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displaying-streamlit-data

Render Streamlit charts, dataframes, and metrics with native APIs.

Updated Feb 19, 2026
Search Tags:#charts#metrics#streamlit#dataframe#data-visualization#sparkline#altair
One-click install
npx skills add https://github.com/guihousun/NTL-GPT-Clone --skill displaying-streamlit-data-guihousun
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: displaying-streamlit-data
Source: https://github.com/guihousun/NTL-GPT-Clone/tree/main/skills/developing-with-streamlit/skills/displaying-streamlit-data
Command: npx skills add https://github.com/guihousun/NTL-GPT-Clone --skill displaying-streamlit-data-guihousun

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Visualizing data inside Streamlit apps can be time-consuming when you need to turn raw data into clear charts, tables, and KPI metrics. This Skill provides a guided approach to rendering charts, dataframes, and sparklines with Streamlit-native APIs, Altair, and configurable columns.

Core Features & Use Cases

  • Native charts: line, bar, area, and scatter charts using st.line_chart, st.bar_chart, st.area_chart, and st.scatter_chart.
  • Dataframe configuration: apply column_config to format numbers, dates, and sparklines for quick insights.
  • KPI metrics: use st.metric with optional sparklines to display key indicators.
  • Altair integration: create custom charts when more control is needed, then render with st.altair_chart.

Quick Start

To start, create a simple Streamlit app and render a line chart using st.line_chart with your dataframe.

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 dataframes and charts in a Streamlit dashboard?▼

To display dataframes and charts in a Streamlit dashboard, use native APIs like st.line_chart, st.bar_chart, and st.dataframe. You can format dataframe columns and add sparklines using column_config to communicate data insights clearly.

Can I add sparklines to Streamlit metrics and dataframes?▼

Yes, you can add sparklines to Streamlit metrics and dataframes. Use st.metric with optional sparklines for KPI indicators, or apply column_config to st.dataframe to format numbers, dates, and embed sparklines for quick visual insights.

What is the best way to create custom data visualizations in Streamlit?▼

The best way to create custom data visualizations in Streamlit is using Altair integration. Build custom charts for advanced control over your data visualization, then render them directly in your app using the st.altair_chart API.

Does Streamlit support rendering line, bar, area, and scatter charts natively?▼

Yes, Streamlit supports rendering line, bar, area, and scatter charts natively. You can quickly generate these visualizations from your raw data using the st.line_chart, st.bar_chart, st.area_chart, and st.scatter_chart APIs.

How do I configure dataframe columns to format numbers and dates in Streamlit?▼

You configure dataframe columns to format numbers and dates in Streamlit by using the column_config parameter with st.dataframe. This allows you to apply specific formatting rules and add sparklines directly within the table display.

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