualize this data" - "CSV转图表" - "数据可视化" - "Excel画图" Auto-detects data types, selects optimal chart type (line, bar, scatter, pie, histogram), and generates publication-ready visualizations in PNG, SVG, HTML, PDF formats. metadata: openclaw: requires: bins: - python3 optional: - node # For interactive HTML output --- # AutoPlot - Automatic Data Visualization Transform any data file into beautiful charts with one command. No Python, no coding, just results. ## When to Use ✅ **Use this skill when:** - "Visualize this CSV file" - "Create a chart from this data" - "Plot these sales numbers" - "Show me trends in this dataset" - "Make a bar chart from this Excel file" - "Generate an infographic from this JSON" - "Analyze and visualize this data" ❌ **Don't use when:** - Real-time streaming data visualization - Complex statistical analysis (use dedicated tools) - 3D visualization (not supported yet) ## Features ### 1. Auto-Detection - **File format** - CSV, Excel (.xlsx/.xls), JSON - **Data types** - Numeric, categorical, datetime, text - **Relationships** - Correlations, trends, distributions ### 2. Smart Chart Selection | Data Pattern | Auto-Selected Chart | |-------------|---------------------| | Time series | Line chart with trend | | Categories + values | Bar chart | | Distributions | Histogram / Box plot | | Correlations | Scatter plot + regression | | Proportions | Pie / Donut chart | | Geographic | Map visualization | ### 3. Output Formats - **PNG** - Static image, email-ready - **SVG** - Scalable, web-ready - **HTML** - Interactive, zoom/pan/hover - **PDF** - Publication quality ### 4. Styling - Professional themes (default, minimal, dark) - Auto-color palettes - Responsive sizing - Annotations and labels ## Quick Start ### Check installation ```bash python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py --version ``` ### Visualize a file ```bash # Auto-detect and visualize python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py visualize data.csv # Specify output format python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py visualize sales.xlsx --format html # Custom title and theme python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py visualize metrics.json --title "Q4 Performance" --theme dark ``` ## Commands ### visualize Create visualization from data file. ```bash python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py visualize <file> [options] Options: --chart-type Override auto-detection (bar, line, scatter, pie, histogram, box) --x-column Specify X-axis column --y-column Specify Y-axis column --title Chart title --theme Visual theme (default, minimal, dark, colorful) --format Output format (png, svg, html, pdf) --output Output file path --width Chart width in pixels (default: 1200) --height Chart height in pixels (default: 800) ``` ### analyze Analyze data structure and suggest visualizations. ```bash python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py analyze <file> [options] Options: --detailed Show detailed statistics --sample N Show first N rows ``` ### dashboard Generate multi-chart dashboard. ```bash python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py dashboard <file> [options] Options: --charts N Number of charts to include --layout Layout style (grid, vertical, horizontal) ``` ## Examples ### Example 1: Sales Data Input: `sales.csv` ```csv Month,Revenue,Profit,Customers Jan,10000,3000,150 Feb,12000,4000,180 Mar,15000,5000,220 ``` Command: ```bash python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py visualize sales.csv --title "Q1 Sales Performance" ``` Output: - Line chart for Revenue/Profit trend - Bar chart for Customers by month - Correlation heatmap ### Example 2: Survey Results Input: `survey.xlsx` with categorical data Command: ```bash python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py visualize survey.xlsx --chart-type pie ``` Output: Pie chart showing response distribution ### Example 3: Interactive Dashboard ```bash python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py dashboard metrics.json --format html ``` Output: `metrics_dashboard.html` - Open in browser for interactive exploration ## Supported Data Formats ### CSV - Comma or tab delimited - Headers auto-detected - Date columns auto-parsed ### Excel - .xlsx and .xls - Multiple sheets (specify with --sheet) - Formulas evaluated ### JSON - Array of objects - Nested objects flattened - Metadata preserved ## Chart Types ### Available Charts - **Line** - Time series, trends - **Bar** - Comparisons, rankings - **Scatter** - Correlations, clusters - **Pie/Donut** - Proportions - **Histogram** - Distributions - **Box/Violin** - Statistical summaries - **Heatmap** - Correlation matrices - **Area** - Cumulative trends - **Bubble** - Multi-dimensional ### Auto-Selection Logic ``` if datetime_column: -> Line chart elif categorical + numeric: -> Bar chart elif two_numeric: if correlation_detected: -> Scatter + regression else: -> Scatter elif single_numeric: -> Histogram elif categorical_only: -> Count plot / Pie ``` ## Styling Options ### Themes - **default** - Clean, professional - **minimal** - No grid, minimal labels - **dark** - Dark background, neon colors - **colorful** - Vibrant palette - **print** - B&W optimized ### Customization ```bash python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py visualize data.csv \ --theme dark \ --title "Revenue Analysis" \ --width 1600 \ --height 900 ``` ## Output Examples ### PNG (Static) - Email attachments - Documents - Social media ### SVG (Vector) - Scalable without quality loss - Web embedding - Print materials ### HTML (Interactive) - Zoom and pan - Hover tooltips - Toggle data series - Export to PNG ### PDF (Publication) - Research papers - Reports - Presentations ## Advanced Usage ### Multi-Series Charts ```bash # Plot multiple columns python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py visualize data.csv \ --y-column Revenue,Profit,Expenses \ --chart-type line ``` ### Aggregations ```bash # Group by category and aggregate python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py visualize data.csv \ --group-by Category \ --aggregate sum ``` ### Filtering ```bash # Filter data before plotting python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py visualize data.csv \ --filter "Year >= 2020" \ --filter "Status = 'Active'" ``` ## Integration with OpenClaw ### In conversation ``` User: "Show me the trend in sales.csv" AI: [Uses autoplot to generate line chart] User: "Create a dashboard from this Excel file" AI: [Generates multi-chart HTML dashboard] ``` ### Batch processing ```bash # Visualize all CSV files in directory for file in *.csv; do python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py visualize "$file" done ``` ## Requirements - Python 3.8+ - pandas - plotly / matplotlib - openpyxl (for Excel files) ## Installation ```bash # Install dependencies pip install -r ~/.openclaw/workspace/autoplot/requirements.txt # Verify installation python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py --version ``` ## Troubleshooting ### Large datasets (>100k rows) Use sampling: ```bash python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py visualize big.csv --sample 10000 ``` ### Memory issues Process in chunks or use aggregation. ### Date parsing errors Specify date format: ```bash python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py visualize data.csv --date-format "%Y-%m-%d" ``` ## Roadmap - [ ] 3D visualization support - [ ] Animation/timelapse charts - [ ] Real-time data streaming - [ ] SQL database connections - [ ] Custom chart templates - [ ] API server mode ## License MIT License - See LICENSE file ## Credits Built with Plotly, Pandas, and OpenClaw


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)