Chartgen: Скилл для анализа и визуализации данных

--- name: chartgen description: | Chartgen skill providing three core functions: data analysis, data interpretation, and data visualization. **Use Cases**: (1) Data Analysis - Statistics, filtering, aggregation, calculation (e.g., "Calculate total sales", "Filter data greater than 100") (2) Data Interpretation - Trend analysis, pattern discovery, report generation (e.g., "Analyze sales trends", "Interpret data changes") (3) Data Visualization - Chart generation, data display (e.g., "Draw a bar chart", "Generate a pie chart") **Trigger Keywords**: analyze data, statistics, calculate, interpret trends, generate chart, visualize, plot **Prerequisites**: Set environment variable CHARTGEN_API_KEY (obtain from chartgen.ai) metadata: openclaw: requires: env: - CHARTGEN_API_KEY --- # ChartGen AI Chart Generator AI-powered chart generator that creates professional visualizations through natural language. Built on ChartGen AI engine. ## Overview Transform your data into stunning, interactive charts with simple natural language commands. No coding required - just describe the chart you want, and ChartGen AI generates it instantly. This skill supports Text-to-Chart, Text-to-SQL, and Text-to-Data analysis. Simply provide Excel/CSV files or JSON data, describe your visualization needs in plain language, and get interactive ECharts visualizations, structured analysis reports, and AI-driven insights. Powered by ChartGen AI engine, supporting multiple chart types including bar, line, pie, scatter, area, and more. Optimized for business analytics and data storytelling. **API Service**: This skill uses the ChartGen API service hosted at [chartgen.ai](https://chartgen.ai). All data is sent to `https://chartgen.ai/api/platform_api/` for processing. --- ## Quick Start ### 1. Apply for an API Key You can easily create and manage your API Key at [chartgen.ai](https://chartgen.ai). To begin with, you need to register for an account. **Steps:** 1. Visit [chartgen.ai](https://chartgen.ai) and sign up for an account 2. Access the API management dashboard 3. Create a new API and set the credit consumption limit 4. Copy the API Key for use ### 2. Configure Environment Variable ```bash export CHARTGEN_API_KEY="your-api-key-here" ``` ### 3. Run Scripts ```bash # Generate Chart (Text-to-Chart) python scripts/data_visualization.py --query "Draw a bar chart of sales by region" --file sales.xlsx # Data Analysis python scripts/data_analysis.py --query "Calculate total sales by region" --file sales.xlsx # Data Interpretation python scripts/data_interpretation.py --query "Analyze sales trends" --file sales.xlsx ``` --- ## Credit Rules - Calling a single tool consumes 20 credits - You get 200 free credits per month for free accounts - When credits run out, you can purchase more or upgrade your account on the [chartgen.ai Billing page](https://chartgen.ai/billing) --- ## Scripts Reference | Script | Function | Use Case | |--------|----------|----------| | `data_visualization.py` | Chart Generation | Text-to-Chart, create bar/line/pie/scatter charts | | `data_analysis.py` | Data Analysis | Statistics, filtering, aggregation, calculation | | `data_interpretation.py` | Insight Generation | Trend analysis, pattern discovery, report generation | --- ## Parameters ### Common Parameters | Parameter | Required | Description | |-----------|----------|-------------| | `--query` | Yes | Natural language query statement | | `--file` | No | Local file path (.xlsx/.xls/.csv), mutually exclusive with --json | | `--json` | No | JSON data (string or file path), mutually exclusive with --file | ### Visualization Specific Parameters | Parameter | Description | |-----------|-------------| | `--output, -o` | Output HTML file path (defaults to /tmp/openclaw/charts/) | --- ## Data Format ### File Format Supports `.xlsx`, `.xls`, `.csv` Excel and CSV files. Note: Only one of --file or --json is needed. If both are provided, --file takes precedence. File types support both row-metric-column data files and column-metric-row data files. ### JSON Format JSON data should be an array format, where each element is a row of data: ```json [ {"name": "Product A", "sales": 1000, "region": "East"}, {"name": "Product B", "sales": 1500, "region": "North"}, {"name": "Product C", "sales": 800, "region": "South"} ] ``` Or pass via file: ```bash python scripts/data_visualization.py --query "Draw a chart" --json data.json ``` --- ## Usage Examples ### Chart Generation (Text-to-Chart) ```bash # Bar chart python scripts/data_visualization.py --query "Draw a bar chart of sales by product" --file sales.xlsx # Line chart python scripts/data_visualization.py --query "Draw a line chart of sales trends" --file trends.xlsx # Pie chart python scripts/data_visualization.py --query "Draw a pie chart of sales by region" --file sales.xlsx # Scatter plot python scripts/data_visualization.py --query "Draw a scatter plot of price vs quantity" --file data.xlsx # Save to specific path python scripts/data_visualization.py --query "Draw a bar chart" --file data.xlsx -o /path/to/chart.html ``` ### Data Analysis ```bash # Statistical calculation python scripts/data_analysis.py --query "Calculate total and average sales by region" --file sales.xlsx # Data filtering python scripts/data_analysis.py --query "Filter products with sales greater than 1000" --file sales.xlsx # Sorting python scripts/data_analysis.py --query "Sort by sales in descending order" --file sales.xlsx ``` ### Insight Generation ```bash # Trend analysis python scripts/data_interpretation.py --query "Analyze monthly sales trends" --file monthly_sales.xlsx # Anomaly detection python scripts/data_interpretation.py --query "Find and explain anomalies in the data" --file data.xlsx # Comprehensive interpretation python scripts/data_interpretation.py --query "Provide a comprehensive analysis with key insights" --file report.xlsx ``` --- ## Supported Chart Types - Bar Chart / Stacked Bar Chart - Line Chart / Area Chart - Pie Chart / Donut Chart - Scatter Plot - And more... --- ## Output Description ### Chart Generation 1. **Console Output**: ECharts configuration JSON 2. **HTML File**: Interactive chart that can be opened in any browser ### Data Analysis & Insight Generation Returns Markdown format text results, including analysis conclusions, data tables, and insights. --- ## Error Handling Common errors and solutions: | Error Message | Cause | Solution | |---------------|-------|----------| | `CHARTGEN_API_KEY not set` | Environment variable not set | `export CHARTGEN_API_KEY="your-key"` | | `API request timeout` | Request timeout | Check network connection and retry | | `File not found` | File does not exist | Check if file path is correct | | `credits are insufficient` | Insufficient credits | Recharge or contact administrator | --- ## Technical Details - **API Base URL**: `https://chartgen.ai/api/platform_api/` - **Authentication**: Header `Authorization: <api-key>` - **Request Format**: JSON - **Timeout**: 60 seconds - **Required Environment Variable**: `CHARTGEN_API_KEY` See `scripts/chartgen_api.py` for implementation details. --- ## Privacy Notice **Data sent to remote API**: This skill reads your provided data files (CSV/XLSX/JSON), base64-encodes them, and sends them to the ChartGen API at `https://chartgen.ai/api/platform_api/` for analysis and chart generation. Your data will leave your machine. **Recommendations**: - Do not upload sensitive or regulated data - Use a dedicated API key with limited scope/credits - Review the privacy practices at [chartgen.ai](https://chartgen.ai) before use