back
loading skill details...
Automatically visualize any data file (CSV/Excel/JSON) with one command. No coding required. Keywords: data visualization, chart generator, CSV plot, CSV vis...
---
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
don't have the plugin yet? install it then click "run inline in claude" again.