A Python-powered data visualization tool that converts CSV files into customizable PNG or SVG charts.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install chart-mpl
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install chart-mpl using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Chart MPL?
Chart MPL is a high-performance data visualization utility designed for the Openclaw Skills ecosystem. It leverages the power of matplotlib to transform static tabular data from CSV files into clear, professional-grade visual representations including line, bar, scatter, and area charts.
Built for developers and data analysts, this skill automates the rendering process, handling complex data cleaning tasks such as delimiter auto-detection, BOM-encoding, and varied numeric formatting (US/EU). Whether you are generating individual reports or integrating charts into a multi-agent workflow, Chart MPL provides the precision and flexibility required for modern BI-ready image exports.
Chart MPL Use Cases
- Generating Monthly Trend reports from financial CSV exports.
- Visualizing database query results by piping CSV outputs from SQL agents.
- Creating stacked bar charts to compare multi-series sales or performance data.
- Producing SVG assets for high-resolution documentation or dashboards.
- Automatically filtering and displaying top N categories in large datasets for cleaner pie and bar charts.
How Chart MPL Works
- The skill accepts a CSV file path along with defined X and Y axis columns.
- It parses the data using a robust engine that detects delimiters and handles localized number formats (dots or commas).
- Depending on the specified kind (e.g., stacked, area, or hbar), the script applies the necessary matplotlib transformations.
- Visual enhancements like human-readable axis ticks (K, M, G suffixes) and color palettes are applied to the series.
- The final visualization is rendered and saved as a PNG or SVG file to the exports directory.
Chart MPL Setup
To use this within the Openclaw Skills framework, set up a dedicated virtual environment and install the required dependencies:
# Create a virtual environment
python3 -m venv ~/.openclaw/workspace/.venv_chart
# Install matplotlib
~/.openclaw/workspace/.venv_chart/bin/pip install matplotlib
Chart MPL Data Schema & Taxonomy
Chart MPL processes CSV inputs and generates image outputs. The data mapping is structured as follows:
| Attribute | Description |
|---|---|
| --csv | Path to the source CSV file. |
| --xcol | The column used for the X-axis (categories/time). |
| --ycol | Comma-separated list of numeric columns for the Y-axis. |
| --kind | The chart format (line, bar, hbar, pie, stacked, scatter, area). |
| --out | Output path; format (PNG/SVG) is determined by extension. |
| --numfmt | Numeric localization: 'fr' (1,5M) or 'en' (1.5M). |
Chart MPL Advanced Features
- Multi-Series Support: Automatically generates legends and cycles through 8-color palettes for complex comparisons.
- Intelligent Data Filtering: Use the --top N flag to aggregate smaller slices into an 'Other' category in pie charts or filter bar charts.
- Automated Data Cleaning: Built-in support for utf-8-sig BOM encoding and automatic conversion of non-numeric values to NaN.
- Flexible Sorting: Options for x-asc, x-desc, and y-desc to organize data before the rendering phase.
- Seamless Integration: Designed to work end-to-end with SQL skills for automated database-to-chart pipelines.
SKILL.md
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