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displaying-streamlit-data

Display dataframes, tables, metrics, and charts in Streamlit apps.

1|1|Updated Nov 9, 2025
Search Tags:#data visualization#charts#streamlit#dataframe#altair#data editor
One-click install
npx skills add https://github.com/Paldom/databricks-apps-streamlit-vibe-coding-starter --skill displaying-streamlit-data-paldom
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: displaying-streamlit-data
Source: https://github.com/Paldom/databricks-apps-streamlit-vibe-coding-starter/tree/main/.agents/skills/developing-with-streamlit/skills/displaying-streamlit-data
Command: npx skills add https://github.com/Paldom/databricks-apps-streamlit-vibe-coding-starter --skill displaying-streamlit-data-paldom

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you present data clearly and effectively within Streamlit applications, making your data understandable and actionable for users.

Core Features & Use Cases

  • Diverse Data Display: Choose from interactive dataframes, editable data editors, static tables, and key metrics.
  • Native & Custom Charts: Utilize Streamlit's built-in charts or leverage Altair for complex visualizations.
  • Enhanced Data Presentation: Configure columns with specific formatting, links, images, and progress bars for better readability.
  • Use Case: Displaying sales figures in a table with formatted currency, showing progress on project completion with progress bars, and visualizing daily revenue trends with a line chart.

Quick Start

Use the displaying-streamlit-data skill to show a dataframe with a 'Revenue' column formatted as currency and a 'Completion' column as a progress bar.

Frequently Asked Questions about displaying-streamlit-data

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

FAQPage Schema
How do I display a dataframe in Streamlit with formatted columns like currency and progress bars?▼

To display a dataframe in Streamlit with formatted columns, use column configuration options to apply specific formatting like currency, links, images, and progress bars, enhancing readability and making the data more actionable.

Can I create complex data visualizations in Streamlit using Altair?▼

Yes, you can create complex data visualizations in Streamlit using Altair. It supports leveraging Altair alongside native Streamlit charts for interactive and static data presentation, allowing for advanced charting beyond basic built-in options.

What is the difference between a static table and an interactive data editor in Streamlit?▼

A static table in Streamlit presents data without editing capabilities, while an interactive data editor allows users to modify data directly. The data editor supports options like column configuration and pinning for enhanced data management.

Does Streamlit support editing data directly within a displayed dataframe?▼

Yes, Streamlit supports editing data directly within a displayed dataframe using the data editor component. This feature allows interactive data modification with options for column configuration and pinning to manage the editing workflow.

What's the best way to show key metrics and daily revenue trends in a Streamlit app?▼

The best way to show key metrics and daily revenue trends in Streamlit is by combining key metrics display elements with native or Altair charts. Visualize daily revenue trends with a line chart and display sales figures using formatted metrics.

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