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csv-data-visualizer

Create interactive Plotly visualizations and statistical reports from CSV files.

19|5|Updated Nov 23, 2025
Search Tags:#data visualization#dashboard#data analysis#csv#plotly#data profiling
One-click install
npx skills add https://github.com/Nir-Bhay/markups --skill csv-data-visualizer-nir-bhay
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: csv-data-visualizer
Source: https://github.com/Nir-Bhay/markups/tree/main/.agents/skills/csv-data-visualizer
Command: npx skills add https://github.com/Nir-Bhay/markups --skill csv-data-visualizer-nir-bhay

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, plotly, numpy, kaleido, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill transforms raw CSV data into insightful visualizations and comprehensive reports, making data analysis accessible and efficient.

Core Features & Use Cases

  • Interactive Visualizations: Create histograms, scatter plots, box plots, line charts, bar charts, and more using Plotly.
  • Data Profiling: Generate detailed statistical summaries and data quality reports.
  • Dashboard Creation: Automatically or custom-build multi-plot dashboards for a holistic view of your data.
  • Use Case: Upload a CSV of customer sales data and ask the AI to "Create a dashboard showing sales trends by region and product category, and profile the data for quality issues."

Quick Start

Use the csv-data-visualizer skill to create a histogram of the 'age' column from the attached file 'customer_data.csv'.

Frequently Asked Questions about csv-data-visualizer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create an interactive dashboard from a CSV file?▼

You can create interactive dashboards from a CSV file by using this tool to automatically generate multi-plot layouts with histograms, scatter plots, and line charts via Plotly and Pandas. This provides a holistic view of your data for exploratory analysis.

What is automatic data profiling for CSV analysis?▼

Automatic data profiling generates detailed statistical summaries and data quality reports directly from CSV files. It highlights quality issues and statistical distributions to support exploratory data analysis without manual calculation.

Can I use Plotly to generate presentation-ready visualizations from CSV data?▼

Yes, Plotly generates presentation-ready visualizations from CSV data by creating interactive histograms, box plots, and bar charts. These visualizations support statistical reporting and exploratory data analysis directly from your dataset.

Does this data visualization approach support exploratory data analysis with Pandas?▼

Yes, this approach supports exploratory data analysis using Pandas. It leverages Pandas and NumPy to process CSV files, generating statistical summaries, interactive plots, and comprehensive data quality reports for exploratory workflows.

What is the best way to visualize CSV data quality issues?▼

The best way to visualize CSV data quality issues is by generating automatic data profiling reports alongside multi-plot dashboards. This combines detailed statistical summaries with interactive Plotly visualizations to highlight anomalies and data problems.

What types of interactive plots can I generate for CSV data analysis?▼

For CSV data analysis, you can generate interactive histograms, scatter plots, box plots, line charts, and bar charts using Plotly. These visualizations can be combined into custom multi-plot dashboards for comprehensive statistical reporting.

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