A comprehensive data science skill for loading, cleaning, and performing statistical analysis on CSV datasets with automated visualization.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ub2-csv-data-analyzer
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 ub2-csv-data-analyzer 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 CSV Data Analyzer?
The CSV Data Analyzer is a sophisticated tool designed to turn raw comma-separated values into meaningful business intelligence. By leveraging this addition to the catalog of Openclaw Skills, users can automate the tedious aspects of data science, such as identifying schema structures, detecting missing values, and generating descriptive statistics.
This skill acts as a bridge between static data files and dynamic interpretation, allowing your AI agent to act as a junior data scientist. It provides the logical framework needed to parse complex datasets, perform multi-variable analysis, and generate professional-grade charts, ensuring that data-driven decisions are backed by rigorous statistical evidence.
CSV Data Analyzer Use Cases
- Analyzing sales records to identify high-growth product categories and revenue trends.
- Detecting statistical outliers and data anomalies in scientific or industrial sensor logs.
- Generating automated visual reports including bar charts, histograms, and scatter plots for presentations.
- Cleaning messy datasets by standardizing formats and handling null values before migration.
How CSV Data Analyzer Works
- The user uploads or references a CSV file and provides a natural language prompt for analysis.
- The skill performs an initial data inspection to identify column headers, data types, and file integrity.
- Statistical operations are executed to calculate means, medians, standard deviations, and correlations.
- Filtering and grouping logic is applied to segment the data based on the specific user query.
- Insights are summarized in plain language, and requested visualizations are rendered as high-quality image files.
CSV Data Analyzer Setup
To use this skill, ensure your environment has Python 3.x installed along with the necessary data processing libraries. You can install the required dependencies using the following command:
pip install pandas matplotlib
Once installed, place your CSV files in a directory accessible by your agent to begin the analysis process.
CSV Data Analyzer Data Schema & Taxonomy
The CSV Data Analyzer organizes its output to ensure maximum clarity and reusability for other Openclaw Skills.
| Output Type | Description | Format |
|---|---|---|
| Data Summary | Statistics including count, mean, and percentiles | Markdown Table |
| Visualizations | Generated charts such as bar, line, or scatter plots | PNG Files |
| Cleaned Data | Exported dataset after handling nulls or duplicates | CSV File |
| Insights | Text-based interpretations of data patterns | Plain Text |
CSV Data Analyzer Advanced Features
- Correlation Analysis: Automatically calculates relationships between numeric variables to find hidden dependencies.
- Custom Delimiter Support: Flexibly handles non-standard data formats including TSV and semicolon-separated files.
- Automated Data Cleaning: Intelligent detection and resolution of type inconsistencies and missing values.
- Extensible Visualization: Supports various plot types to best represent the underlying data distribution, integrated seamlessly with other Openclaw Skills.
SKILL.md
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