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Autoplot Skill自动数据可视化

Automatically visualize any data file (CSV/Excel/JSON) with one command. No coding required. Keywords: data visualization, chart generator, CSV plot, CSV vis...

personAuthor: zaosusuhubclawhub
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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

python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py --version

Visualize a file

# 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.

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.

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.

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

Month,Revenue,Profit,Customers
Jan,10000,3000,150
Feb,12000,4000,180
Mar,15000,5000,220

Command:

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:

python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py visualize survey.xlsx --chart-type pie

Output: Pie chart showing response distribution

Example 3: Interactive Dashboard

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

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

# Plot multiple columns
python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py visualize data.csv \
  --y-column Revenue,Profit,Expenses \
  --chart-type line

Aggregations

# Group by category and aggregate
python3 ~/.openclaw/workspace/autoplot/scripts/autoplot.py visualize data.csv \
  --group-by Category \
  --aggregate sum

Filtering

# 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

# 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

# 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:

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:

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